Time-series forecasting
This page was last updated on 2024-07-17 08:45:06 UTC
Manually curated articles on Time-series forecasting
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
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visibility_off | A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection | Ming Jin, Huan Yee Koh, Qingsong Wen, Daniele Zambon, C. Alippi, G. I. Webb, Irwin King, Shirui Pan | 2023-07-07 | arXiv.org, ArXiv | 51 | 49 | open_in_new |
visibility_off | Graph-Guided Network for Irregularly Sampled Multivariate Time Series | Xiang Zhang, M. Zeman, Theodoros Tsiligkaridis, M. Zitnik | 2021-10-11 | International Conference on Learning Representations, ArXiv | 65 | 46 | open_in_new |
visibility_off | Taming Local Effects in Graph-based Spatiotemporal Forecasting | Andrea Cini, Ivan Marisca, Daniele Zambon, C. Alippi | 2023-02-08 | Neural Information Processing Systems, ArXiv | 14 | 49 | open_in_new |
visibility_off | Sparse Graph Learning from Spatiotemporal Time Series | Andrea Cini, Daniele Zambon, C. Alippi | 2022-05-26 | J. Mach. Learn. Res., Journal of machine learning research | 10 | 49 | open_in_new |
visibility_off | Graph Deep Learning for Time Series Forecasting | Andrea Cini, Ivan Marisca, Daniele Zambon, C. Alippi | 2023-10-24 | arXiv.org, ArXiv | 4 | 49 | open_in_new |
visibility_off | Large Language Models Are Zero-Shot Time Series Forecasters | Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson | 2023-10-11 | Neural Information Processing Systems, ArXiv | 110 | 14 | open_in_new |
visibility_off | Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces | Chloe X. Wang, Oleksii Tsepa, Jun Ma, Bo Wang | 2024-02-01 | arXiv.org, ArXiv | 43 | 7 | open_in_new |
visibility_off | A decoder-only foundation model for time-series forecasting | Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou | 2023-10-14 | arXiv.org, ArXiv | 41 | 14 | open_in_new |
visibility_off | Unified Training of Universal Time Series Forecasting Transformers | Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo | 2024-02-04 | arXiv.org, ArXiv | 24 | 22 | open_in_new |
visibility_off | Time-LLM: Time Series Forecasting by Reprogramming Large Language Models | Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, X. Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen | 2023-10-03 | arXiv.org, ArXiv | 104 | 9 | open_in_new |
visibility_off | Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series | Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam | 2024-01-08 | arXiv.org, ArXiv | 2 | 2 | open_in_new |
visibility_off | Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency | Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, M. Zitnik | 2022-06-17 | Neural Information Processing Systems, ArXiv | 145 | 46 | open_in_new |
visibility_off | Domain Adaptation for Time Series Under Feature and Label Shifts | Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, M. Zitnik | 2023-02-06 | DBLP, ArXiv | 21 | 46 | open_in_new |
visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | DBLP | 6 | 49 | open_in_new |
visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | arXiv.org, ArXiv | 3 | 49 | open_in_new |
visibility_off | UNITS: A Unified Multi-Task Time Series Model | Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, M. Zitnik | 2024-02-29 | ArXiv | 2 | 46 | open_in_new |
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
Recommended articles on Time-series forecasting
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |
---|---|---|---|---|---|---|
visibility_off | ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks | Wanlin Cai, Kun Wang, Hao Wu, Xiaoxu Chen, Yuankai Wu | 2024-05-28 | ArXiv | 0 | 3 |
visibility_off | TimeCMA: Towards LLM-Empowered Time Series Forecasting via Cross-Modality Alignment | Chenxi Liu, Qianxiong Xu, Hao Miao, Sun Yang, Lingzheng Zhang, Cheng Long, Ziyue Li, Rui Zhao | 2024-06-03 | ArXiv | 1 | 4 |
visibility_off | NuwaTS: a Foundation Model Mending Every Incomplete Time Series | Jinguo Cheng, Chunwei Yang, Wanlin Cai, Yuxuan Liang, Yuankai Wu | 2024-05-24 | ArXiv | 0 | 3 |
visibility_off | Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting | Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang | 2024-05-23 | ArXiv | 0 | 6 |
visibility_off | DeepHGNN: Study of Graph Neural Network based Forecasting Methods for Hierarchically Related Multivariate Time Series | Abishek Sriramulu, Nicolas Fourrier, Christoph Bergmeir | 2024-05-29 | ArXiv | 0 | 4 |
visibility_off | UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting | Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo | 2024-06-07 | ArXiv | 0 | 22 |
visibility_off | Are Self-Attentions Effective for Time Series Forecasting? | Dongbin Kim, Jinseong Park, Jaewook Lee, Hoki Kim | 2024-05-27 | ArXiv | 0 | 7 |
visibility_off | Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting | Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. A. Prakash | 2024-07-02 | ArXiv | 0 | 9 |
visibility_off | ROSE: Register Assisted General Time Series Forecasting with Decomposed Frequency Learning | Yihang Wang, Yuying Qiu, Peng Chen, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo | 2024-05-24 | ArXiv | 0 | 26 |
visibility_off | MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting | Xiuding Cai, Yaoyao Zhu, Xueyao Wang, Yu Yao | 2024-05-26 | ArXiv | 0 | 2 |
visibility_off | SiamTST: A Novel Representation Learning Framework for Enhanced Multivariate Time Series Forecasting applied to Telco Networks | S. Kristoffersen, Peter Skaar Nordby, Sara Malacarne, Massimiliano Ruocco, Pablo Ortiz | 2024-07-02 | ArXiv | 0 | 0 |
visibility_off | Are Language Models Actually Useful for Time Series Forecasting? | Mingtian Tan, Mike A. Merrill, Vinayak Gupta, Tim Althoff, Tom Hartvigsen | 2024-06-22 | ArXiv | 0 | 3 |
visibility_off | Prompt-Enhanced Spatio-Temporal Graph Transfer Learning | Junfeng Hu, Xu Liu, Zhencheng Fan, Yifang Yin, Shili Xiang, Savitha Ramasamy, Roger Zimmermann | 2024-05-21 | ArXiv | 0 | 16 |
visibility_off | SpoT-Mamba: Learning Long-Range Dependency on Spatio-Temporal Graphs with Selective State Spaces | Jinhyeok Choi, Heehyeon Kim, Minhyeong An, Joyce Jiyoung Whang | 2024-06-17 | ArXiv | 0 | 1 |
visibility_off | MSegRNN:Enhanced SegRNN Model with Mamba for Long-Term Time Series Forecasting | GaoXiang Zhao, Xiaoqiang Wang | 2024-07-15 | ArXiv | 0 | 0 |
visibility_off | Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting | Jiarui Yang, Tao Dai, Naiqi Li, Junxi Wu, Peiyuan Liu, Jinmin Li, Jigang Bao, Haigang Zhang, Shutao Xia | 2024-06-04 | ArXiv | 0 | 3 |
visibility_off | Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla Transformers | Xin Cheng, Xiuying Chen, Shuqi Li, Di Luo, Xun Wang, Dongyan Zhao, Rui Yan | 2024-05-22 | ArXiv | 0 | 7 |
visibility_off | Time Series Representation Models | Robert Leppich, Vanessa Borst, Veronika Lesch, Samuel Kounev | 2024-05-28 | ArXiv | 0 | 9 |
visibility_off | C-Mamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting | Chaolv Zeng, Zhanyu Liu, Guanjie Zheng, Linghe Kong | 2024-06-08 | ArXiv | 1 | 5 |
visibility_off | xLSTMTime : Long-term Time Series Forecasting With xLSTM | Musleh Alharthi, Ausif Mahmood | 2024-07-14 | ArXiv | 0 | 0 |
visibility_off | Sparse transformer with local and seasonal adaptation for multivariate time series forecasting | Yifan Zhang, Rui Wu, S. Dascalu, Frederick C. Harris | 2024-07-10 | Scientific Reports | 0 | 18 |
visibility_off | Toto: Time Series Optimized Transformer for Observability | Ben Cohen, E. Khwaja, Kan Wang, Charles Masson, Elise Ram'e, Youssef Doubli, Othmane Abou-Amal | 2024-07-10 | ArXiv | 0 | 4 |
visibility_off | Understanding Different Design Choices in Training Large Time Series Models | Yu-Neng Chuang, Songchen Li, Jiayi Yuan, Guanchu Wang, Kwei-Herng Lai, Leisheng Yu, Sirui Ding, Chia-yuan Chang, Qiaoyu Tan, D. Zha, Xia Hu | 2024-06-20 | ArXiv | 0 | 22 |
visibility_off | A Pure Transformer Pretraining Framework on Text-attributed Graphs | Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei-dong Jin, Carl Yang, Jiliang Tang, Hui Liu | 2024-06-19 | ArXiv | 0 | 9 |
visibility_off | In-context Time Series Predictor | Jiecheng Lu, Yan Sun, Shihao Yang | 2024-05-23 | ArXiv | 0 | 1 |
visibility_off | A Scalable and Effective Alternative to Graph Transformers | Kaan Sancak, Zhigang Hua, Jin Fang, Yan Xie, Andrey Malevich, Bo Long, M. F. Balin, Umit V. cCatalyurek | 2024-06-17 | ArXiv | 0 | 6 |
visibility_off | VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting | Yingnan Yang, Qingling Zhu, Jianyong Chen | 2024-05-19 | ArXiv | 0 | 9 |
visibility_off | Omni-Dimensional Frequency Learner for General Time Series Analysis | Xianing Chen.Hanting Chen, Hailin Hu | 2024-07-15 | ArXiv | 0 | 0 |
visibility_off | DeformTime: Capturing Variable Dependencies with Deformable Attention for Time Series Forecasting | Yuxuan Shu, Vasileios Lampos | 2024-06-11 | ArXiv | 0 | 24 |
visibility_off | TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting | Shiyu Wang, Haixu Wu, X. Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou | 2024-05-23 | ArXiv | 13 | 13 |
visibility_off | TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecasting | Jiaxi Hu, Qingsong Wen, Sijie Ruan, Li Liu, Yuxuan Liang | 2024-06-06 | ArXiv | 1 | 5 |
visibility_off | MGCP: A Multi-Grained Correlation based Prediction Network for Multivariate Time Series | Zhicheng Chen, Xi Xiao, Ke Xu, Zhong Zhang, Yu Rong, Qing Li, Guojun Gan, Zhiqiang Xu, Peilin Zhao | 2024-05-30 | ArXiv | 0 | 1 |
visibility_off | Multiple-Resolution Tokenization for Time Series Forecasting with an Application to Pricing | Egon Pervsak, Miguel F. Anjos, Sebastian Lautz, Aleksandar Kolev | 2024-07-03 | ArXiv | 0 | 0 |
visibility_off | Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks | Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo | 2024-05-29 | ArXiv | 0 | 17 |
visibility_off | Efficient Time Series Processing for Transformers and State-Space Models through Token Merging | Leon Götz, Marcel Kollovieh, Stephan Günnemann, Leo Schwinn | 2024-05-28 | ArXiv | 0 | 7 |
visibility_off | FAITH: Frequency-domain Attention In Two Horizons for Time Series Forecasting | Ruiqi Li, Maowei Jiang, Kai Wang, Kaiduo Feng, Quangao Liu, Yue Sun, Xiufang Zhou | 2024-05-22 | ArXiv | 0 | 2 |
visibility_off | What Can We Learn from State Space Models for Machine Learning on Graphs? | Yinan Huang, Siqi Miao, Pan Li | 2024-06-09 | ArXiv | 0 | 2 |
visibility_off | Large language models can be zero-shot anomaly detectors for time series? | Sarah Alnegheimish, Linh Nguyen, Laure Berti-Equille, K. Veeramachaneni | 2024-05-23 | ArXiv | 1 | 33 |
visibility_off | FTMixer: Frequency and Time Domain Representations Fusion for Time Series Modeling | Zhengnan Li, Yunxiao Qin, Xilong Cheng, Yuting Tan | 2024-05-24 | ArXiv | 0 | 0 |
visibility_off | Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach | Difan Deng, Marius Lindauer | 2024-06-07 | ArXiv | 0 | 6 |
visibility_off | Performance Evaluation of Sequence Model Architectures for Load Forecasting: A Comparative Study | G. Sideratos, A. Dimeas, N. Hatziargyriou | 2024-05-20 | 2024 International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation (AIE) | 0 | 11 |
visibility_off | Beyond Trend and Periodicity: Guiding Time Series Forecasting with Textual Cues | Zhijian Xu, Yuxuan Bian, Jianyuan Zhong, Xiangyu Wen, Qiang Xu | 2024-05-22 | ArXiv | 0 | 3 |
visibility_off | Fine-grained Attention in Hierarchical Transformers for Tabular Time-series | Raphaël Azorin, Z. B. Houidi, Massimo Gallo, A. Finamore, Pietro Michiardi | 2024-06-21 | ArXiv | 0 | 24 |
visibility_off | Score-CDM: Score-Weighted Convolutional Diffusion Model for Multivariate Time Series Imputation | S. Zhang, S. Wang, H. Miao, H. Chen, C. Fan, J. Zhang | 2024-05-21 | ArXiv | 0 | 10 |
visibility_off | Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Models | Litton J. Kurisinkel, Pruthwik Mishra, Yue Zhang | 2024-07-04 | ArXiv | 0 | 5 |
visibility_off | HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model | Zhenyu Pan, Yoonsung Jeong, Xiaoda Liu, Han Liu | 2024-05-22 | ArXiv | 0 | 2 |
visibility_off | Generalizing Graph Transformers Across Diverse Graphs and Tasks via Pre-Training on Industrial-Scale Data | Yufei He, Zhenyu Hou, Yukuo Cen, Feng He, Xu Cheng, Bryan Hooi | 2024-07-04 | ArXiv | 0 | 12 |
visibility_off | Learning Long Range Dependencies on Graphs via Random Walks | Dexiong Chen, Till Hendrik Schulz, Karsten Borgwardt | 2024-06-05 | ArXiv | 0 | 8 |
visibility_off | ARC: A Generalist Graph Anomaly Detector with In-Context Learning | Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Shirui Pan | 2024-05-27 | ArXiv | 0 | 8 |
visibility_off | A Temporal Kolmogorov-Arnold Transformer for Time Series Forecasting | Remi Genet, Hugo Inzirillo | 2024-06-04 | ArXiv | 5 | 1 |
visibility_off | Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models | Ali Behrouz, Michele Santacatterina, Ramin Zabih | 2024-06-06 | ArXiv | 0 | 8 |
visibility_off | Adaptive Convolutional Forecasting Network Based on Time Series Feature-Driven | Dandan Zhang, Zhiqiang Zhang, Nanguang Chen, Yun Wang | 2024-05-20 | ArXiv | 0 | 1 |
visibility_off | Deep-Graph-Sprints: Accelerated Representation Learning in Continuous-Time Dynamic Graphs | Ahmad Naser Eddin, Jacopo Bono, David Apar'icio, Hugo Ferreira, Pedro Ribeiro, P. Bizarro | 2024-07-10 | ArXiv | 0 | 17 |
visibility_off | Segment, Shuffle, and Stitch: A Simple Mechanism for Improving Time-Series Representations | Shivam Grover, Amin Jalali, Ali Etemad | 2024-05-30 | ArXiv | 0 | 1 |
visibility_off | Large Language Models as Event Forecasters | Libo Zhang, Yue Ning | 2024-06-15 | ArXiv | 0 | 0 |
visibility_off | Efficient Neural Common Neighbor for Temporal Graph Link Prediction | Xiaohui Zhang, Yanbo Wang, Xiyuan Wang, Muhan Zhang | 2024-06-12 | ArXiv | 0 | 6 |
visibility_off | Towards Neural Scaling Laws for Foundation Models on Temporal Graphs | Razieh Shirzadkhani, Tran Gia Bao Ngo, Kiarash Shamsi, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, C. Akcora | 2024-06-14 | ArXiv | 0 | 19 |
visibility_off | Hierarchical Classification Auxiliary Network for Time Series Forecasting | Yanru Sun, Zongxia Xie, Dongyue Chen, Emadeldeen Eldele, Qinghua Hu | 2024-05-29 | ArXiv | 0 | 17 |
visibility_off | Timeless Foundations: Exploring DC-VAEs as Foundation Models for Time Series Analysis | Gastón García González, P. Casas, Emilio Martínez, Alicia Fernández | 2024-05-21 | 2024 8th Network Traffic Measurement and Analysis Conference (TMA) | 0 | 4 |
visibility_off | TDT Loss Takes It All: Integrating Temporal Dependencies among Targets into Non-Autoregressive Time Series Forecasting | Qi Xiong, Kai Tang, Minbo Ma, Jie Xu, Tianrui Li | 2024-06-07 | ArXiv | 0 | 4 |
visibility_off | Scalable Numerical Embeddings for Multivariate Time Series: Enhancing Healthcare Data Representation Learning | Chun-Kai Huang, Yi-Hsien Hsieh, Ta-Jung Chien, Li-Cheng Chien, Shao-Hua Sun, T. Su, J. Kao, Che Lin | 2024-05-26 | ArXiv | 0 | 87 |
visibility_off | Rough Transformers: Lightweight Continuous-Time Sequence Modelling with Path Signatures | Fernando Moreno-Pino, Alvaro Arroyo, H. Waldon, Xiaowen Dong, Álvaro Cartea | 2024-05-31 | ArXiv | 0 | 5 |
visibility_off | TimeSieve: Extracting Temporal Dynamics through Information Bottlenecks | Ninghui Feng, Songning Lai, Fobao Zhou, Zhenxiao Yin, Hang Zhao | 2024-06-07 | ArXiv | 0 | 2 |
visibility_off | Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting | Wei Fan, Kun Yi, Hangting Ye, Zhiyuan Ning, Qi Zhang, Ning An | 2024-06-29 | ArXiv | 0 | 3 |
visibility_off | Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning | Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. A. Prakash | 2024-06-13 | ArXiv | 0 | 9 |
visibility_off | Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity | Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. A. Prakash | 2024-07-02 | ArXiv | 0 | 7 |
visibility_off | Capturing Temporal Components for Time Series Classification | Venkata Ragavendra Vavilthota, Ranjith Ramanathan, Sathyanarayanan N. Aakur | 2024-06-20 | ArXiv | 0 | 7 |
visibility_off | Long Range Propagation on Continuous-Time Dynamic Graphs | Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio, Davide Bacciu, Claas Grohnfeldt | 2024-06-04 | ArXiv | 0 | 10 |
visibility_off | Attention as an RNN | Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Mohamed Osama Ahmed, Y. Bengio, Greg Mori | 2024-05-22 | ArXiv | 0 | 40 |
visibility_off | MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMs | Georgios Chatzigeorgakidis, Konstantinos Lentzos, Dimitrios Skoutas | 2024-05-13 | 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW) | 0 | 7 |
visibility_off | Kolmogorov-Arnold Networks for Time Series: Bridging Predictive Power and Interpretability | Kunpeng Xu, Lifei Chen, Shengrui Wang | 2024-06-04 | ArXiv | 7 | 4 |
visibility_off | F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data | Zexing Xu, Linjun Zhang, Sitan Yang, Rasoul Etesami, Hanghang Tong, Huan Zhang, Jiawei Han | 2024-06-23 | ArXiv | 0 | 1 |
visibility_off | Scaling-laws for Large Time-series Models | Thomas D. P. Edwards, James Alvey, Justin Alsing, Nam H. Nguyen, B. Wandelt | 2024-05-22 | ArXiv | 0 | 98 |
visibility_off | Time-series representation learning via Time-Frequency Fusion Contrasting | Wenbo Zhao, Ling Fan | 2024-06-12 | Frontiers in Artificial Intelligence | 0 | 1 |
visibility_off | BiLSTM-MLAM: A Multi-Scale Time Series Prediction Model for Sensor Data Based on Bi-LSTM and Local Attention Mechanisms | Yongxin Fan, Qian Tang, Yangming Guo, Yifei Wei | 2024-06-01 | Sensors (Basel, Switzerland) | 0 | 1 |
visibility_off | EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation | Yuda Wang, Xuxin He, Shengxin Zhu | 2024-06-04 | ArXiv | 1 | 1 |
visibility_off | Membership Inference Attacks Against Time-Series Models | Noam Koren, Abigail Goldsteen, Ariel Farkash, Guy Amit | 2024-07-03 | ArXiv | 0 | 8 |
visibility_off | Slot State Space Models | Jindong Jiang, Fei Deng, Gautam Singh, Minseung Lee, Sungjin Ahn | 2024-06-18 | ArXiv | 0 | 10 |
visibility_off | Mamba Hawkes Process | Anningzhe Gao, Shan Dai, Yan Hu | 2024-07-07 | ArXiv | 0 | 1 |
visibility_off | Probability Passing for Graph Neural Networks: Graph Structure and Representations Joint Learning | Ziteng Wang, YaXuan He, Bin Liu | 2024-07-15 | ArXiv | 0 | 14 |
visibility_off | CGAP: Urban Region Representation Learning with Coarsened Graph Attention Pooling | Zhuo Xu, Xiao Zhou | 2024-07-02 | ArXiv | 0 | 0 |
visibility_off | Neighbor-enhanced Representation Learning for Link Prediction in Dynamic Heterogeneous Attributed Networks | Xiangyu Wei, Wei Wang, Chongsheng Zhang, Weiping Ding, Bin Wang, Yaguan Qian, Zhen Han, Chunhua Su | 2024-07-04 | ACM Transactions on Knowledge Discovery from Data | 0 | 11 |
visibility_off | Boosting X-formers with Structured Matrix for Long Sequence Time Series Forecasting | Zhicheng Zhang, Yong Wang, Shaoqi Tan, Bowei Xia, Yujie Luo, | 2024-05-21 | ArXiv | 0 | 3 |
visibility_off | SFANet: Spatial-Frequency Attention Network for Weather Forecasting | Jiaze Wang, Hao Chen, Hongcan Xu, Jinpeng Li, Bo-Lan Wang, Kun Shao, Furui Liu, Huaxi Chen, Guangyong Chen, P. Heng | 2024-05-29 | ArXiv | 0 | 3 |
visibility_off | ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification | Xuan-May Le, Ling Luo, Uwe Aickelin, Minh-Tuan Tran | 2024-05-23 | ArXiv | 0 | 2 |
visibility_off | Interpretable Multivariate Time Series Forecasting Using Neural Fourier Transform | Noam Koren, Kira Radinsky | 2024-05-22 | ArXiv | 1 | 24 |
visibility_off | Long Short-term Cognitive Networks: An Empirical Performance Study | Gonzalo Nápoles, Isel Grau | 2024-05-23 | 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) | 0 | 13 |
visibility_off | PDMLP: Patch-based Decomposed MLP for Long-Term Time Series Forecasting | Peiwang Tang, Weitai Zhang | 2024-05-22 | ArXiv | 0 | 0 |
visibility_off | Forecasting with Deep Learning: Beyond Average of Average of Average Performance | Vítor Cerqueira, Luis Roque, Carlos Soares | 2024-06-24 | ArXiv | 0 | 13 |
visibility_off | Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting | Yuansan Liu, S. Wijewickrema, Dongting Hu, C. Bester, Stephen O'Leary, James Bailey | 2024-06-05 | ArXiv | 0 | 15 |
visibility_off | Structure-aware Semantic Node Identifiers for Learning on Graphs | Yuankai Luo, Qijiong Liu, Lei Shi, Xiao-Ming Wu | 2024-05-26 | ArXiv | 1 | 5 |
visibility_off | Improving global awareness of linkset predictions using Cross-Attentive Modulation tokens | Félix Marcoccia, C. Adjih, P. Mühlethaler | 2024-05-28 | ArXiv | 0 | 23 |
visibility_off | ViTime: A Visual Intelligence-Based Foundation Model for Time Series Forecasting | Luoxiao Yang, Yun Wang, Xinqi Fan, Israel Cohen, Yue Zhao, Zijun Zhang | 2024-07-10 | ArXiv | 0 | 8 |
visibility_off | Efficient and Effective Implicit Dynamic Graph Neural Network | Yongjian Zhong, Hieu Vu, Tianbao Yang, Bijaya Adhikari | 2024-06-25 | ArXiv | 0 | 4 |
visibility_off | A Language Model-Guided Framework for Mining Time Series with Distributional Shifts | Haibei Zhu, Yousef El-Laham, Elizabeth Fons, Svitlana Vyetrenko | 2024-06-07 | ArXiv | 0 | 7 |
visibility_off | Improving Time-Series Forecasting Performance Using Imputation Techniques in Deep Learning | Agung Bella, Putra Utama, Wahyu Sakti, Gunawan Irianto, A. Wibawa, A. N. Handayani, Amat Nyoto | 2024-06-06 | 2024 International Conference on Smart Computing, IoT and Machine Learning (SIML) | 0 | 15 |
visibility_off | Rethinking Independent Cross-Entropy Loss For Graph-Structured Data | Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang, Xin Wang | 2024-05-24 | ArXiv | 0 | 5 |
visibility_off | Repeat-Aware Neighbor Sampling for Dynamic Graph Learning | Tao Zou, Yuhao Mao, Junchen Ye, Bo Du | 2024-05-24 | ArXiv | 0 | 6 |
visibility_off | Contaminant Transport Modeling and Source Attribution With Attention‐Based Graph Neural Network | Min Pang, E. Du, Chunmiao Zheng | 2024-06-01 | Water Resources Research | 0 | 11 |
visibility_off | Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting | Sanghyun Lee, Chanyoung Park | 2024-06-04 | ArXiv | 0 | 0 |
visibility_off | UnitNorm: Rethinking Normalization for Transformers in Time Series | Nan Huang, C. Kümmerle, Xiang Zhang | 2024-05-24 | ArXiv | 0 | 5 |
visibility_off | Efficient Topology-aware Data Augmentation for High-Degree Graph Neural Networks | Yurui Lai, Xiaoyang Lin, Renchi Yang, Hongtao Wang | 2024-06-08 | ArXiv | 0 | 10 |
visibility_off | TimeAutoDiff: Combining Autoencoder and Diffusion model for time series tabular data synthesizing | Namjoon Suh, Yuning Yang, Din-Yin Hsieh, Qitong Luan, Shirong Xu, Shixiang Zhu, Guang Cheng | 2024-06-23 | ArXiv | 0 | 3 |
visibility_off | Stock Movement Prediction with Multimodal Stable Fusion via Gated Cross-Attention Mechanism | Chang Zong, Jian Shao, Weiming Lu, Yueting Zhuang | 2024-06-06 | ArXiv | 0 | 2 |
visibility_off | CEEMD-based Multivariate Financial Time Series Forecasting using a Temporal Fusion Transformer | Raymond Ho, Kevin Hung | 2024-05-24 | 2024 IEEE 14th Symposium on Computer Applications & Industrial Electronics (ISCAIE) | 0 | 3 |
visibility_off | Integrating gated recurrent unit in graph neural network to improve infectious disease prediction: an attempt | Xu-dong Liu, Bo-han Hou, Zhong-jun Xie, Ning Feng, Xiao−ping Dong | 2024-05-20 | Frontiers in Public Health | 0 | 1 |
visibility_off | From Link Prediction to Forecasting: Information Loss in Batch-based Temporal Graph Learning | Moritz Lampert, Christopher Blöcker, Ingo Scholtes | 2024-06-07 | ArXiv | 0 | 1 |
visibility_off | Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers | Chao Lou, Zixia Jia, Zilong Zheng, Kewei Tu | 2024-06-24 | ArXiv | 0 | 21 |
visibility_off | GraphFM: A Comprehensive Benchmark for Graph Foundation Model | Yuhao Xu, Xinqi Liu, Keyu Duan, Yi Fang, Yu-Neng Chuang, D. Zha, Qiaoyu Tan | 2024-06-12 | ArXiv | 0 | 22 |
visibility_off | NFCL: Simply interpretable neural networks for a short-term multivariate forecasting | Wonkeun Jo, Dongil Kim | 2024-05-22 | ArXiv | 0 | 5 |
visibility_off | FPN-fusion: Enhanced Linear Complexity Time Series Forecasting Model | Chu Li, Bingjia Xiao, Q. Yuan | 2024-06-06 | ArXiv | 0 | 1 |
visibility_off | LLM-based Knowledge Pruning for Time Series Data Analytics on Edge-computing Devices | Ruibing Jin, Qing Xu, Min Wu, Yuecong Xu, Dan Li, Xiaoli Li, Zhenghua Chen | 2024-06-13 | ArXiv | 0 | 13 |
visibility_off | Machine Learning-Enhanced Pairs Trading | Eli Hadad, Sohail Hodarkar, Beakal Lemeneh, Dennis Shasha | 2024-06-11 | Forecasting | 0 | 0 |
visibility_off | Unilateral boundary time series forecasting | Chao-Min Chang, Cheng-Te Li, Shou-de Lin | 2024-06-05 | Frontiers in Big Data | 0 | 2 |
visibility_off | Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection | Junqi Chen, Xu Tan, S. Rahardja, Jiawei Yang, S. Rahardja | 2024-05-30 | ArXiv | 0 | 37 |
visibility_off | Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting | Jiaxi Hu, Disen Lan, Ziyu Zhou, Qingsong Wen, Yuxuan Liang | 2024-05-25 | ArXiv | 2 | 5 |
visibility_off | ContrAttNet: Contribution and attention approach to multivariate time-series data imputation. | Yunfei Yin, Caihao Huang, Xianjian Bao | 2024-06-03 | Network | 0 | 2 |
visibility_off | Many-to-Many Prediction for Effective Modeling of Frequent Label Transitions in Time Series | Alexander Katrompas, V. Metsis | 2024-06-26 | Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments | 0 | 17 |
visibility_off | Foundations and Frontiers of Graph Learning Theory | Yu Huang, Min Zhou, Menglin Yang, Zhen Wang, Muhan Zhang, Jie Wang, Hong Xie, Hao Wang, Defu Lian, Enhong Chen | 2024-07-03 | ArXiv | 0 | 37 |
visibility_off | Dynamic Spatial-Temporal Embedding via Neural Conditional Random Field for Multivariate Time Series Forecasting | Peiyu Yi, Feihu Huang, Jian Peng, Zhifeng Bao | 2024-06-27 | ACM Transactions on Spatial Algorithms and Systems | 0 | 3 |
visibility_off | TimeLDM: Latent Diffusion Model for Unconditional Time Series Generation | Jian Qian, Miao Sun, Sifan Zhou, Biao Wan, Minhao Li, Patrick Chiang | 2024-07-05 | ArXiv | 0 | 0 |
visibility_off | State Space Models on Temporal Graphs: A First-Principles Study | Jintang Li, Ruofan Wu, Xinzhou Jin, Boqun Ma, Liang Chen, Zibin Zheng | 2024-06-03 | ArXiv | 0 | 10 |
visibility_off | Deep learning for precipitation nowcasting: A survey from the perspective of time series forecasting | Sojung An, Tae-Jin Oh, Eunha Sohn, Donghyun Kim | 2024-06-07 | ArXiv | 0 | 1 |
visibility_off | In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs | Grzegorz Kaszuba, Amirhossein D. Naghdi, Dario Massa, Stefanos Papanikolaou, Andrzej Jaszkiewicz, Piotr Sankowski | 2024-06-03 | ArXiv | 0 | 2 |
visibility_off | Frequency-Enhanced Transformer with Symmetry-Based Lightweight Multi-Representation for Multivariate Time Series Forecasting | Chenyue Wang, Zhouyuan Zhang, Xin Wang, Mingyang Liu, Lin Chen, Jiatian Pi | 2024-06-25 | Symmetry | 0 | 1 |
visibility_off | GraphAny: A Foundation Model for Node Classification on Any Graph | Jianan Zhao, Hesham Mostafa, Mikhail Galkin, Michael Bronstein, Zhaocheng Zhu, Jian Tang | 2024-05-30 | ArXiv | 3 | 19 |
visibility_off | Inference of Sequential Patterns for Neural Message Passing in Temporal Graphs | J. V. Pichowski, Vincenzo Perri, Lisi Qarkaxhija, Ingo Scholtes | 2024-06-24 | ArXiv | 0 | 8 |
visibility_off | Latent Conditional Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Mode | Yuxing Tian, Yiyan Qi, Aiwen Jiang, Qi Huang, Jian Guo | 2024-07-11 | ArXiv | 0 | 2 |
visibility_off | Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns | Haoren Zhu, Pengfei Zhao, NG WilfredSiuHung, Dik Lun Lee | 2024-06-13 | ArXiv | 0 | 2 |
visibility_off | Kolmogorov-Arnold Graph Neural Networks | Gianluca De Carlo, A. Mastropietro, Aris Anagnostopoulos | 2024-06-26 | ArXiv | 0 | 4 |
visibility_off | Temporal Graph Rewiring with Expander Graphs | Katarina Petrovi'c, Shenyang Huang, Farimah Poursafaei, Petar Velickovic | 2024-06-04 | ArXiv | 0 | 2 |
visibility_off | Scaling Law for Time Series Forecasting | Jingzhe Shi, Qinwei Ma, Huan Ma, Lei Li | 2024-05-24 | ArXiv | 1 | 1 |
visibility_off | Synergistic Deep Graph Clustering Network | Benyu Wu, Shifei Ding, Xiao Xu, Lili Guo, Ling Ding, Xindong Wu | 2024-06-22 | ArXiv | 0 | 11 |
visibility_off | Reinforced Decoder: Towards Training Recurrent Neural Networks for Time Series Forecasting | Qi Sima, Xinze Zhang, Yukun Bao, Siyue Yang, Liang Shen | 2024-06-14 | ArXiv | 0 | 0 |
visibility_off | SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic Graphs | Lanting Fang, Yulian Yang, Kai Wang, Shanshan Feng, Kaiyu Feng, Jie Gui, Shuliang Wang, Y. Ong | 2024-05-29 | ArXiv | 0 | 2 |
visibility_off | Pay Attention to Weak Ties: A Heterogeneous Multiplex Representation Learning Framework for Link Prediction | Weiwei Gu, Linbi Lv, Gang Lu, Ruiqi Li | 2024-06-15 | ArXiv | 0 | 0 |
visibility_off | Enhanced Spatiotemporal Prediction Using Physical-guided And Frequency-enhanced Recurrent Neural Networks | Xuanle Zhao, Yue Sun, Tielin Zhang, Bo Xu | 2024-05-23 | ArXiv | 0 | 15 |
visibility_off | Towards Faster Deep Graph Clustering via Efficient Graph Auto-Encoder | Shifei Ding, Benyu Wu, Ling Ding, Xiao Xu, Lili Guo, Hongmei Liao, Xindong Wu | 2024-06-28 | ACM Transactions on Knowledge Discovery from Data | 0 | 11 |
visibility_off | A Multi-Graph Convolutional Neural Network Model for Short-Term Prediction of Turning Movements at Signalized Intersections | Jewel Rana Palit, Osama A Osman | 2024-06-02 | ArXiv | 0 | 1 |
visibility_off | Correlation-enhanced Dynamic Graph Learning for Temporal Link Prediction | Junzhe Chen, Zhiqiang Pan, Honghui Chen | 2024-05-23 | 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) | 0 | 6 |
visibility_off | A Unified Implicit Attention Formulation for Gated-Linear Recurrent Sequence Models | Itamar Zimerman, Ameen Ali, Lior Wolf | 2024-05-26 | ArXiv | 1 | 4 |
visibility_off | Unleash Graph Neural Networks from Heavy Tuning | Lequan Lin, Dai Shi, Andi Han, Zhiyong Wang, Junbin Gao | 2024-05-21 | ArXiv | 0 | 7 |
visibility_off | Transformer Conformal Prediction for Time Series | Junghwan Lee, Chen Xu, Yao Xie | 2024-06-08 | ArXiv | 0 | 7 |
visibility_off | Deep Temporal Deaggregation: Large-Scale Spatio-Temporal Generative Models | David Bergstrom, Mattias Tiger, Fredrik Heintz | 2024-06-18 | ArXiv | 0 | 6 |
visibility_off | Dynamic Context Adaptation and Information Flow Control in Transformers: Introducing the Evaluator Adjuster Unit and Gated Residual Connections | Sahil Rajesh Dhayalkar | 2024-05-22 | ArXiv | 0 | 0 |
visibility_off | A TCN-Linear Hybrid Model for Chaotic Time Series Forecasting | Mengjiao Wang, Fengtai Qin | 2024-05-29 | Entropy | 0 | 14 |
visibility_off | Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks | Yuwen Wang, Shunyu Liu, Tongya Zheng, Kaixuan Chen, Mingli Song | 2024-07-02 | ArXiv | 0 | 7 |
visibility_off | DAGER: Exact Gradient Inversion for Large Language Models | Ivo Petrov, D. I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev | 2024-05-24 | ArXiv | 0 | 54 |
visibility_off | Discrete-state Continuous-time Diffusion for Graph Generation | Zhe Xu, Ruizhong Qiu, Yuzhong Chen, Huiyuan Chen, Xiran Fan, Menghai Pan, Zhichen Zeng, Mahashweta Das, Hanghang Tong | 2024-05-19 | ArXiv | 0 | 4 |
visibility_off | Conditional Shift-Robust Conformal Prediction for Graph Neural Network | Akansha Agrawal | 2024-05-20 | ArXiv | 0 | 0 |
visibility_off | Anomaly Detection in Dynamic Graphs: A Comprehensive Survey | Ocheme Anthony Ekle, William Eberle | 2024-05-29 | ACM Transactions on Knowledge Discovery from Data | 0 | 0 |
visibility_off | Spatial-temporal Attention Model Based on Transformer Architecture for Anomaly Detection in Multivariate Time Series Data | Lai Zeng Lai Zeng, Xiaomei Yang Lai Zeng | 2024-06-01 | 電腦學刊 | 0 | 0 |
visibility_off | Attending to Topological Spaces: The Cellular Transformer | Rubén Ballester, Pablo Hern'andez-Garc'ia, Mathilde Papillon, Claudio Battiloro, Nina Miolane, Tolga Birdal, Carles Casacuberta, Sergio Escalera, Mustafa Hajij | 2024-05-23 | ArXiv | 2 | 16 |
visibility_off | Corrector LSTM: built-in training data correction for improved time-series forecasting | Yassine Baghoussi, Carlos Soares, João Mendes-Moreira | 2024-05-23 | Neural Computing and Applications | 0 | 20 |
visibility_off | Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification | Ziyu Liu, Azadeh Alavi, Minyi Li, Xiang Zhang | 2024-07-12 | ArXiv | 0 | 1 |
visibility_off | Temporal Convolution Derived Multi-Layered Reservoir Computing | Johannes Viehweg, Dominik Walther, Prof. Dr.-Ing. Patrick Mader | 2024-07-09 | ArXiv | 0 | 2 |
visibility_off | TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs | J. Gastinger, Shenyang Huang, Mikhail Galkin, Erfan Loghmani, Alipanah Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau | 2024-06-14 | ArXiv | 0 | 19 |
visibility_off | Learning Divergence Fields for Shift-Robust Graph Representations | Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan | 2024-06-07 | ArXiv | 0 | 17 |
visibility_off | MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model Integrating CNN, LSTM, and GRU | Md Abrar Jahin, Asef Shahriar, Md Al Amin | 2024-05-24 | ArXiv | 0 | 2 |
visibility_off | Dominant Shuffle: A Simple Yet Powerful Data Augmentation for Time-series Prediction | Kai Zhao, Zuojie He, A. Hung, Dan Zeng | 2024-05-26 | ArXiv | 0 | 3 |
visibility_off | Gradient Transformation: Towards Efficient and Model-Agnostic Unlearning for Dynamic Graph Neural Networks | He Zhang, Bang Wu, Xiangwen Yang, Xingliang Yuan, Chengqi Zhang, Shirui Pan | 2024-05-23 | ArXiv | 0 | 8 |
visibility_off | Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting | Romain Ilbert, Malik Tiomoko, Cosme Louart, Ambroise Odonnat, Vasilii Feofanov, Themis Palpanas, I. Redko | 2024-06-14 | ArXiv | 0 | 49 |
visibility_off | Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting | Yifan Hu, Peiyuan Liu, Peng Zhu, Dawei Cheng, Tao Dai | 2024-06-06 | ArXiv | 0 | 1 |
visibility_off | Transfer Entropy in Graph Convolutional Neural Networks | Adrian Moldovan, A. Cataron, Răzvan Andonie | 2024-06-08 | ArXiv | 0 | 13 |
visibility_off | Bundle Neural Networks for message diffusion on graphs | Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael Bronstein | 2024-05-24 | ArXiv | 0 | 6 |
visibility_off | Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusion | Xiaobao Wu, Xinshuai Dong, Liangming Pan, Thong Nguyen, A. Luu | 2024-05-28 | ArXiv | 4 | 20 |
visibility_off | Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphs | Tim Postuvan, Claas Grohnfeldt, Michele Russo, Giulio Lovisotto | 2024-05-28 | ArXiv | 0 | 10 |
visibility_off | Assessing the Impact of Seasonal Decomposition on the Time Series Analysis Accuracy: A Comprehensive Study | Shivam Raghuvanshi | 2024-05-31 | International Journal for Research in Applied Science and Engineering Technology | 0 | 0 |
visibility_off | Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization | Sheo Yon Jhin, Seojin Kim, Noseong Park | 2024-06-29 | ArXiv | 0 | 1 |
visibility_off | Causal-Aware Graph Neural Architecture Search under Distribution Shifts | Peiwen Li, Xin Wang, Zeyang Zhang, Yi Qin, Ziwei Zhang, Jialong Wang, Yang Li, Wenwu Zhu | 2024-05-26 | ArXiv | 1 | 17 |
visibility_off | Enhancing Few-Shot Stock Trend Prediction with Large Language Models | Yiqi Deng, Xingwei He, Jiahao Hu, S.M. Yiu | 2024-07-12 | ArXiv | 0 | 0 |
visibility_off | Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting | Vijaya Krishna Yalavarthi, Randolf Scholz, Kiran Madhusudhanan, Stefan Born, Lars Schmidt-Thieme | 2024-06-11 | ArXiv | 0 | 4 |
visibility_off | Graph Condensation for Open-World Graph Learning | Xin Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin | 2024-05-27 | ArXiv | 1 | 4 |
visibility_off | Conformal time series decomposition with component-wise exchangeability | Derck W. E. Prinzhorn, Thijmen Nijdam, Putri A. van der Linden, Alexander Timans | 2024-06-24 | ArXiv | 0 | 0 |
visibility_off | Rating Multi-Modal Time-Series Forecasting Models (MM-TSFM) for Robustness Through a Causal Lens | Kausik Lakkaraju, Rachneet Kaur, Zhen Zeng, Parisa Zehtabi, Sunandita Patra, Biplav Srivastava, Marco Valtorta | 2024-06-12 | ArXiv | 0 | 7 |
visibility_off | Adapting Random Simple Recurrent Network for Online Forecasting Problems | Mohammed Elmahdi Khennour, A. Bouchachia, M. L. Kherfi, Khadra Bouanane, Oussama Aiadi | 2024-05-23 | 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) | 0 | 29 |
visibility_off | Anomaly detection in multivariate time series data using deep ensemble models | Amjad Iqbal, Rashid Amin, Faisal S. Alsubaei, Abdulrahman Alzahrani | 2024-06-06 | PLOS ONE | 1 | 4 |
visibility_off | How Well Can a Long Sequence Model Model Long Sequences? Comparing Architechtural Inductive Biases on Long-Context Abilities | Jerry Huang | 2024-07-11 | ArXiv | 0 | 0 |
visibility_off | Deep Learning Surrogate Models for Network Simulation | M. Dearing | 2024-06-24 | Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation | 0 | 3 |
visibility_off | Multiview Spatial-Temporal Meta-Learning for Multivariate Time Series Forecasting | Liang Zhang, Jianping Zhu, Bo Jin, Xiaopeng Wei | 2024-07-10 | Sensors | 0 | 6 |
visibility_off | ARIMA Model Time Series Forecasting | Mohd Faizan Rizvi | 2024-05-31 | International Journal for Research in Applied Science and Engineering Technology | 0 | 0 |
visibility_off | A Regional Short-term Load Forecasting Method Based on Adaptive Graph Construction and Kernel Size Selection | Jiansheng Zhao, Haonan Dai, Z. Zhen, Fei Wang | 2024-05-19 | 2024 IEEE/IAS 60th Industrial and Commercial Power Systems Technical Conference (I&CPS) | 0 | 21 |
visibility_off | Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph | Weihuang Zheng, Jiashuo Liu, Jiaxing Li, Jiayun Wu, Peng Cui, Youyong Kong | 2024-06-03 | ArXiv | 0 | 8 |
visibility_off | LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering | Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu | 2024-05-20 | ArXiv | 0 | 3 |
visibility_off | HoTPP Benchmark: Are We Good at the Long Horizon Events Forecasting? | Ivan Karpukhin, F. Shipilov, Andrey Savchenko | 2024-06-20 | ArXiv | 0 | 0 |
visibility_off | Preparing for Disease X: Predicting ICU Admissions Using Time Series Forecasting with Decoder-Only Transformer Neural Networks | Nejc Čelik, Andrej Škraba | 2024-05-29 | Resilience Through Digital Innovation: Enabling the Twin Transition | 0 | 0 |
visibility_off | Understanding the Generalizability of Link Predictors Under Distribution Shifts on Graphs | Jay Revolinsky, Harry Shomer, Jiliang Tang | 2024-06-13 | ArXiv | 0 | 4 |
visibility_off | TSI-Bench: Benchmarking Time Series Imputation | Wenjie Du, Jun Wang, Linglong Qian, Yiyuan Yang, Fanxing Liu, Zepu Wang, Zina Ibrahim, Haoxin Liu, Zhiyuan Zhao, Yingjie Zhou, Wenjia Wang, Kaize Ding, Yuxuan Liang, B. A. Prakash, Qingsong Wen | 2024-06-18 | ArXiv | 0 | 4 |
visibility_off | Deep Learning Methods for Adjusting Global MFD Speed Estimations to Local Link Configurations | Zhixiong Jin, Dimitrios Tsitsokas, N. Geroliminis, Ludovic Leclercq | 2024-05-23 | ArXiv | 0 | 41 |
visibility_off | Bond Graphs for multi-physics informed Neural Networks for multi-variate time series | Alexis-Raja Brachet, Pierre-Yves Richard, C'eline Hudelot | 2024-05-22 | ArXiv | 0 | 1 |
visibility_off | TGC-ARG: Anticipating Antibiotic Resistance via Transformer-Based Modeling and Contrastive Learning | Yihan Dong, Hanming Quan, Chenxi Ma, Linchao Shan, Lei Deng | 2024-06-30 | International Journal of Molecular Sciences | 0 | 1 |
visibility_off | Injecting Hamiltonian Architectural Bias into Deep Graph Networks for Long-Range Propagation | Simon Heilig, Alessio Gravina, Alessandro Trenta, Claudio Gallicchio, Davide Bacciu | 2024-05-27 | ArXiv | 0 | 4 |
visibility_off | GNNAnatomy: Systematic Generation and Evaluation of Multi-Level Explanations for Graph Neural Networks | Hsiao-Ying Lu, Yiran Li, Ujwal Pratap Krishna Kaluvakolanu Thyagarajan, Kwan-Liu Ma | 2024-06-06 | ArXiv | 0 | 6 |
visibility_off | Fusion of Movement and Naive Predictions for Point Forecasting in Univariate Random Walks | Cheng Zhang | 2024-06-20 | ArXiv | 0 | 0 |
visibility_off | GNAR: graph contrastive learning networks with adaptive readouts for anomaly detection | changcheng wan, Suixiang Gao | 2024-06-08 | None | 0 | 0 |
visibility_off | Coherent Multi-Table Data Synthesis for Tabular and Time-Series Data with GANs | Clément Elliker, Emeric Tonnelier, A. Shabou | 2024-06-19 | Proceedings of the Fourteenth ACM Conference on Data and Application Security and Privacy | 0 | 9 |
visibility_off | STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning | Wei Shao, Yufan Kang, Ziyan Peng, Xiao Xiao, Lei Wang, Yuhui Yang, Flora D. Salim | 2024-06-06 | ArXiv | 0 | 3 |
visibility_off | Efficient World Models with Context-Aware Tokenization | Vincent Micheli, Eloi Alonso, Franccois Fleuret | 2024-06-27 | ArXiv | 0 | 11 |
visibility_off | Alternators For Sequence Modeling | Mohammad Reza Rezaei, Adji B. Dieng | 2024-05-20 | ArXiv | 0 | 13 |
visibility_off | Parallelizing Linear Transformers with the Delta Rule over Sequence Length | Songlin Yang, Bailin Wang, Yu Zhang, Yikang Shen, Yoon Kim | 2024-06-10 | ArXiv | 0 | 9 |
visibility_off | Class-Based Time Series Data Augmentation to Mitigate Extreme Class Imbalance for Solar Flare Prediction | Junzhi Wen, R. Angryk | 2024-05-31 | ArXiv | 0 | 22 |
visibility_off | HLOB - Information Persistence and Structure in Limit Order Books | Antonio Briola, Silvia Bartolucci, T. Aste | 2024-05-29 | ArXiv | 0 | 47 |
visibility_off | Predictive Analysis of Sarajevo’s AQI using Machine Learning Models for Varied Data Granularity and Prediction Windows | Emina Zolota, Vahidin Hasić, Amina Mević, Amra Delić, Senka Krivic | 2024-05-20 | 2024 47th MIPRO ICT and Electronics Convention (MIPRO) | 0 | 8 |
visibility_off | ArchesWeather: An efficient AI weather forecasting model at 1.5{\deg} resolution | Guillaume Couairon, Christian Lessig, A. Charantonis, C. Monteleoni | 2024-05-23 | ArXiv | 0 | 20 |
visibility_off | KPG: Key Propagation Graph Generator for Rumor Detection based on Reinforcement Learning | Yusong Zhang, Kun Xie, Xingyi Zhang, Xiangyu Dong, Sibo Wang | 2024-05-21 | ArXiv | 0 | 4 |
visibility_off | A spatial‐temporal graph gated transformer for traffic forecasting | Haroun Bouchemoukha, M. Zennir, Ahmed Alioua | 2024-06-26 | Transactions on Emerging Telecommunications Technologies | 0 | 4 |
visibility_off | An Attention-Based Multi-Context Convolutional Encoder-Decoder Neural Network for Work Zone Traffic Impact Prediction | Qinhua Jiang, Xishun Liao, Yaofa Gong, Jiaqi Ma | 2024-05-31 | ArXiv | 1 | 4 |
visibility_off | Global-local graph attention: unifying global and local attention for node classification | Keao Lin, Xiao-Zhu Xie, Wei Weng, Xiaofeng Du | 2024-07-11 | The Computer Journal | 0 | 1 |
visibility_off | Heterogeneous Graph Neural Networks with Post-hoc Explanations for Multi-modal and Explainable Land Use Inference | Xuehao Zhai, Junqi Jiang, Adam Dejl, Antonio Rago, Fangce Guo, Francesca Toni, Aruna Sivakumar | 2024-06-19 | ArXiv | 0 | 14 |
visibility_off | Know Your Neighborhood: General and Zero-Shot Capable Binary Function Search Powered by Call Graphlets | Josh Collyer, Tim Watson, Iain Phillips | 2024-06-02 | ArXiv | 0 | 1 |
visibility_off | Building a Model for Time Series Forecasting using AutoML Methods | V. Kovalevsky, N. Zhukova | 2024-05-22 | 2024 XXVII International Conference on Soft Computing and Measurements (SCM) | 0 | 7 |
visibility_off | Review of Open-Source Libraries for Solving Time Series Forecasting Problems | E.A. Svekolnikova, V.N. Panovskiy | 2024-07-01 | Моделирование и анализ данных | 0 | 0 |
visibility_off | IENE: Identifying and Extrapolating the Node Environment for Out-of-Distribution Generalization on Graphs | Haoran Yang, Xiaobing Pei, Kai Yuan | 2024-06-02 | ArXiv | 0 | 1 |
visibility_off | GNNTAL:A Novel Model for Identifying Critical Nodes in Complex Networks | Hao Wang, Ting Luo, Shuang-ping Yang, Ming Jing, Jian Wang, Na Zhao | 2024-06-24 | ArXiv | 0 | 3 |
visibility_off | Multi-variable Adversarial Time-Series Forecast Model | Xiaoqiao Chen | 2024-06-02 | ArXiv | 0 | 0 |
visibility_off | Nonlinear time-series embedding by monotone variational inequality | Jonathan Y. Zhou, Yao Xie | 2024-06-11 | ArXiv | 0 | 0 |
visibility_off | Distributional Refinement Network: Distributional Forecasting via Deep Learning | Benjamin Avanzi, Eric Dong, P. Laub, Bernard Wong | 2024-06-03 | ArXiv | 0 | 14 |
visibility_off | Addressing the Non-Stationarity and Complexity of Time Series Data for Long-Term Forecasts | Ranjai Baidya, Sang-Woong Lee | 2024-05-23 | Applied Sciences | 0 | 4 |
visibility_off | Research on load clustering algorithm based on variational autoencoder and hierarchical clustering | Miaozhuang Cai, Yin Zheng, Zhengyang Peng, Chunyan Huang, Haoxia Jiang | 2024-06-13 | PLOS ONE | 0 | 1 |
visibility_off | Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs | Hrishikesh Viswanath, Yue Chang, Julius Berner, Peter Yichen Chen, Aniket Bera | 2024-07-04 | ArXiv | 0 | 28 |
visibility_off | Situational awareness on a graph: towards graph neural networks for spectrum analysis and battlefield management | Jeff Anderson | 2024-06-06 | None | 0 | 0 |
visibility_off | DyGPrompt: Learning Feature and Time Prompts on Dynamic Graphs | Xingtong Yu, Zhenghao Liu, Yuan Fang, Xinming Zhang | 2024-05-22 | ArXiv | 1 | 6 |
visibility_off | Stacking for Probabilistic Short-Term Load Forecasting | Grzegorz Dudek | 2024-06-15 | DBLP, ArXiv | 0 | 0 |
visibility_off | Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification | Jiachen Chen, Danyang Huang, Liyuan Wang, Kathryn L. Lunetta, Debarghya Mukherjee, Huimin Cheng | 2024-05-26 | ArXiv | 0 | 4 |
visibility_off | Cross-Temporal Hierarchical Forecast Reconciliation of Natural Gas Demand | Colin O. Quinn, G. Corliss, Richard J. Povinelli | 2024-06-21 | Energies | 0 | 27 |
visibility_off | TENNs-PLEIADES: Building Temporal Kernels with Orthogonal Polynomials | Yan Ru Pei, Olivier Coenen | 2024-05-20 | ArXiv | 0 | 2 |
visibility_off | Predicting grid frequency short-term dynamics with Gaussian processes and sequence modeling | Bolin Liu, Maximilian Coblenz, Oliver Grothe | 2024-05-31 | Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems | 0 | 5 |
visibility_off | Explaining time series models using frequency masking | Thea Brusch, Kristoffer Wickstrøm, Mikkel N. Schmidt, T. S. Alstrøm, Robert Jenssen | 2024-06-19 | ArXiv | 0 | 12 |
visibility_off | SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning | Hongfei Wu, Lijun Wu, Guoqing Liu, Zhirong Liu, Bin Shao, Zun Wang | 2024-05-26 | ArXiv | 0 | 5 |
visibility_off | DeFiGuard: A Price Manipulation Detection Service in DeFi using Graph Neural Networks | Dabao Wang, Bang Wu, Xingliang Yuan, Lei Wu, Yajin Zhou, Helei Cui | 2024-06-17 | ArXiv | 0 | 8 |
visibility_off | Discover Your Neighbors: Advanced Stable Test-Time Adaptation in Dynamic World | Qinting Jiang, Chuyang Ye, Dongyan Wei, Yuan Xue, Jingyan Jiang, Zhi Wang | 2024-06-08 | ArXiv | 0 | 1 |
visibility_off | Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations | Yujee Song, Donghyun Lee, Rui Meng, Won Hwa Kim | 2024-06-10 | ArXiv | 0 | 0 |
visibility_off | Time-Series JEPA for Predictive Remote Control under Capacity-Limited Networks | Abanoub M. Girgis, Álvaro Valcarce, Mehdi Bennis | 2024-06-07 | ArXiv | 0 | 4 |
visibility_off | Link Prediction in Dynamic Social Networks Combining Entropy, Causality, and a Graph Convolutional Network Model | Xiaoli Huang, Jingyu Li, Yumiao Yuan | 2024-05-30 | Entropy | 0 | 0 |
visibility_off | Efficient Clothing Fashion Prediction using Machine Learning | M. Sanjai, Dr. C. Meenakshi | 2024-07-10 | International Journal of Advanced Research in Science, Communication and Technology | 0 | 0 |
visibility_off | SimLOB: Learning Representations of Limited Order Book for Financial Market Simulation | Yuanzhe Li, Yue Wu, Peng Yang | 2024-06-27 | ArXiv | 0 | 0 |
visibility_off | SigDiffusions: Score-Based Diffusion Models for Long Time Series via Log-Signature Embeddings | Barbora Barancikova, Zhuoyue Huang, Cristopher Salvi | 2024-06-14 | ArXiv | 0 | 1 |
visibility_off | Quantum-Train Long Short-Term Memory: Application on Flood Prediction Problem | Chu-Hsuan Abraham Lin, Chen-Yu Liu, Kuan-Cheng Chen | 2024-07-11 | ArXiv | 0 | 2 |
visibility_off | MeMSVD: Long-Range Temporal Structure Capturing Using Incremental SVD | Ioanna Ntinou, Enrique Sanchez, Georgios Tzimiropoulos | 2024-06-11 | ArXiv | 0 | 13 |
visibility_off | An Aggregated Baseline Load Estimation Method Based on Graph Convolutional Networks Introducing Graph Structure Learning | Xuefeng Peng, Fei Wang, X. Ge, Yuqing Wang | 2024-05-19 | 2024 IEEE/IAS 60th Industrial and Commercial Power Systems Technical Conference (I&CPS) | 0 | 11 |
visibility_off | Time Elastic Neural Networks | Pierre-Franccois Marteau | 2024-05-27 | ArXiv | 0 | 0 |
visibility_off | Time-Series Forecasting and Sequence Learning Using Memristor-based Reservoir System | Abdullah M. Zyarah, D. Kudithipudi | 2024-05-22 | ArXiv | 0 | 20 |
visibility_off | Spatiotemporal Dynamic Multi-Hop Network for Traffic Flow Forecasting | Wenguang Chai, Qingfeng Luo, Zhizhe Lin, Jingwen Yan, Jinglin Zhou, Teng Zhou | 2024-07-09 | Sustainability | 0 | 11 |
visibility_off | A data-centric approach for assessing progress of Graph Neural Networks | Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla | 2024-06-18 | ArXiv | 0 | 2 |
visibility_off | An All-MLP Sequence Modeling Architecture That Excels at Copying | Chenwei Cui, Zehao Yan, Gedeon Muhawenayo, Hannah Kerner | 2024-06-23 | ArXiv | 0 | 2 |
visibility_off | Health supply chain forecasting: a comparison of ARIMA and LSTM time series models for demand prediction of medicines | F. Mbonyinshuti, Joseph Nkurunziza, J. Niyobuhungiro, Egide Kayitare | 2024-06-30 | Acta logistica | 0 | 6 |
visibility_off | Adaptive predictive modeling with online learning: addressing data drift challenges in historical data for distributed inferencing | Cleon Anderson, Scott E. Brown, David Harman, M. Dwyer | 2024-06-07 | None | 0 | 3 |
visibility_off | A binary-domain recurrent-like architecture-based dynamic graph neural network | Zi-chao Chen, Sui Lin | 2024-06-25 | Auton. Intell. Syst. | 0 | 0 |
visibility_off | Evaluating Recurrent Neural Networks for prediction of Multi- Variate time series VoIP metrics | M. Di Mauro, G. Galatro, F. Postiglione, W. Song, A. Liotta | 2024-06-11 | 2024 22nd Mediterranean Communication and Computer Networking Conference (MedComNet) | 0 | 7 |
visibility_off | Multivariate Bayesian Time-Series Model with Multi-temporal Convolution Network for Forecasting Stock Market During COVID-19 Pandemic | Paramita Ray, B. Ganguli, Amlan Chakrabarti | 2024-06-27 | Int. J. Comput. Intell. Syst. | 0 | 13 |
visibility_off | Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks | Joel Oskarsson, Tomas Landelius, M. Deisenroth, Fredrik Lindsten | 2024-06-07 | ArXiv | 1 | 44 |
visibility_off | Continuous Temporal Domain Generalization | Z. Cai, Guangji Bai, Renhe Jiang, Xuan Song, Liang Zhao | 2024-05-25 | ArXiv | 1 | 18 |
visibility_off | Recurrent Stochastic Configuration Networks for Temporal Data Analytics | Dianhui Wang, Gang Dang | 2024-06-21 | ArXiv | 0 | 1 |
visibility_off | Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts | Romain Pic, Cl'ement Dombry, Philippe Naveau, Maxime Taillardat | 2024-07-02 | ArXiv | 0 | 7 |
visibility_off | DyHANE: dynamic heterogeneous attributed network embedding through experience node replay | Liliana Martirano, D. Ienco, R. Interdonato, Andrea Tagarelli | 2024-07-05 | Appl. Netw. Sci. | 0 | 29 |
visibility_off | Deep LPPLS: Forecasting of temporal critical points in natural, engineering and financial systems | Joshua Nielsen, Didier Sornette, M. Raissi | 2024-05-21 | ArXiv | 0 | 24 |
visibility_off | A Large Reservoir Computing Forecasting Method Based on Randomized Fuzzy Cognitive Maps | Omid Orang, F. J. Erazo-Costa, Petrônio C. L. Silva, Guilherme de Alencar Barreto, F. G. Guimarães | 2024-05-23 | 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) | 0 | 12 |
visibility_off | Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification | D. Serramazza, Thach Le Nguyen, Georgiana Ifrim | 2024-06-18 | ArXiv | 0 | 7 |
visibility_off | Stock Volume Forecasting with Advanced Information by Conditional Variational Auto-Encoder | Parley R Yang, Alexander Y. Shestopaloff | 2024-06-19 | ArXiv | 0 | 7 |
visibility_off | Semi-supervised contrastive learning with decomposition-based data augmentation for time series classification | Dokyun Kim, Sukhyun Cho, Heewoong Chae, Jonghun Park, Jaeseok Huh | 2024-05-30 | Intelligent Data Analysis | 0 | 4 |
visibility_off | Time Series Forecasting with Many Predictors | Shuo-chieh Huang, R. Tsay | 2024-06-13 | ArXiv | 0 | 50 |
visibility_off | A Review of Optimization Algorithms in Deep Learning Models for Improving the Forecasting Accuracy in Sequential Datasets with Application in the South African Stock Market Index | Sanele Makamo | 2024-05-25 | Advanced Natural Language Processing | 0 | 0 |
visibility_off | Higher-Order Convolutional Neural Networks for Essential Climate Variables Forecasting | Michalis Giannopoulos, G. Tsagkatakis, P. Tsakalides | 2024-06-04 | Remote. Sens. | 0 | 31 |
visibility_off | Enhancing reliability in prediction intervals using point forecasters: Heteroscedastic Quantile Regression and Width-Adaptive Conformal Inference | Carlos Sebasti'an, Carlos E. Gonz'alez-Guill'en, Jes'us Juan | 2024-06-21 | ArXiv | 0 | 1 |
visibility_off | A Meta-learner approach to multistep-ahead time series prediction | Fouad Bahrpeyma, V. M. Ngo, M. Roantree, A. Mccarren | 2024-07-09 | International Journal of Data Science and Analytics | 0 | 17 |
visibility_off | State-Space Modeling in Long Sequence Processing: A Survey on Recurrence in the Transformer Era | Matteo Tiezzi, Michele Casoni, Alessandro Betti, Marco Gori, S. Melacci | 2024-06-13 | ArXiv | 0 | 14 |
visibility_off | Encoding temporal information in deep convolution neural network | Avinash Kumar Singh, Luigi Bianchi | 2024-06-19 | Frontiers in Neuroergonomics | 0 | 0 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |