Neural ODEs

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Manually curated articles on Neural ODEs

Abstract Title Authors Publication Date Journal/ Conference Citation count Highest h-index View recommendations
visibility_off Neural Ordinary Differential Equations T. Chen, Yulia Rubanova, J. Bettencourt, D. Duvenaud 2018-06-19 MAG, DBLP, ArXiv 3930 48 open_in_new
visibility_off Dissecting Neural ODEs Stefano Massaroli, Michael Poli, Jinkyoo Park, A. Yamashita, H. Asama 2020-02-19 Neural Information Processing Systems, ArXiv 165 39 open_in_new
visibility_off Graph Neural Ordinary Differential Equations Michael Poli, Stefano Massaroli, Junyoung Park, A. Yamashita, H. Asama, Jinkyoo Park 2019-11-18 arXiv.org, ArXiv 121 39 open_in_new
visibility_off GRAND: Graph Neural Diffusion B. Chamberlain, J. Rowbottom, Maria I. Gorinova, Stefan Webb, Emanuele Rossi, M. Bronstein 2021-06-21 International Conference on Machine Learning, ArXiv 199 76 open_in_new
visibility_off Message Passing Neural PDE Solvers Johannes Brandstetter, Daniel E. Worrall, M. Welling 2022-02-07 International Conference on Learning Representations, ArXiv 196 88 open_in_new
visibility_off Graph-Coupled Oscillator Networks T. Konstantin Rusch, B. Chamberlain, J. Rowbottom, S. Mishra, M. Bronstein 2022-02-04 DBLP, ArXiv 70 76 open_in_new
visibility_off Continuous PDE Dynamics Forecasting with Implicit Neural Representations Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, A. Rakotomamonjy, P. Gallinari 2022-09-29 International Conference on Learning Representations, ArXiv 33 48 open_in_new
Abstract Title Authors Publication Date Journal/ Conference Citation count Highest h-index View recommendations

Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index
visibility_off Graph Neural Reaction Diffusion Models Moshe Eliasof, Eldad Haber, Eran Treister 2024-06-16 ArXiv 1 15
visibility_off Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp, Mathias Niepert 2024-06-06 ArXiv 1 2
visibility_off Continuous Geometry-Aware Graph Diffusion via Hyperbolic Neural PDE Jiaxu Liu, Xinping Yi, Sihao Wu, Xiangyu Yin, Tianle Zhang, Xiaowei Huang, Shi Jin 2024-06-03 ArXiv 0 2
visibility_off KAN-ODEs: Kolmogorov-Arnold Network Ordinary Differential Equations for Learning Dynamical Systems and Hidden Physics Benjamin C. Koenig, Suyong Kim, Sili Deng 2024-07-05 ArXiv 0 2
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 Solving partial differential equations with sampled neural networks Chinmay Datar, Taniya Kapoor, Abhishek Chandra, Qing Sun, Iryna Burak, Erik Lien Bolager, Anna Veselovska, Massimo Fornasier, Felix Dietrich 2024-05-31 ArXiv 0 4
visibility_off Advection Augmented Convolutional Neural Networks N. Zakariaei, Siddharth Rout, Eldad Haber, Moshe Eliasof 2024-06-27 ArXiv 0 6
visibility_off Space-Time Continuous PDE Forecasting using Equivariant Neural Fields David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, J. Sonke, E. Gavves, E. J. Bekkers 2024-06-10 ArXiv 1 56
visibility_off Graph Neural PDE Solvers with Conservation and Similarity-Equivariance Masanobu Horie, Naoto Mitsume 2024-05-25 ArXiv 0 0
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 A numerical method to solve PDE through PINN based on ODENet Ziyi Wang 2024-06-24 Applied and Computational Engineering 0 0
visibility_off From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems Xin Li, Jingdong Zhang, Qunxi Zhu, Chengli Zhao, Xue Zhang, Xiaojun Duan, Wei Lin 2024-05-19 ArXiv 0 12
visibility_off Stable Weight Updating: A Key to Reliable PDE Solutions Using Deep Learning A. Noorizadegan, R. Cavoretto, D. Young, C. S. Chen 2024-07-10 ArXiv 0 4
visibility_off Learning to Discretize Denoising Diffusion ODEs Vinh Tong, Anji Liu, Trung-Dung Hoang, Guy Van den Broeck, Mathias Niepert 2024-05-24 ArXiv 0 38
visibility_off Solving Poisson Equations using Neural Walk-on-Spheres Hong Chul Nam, Julius Berner, A. Anandkumar 2024-06-05 ArXiv 2 5
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 The Disappearance of Timestep Embedding in Modern Time-Dependent Neural Networks Bum Jun Kim, Yoshinobu Kawahara, Sang Woo Kim 2024-05-23 ArXiv 0 8
visibility_off Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks Felix Dangel, Johannes Müller, Marius Zeinhofer 2024-05-24 ArXiv 0 6
visibility_off Modeling Randomly Observed Spatiotemporal Dynamical Systems V. Iakovlev, Harri Lähdesmäki 2024-06-01 ArXiv 0 2
visibility_off On Dissipativity of Cross-Entropy Loss in Training ResNets Jens Püttschneider, T. Faulwasser 2024-05-29 ArXiv 0 28
visibility_off A Review of Neural Network Solvers for Second-order Boundary Value Problems Ramesh Chandra Sau, Luowei Yin 2024-06-29 ArXiv 0 0
visibility_off Gradients of Functions of Large Matrices Nicholas Krämer, Pablo Moreno-Munoz, Hrittik Roy, Søren Hauberg 2024-05-27 ArXiv 0 8
visibility_off RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators Gianluca Fabiani, Ioannis G. Kevrekidis, Constantinos Siettos, A. Yannacopoulos 2024-06-08 ArXiv 0 17
visibility_off Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers Zhou Hang, Yuezhou Ma, Haixu Wu, Haowen Wang, Mingsheng Long 2024-05-27 ArXiv 0 20
visibility_off A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks K. Shukla, Juan Diego Toscano, Zhicheng Wang, Zongren Zou, G. Karniadakis 2024-06-05 ArXiv 4 127
visibility_off Flow Map Matching Nicholas M. Boffi, M. S. Albergo, Eric Vanden-Eijnden 2024-06-11 ArXiv 0 16
visibility_off Stable tensor neural networks for efficient deep learning Elizabeth Newman, L. Horesh, H. Avron, M. Kilmer 2024-05-30 Frontiers in Big Data 1 34
visibility_off PDEformer-1: A Foundation Model for One-Dimensional Partial Differential Equations Zhanhong Ye, Xiang Huang, Leheng Chen, Zining Liu, Bingyang Wu, Hongsheng Liu, Zidong Wang, Bin Dong 2024-07-09 ArXiv 0 5
visibility_off Self-supervised Pretraining for Partial Differential Equations Varun Madhavan, Amal S Sebastian, Bharath Ramsundar, Venkat Viswanathan 2024-07-03 ArXiv 0 19
visibility_off Switched Flow Matching: Eliminating Singularities via Switching ODEs Qunxi Zhu, Wei Lin 2024-05-19 ArXiv 0 8
visibility_off Dynamical Measure Transport and Neural PDE Solvers for Sampling Jingtong Sun, Julius Berner, Lorenz Richter, Marius Zeinhofer, Johannes Muller, K. Azizzadenesheli, A. Anandkumar 2024-07-10 ArXiv 0 31
visibility_off AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields Louis Serrano, Thomas X. Wang, E. L. Naour, Jean-Noël Vittaut, P. Gallinari 2024-06-04 ArXiv 0 48
visibility_off Flexible SE(2) graph neural networks with applications to PDE surrogates Maria Bånkestad, Olof Mogren, Aleksis Pirinen 2024-05-30 ArXiv 0 12
visibility_off Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals Christian Holberg, C. Salvi 2024-05-22 ArXiv 0 12
visibility_off Solving forward and inverse PDE problems on unknown manifolds via physics-informed neural operators Anran Jiao, Qile Yan, Jhn Harlim, Lu Lu 2024-07-07 ArXiv 0 2
visibility_off Newton Informed Neural Operator for Computing Multiple Solutions of Nonlinear Partials Differential Equations Wenrui Hao, Xinliang Liu, Yahong Yang 2024-05-23 ArXiv 0 1
visibility_off Error Analysis and Numerical Algorithm for PDE Approximation with Hidden-Layer Concatenated Physics Informed Neural Networks Yianxia Qian, Yongchao Zhang, Suchuan Dong 2024-06-10 ArXiv 0 2
visibility_off fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions A. Aghaei 2024-06-11 ArXiv 4 4
visibility_off Directly Denoising Diffusion Models Dan Zhang, Jingjing Wang, Feng Luo 2024-05-22 ArXiv 0 0
visibility_off Regularity-Conforming Neural Networks (ReCoNNs) for solving Partial Differential Equations Jamie M. Taylor, David Pardo, J. Muñoz‐Matute 2024-05-23 ArXiv 0 7
visibility_off Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations Zheyuan Hu, Zhongqiang Zhang, G. Karniadakis, Kenji Kawaguchi 2024-06-17 ArXiv 0 127
visibility_off Physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics Simone Brugiapaglia, N. Dexter, Samir Karam, Weiqi Wang 2024-06-03 ArXiv 1 9
visibility_off Solving Bivariate Kinetic Equations for Polymer Diffusion Using Deep Learning Heng Wang null, Weihua Deng 2024-06-01 Journal of Machine Learning 0 0
visibility_off ConDiff: A Challenging Dataset for Neural Solvers of Partial Differential Equations Vladislav Trifonov, Alexander Rudikov, Oleg Iliev, I. Oseledets, Ekaterina A. Muravleva 2024-06-07 ArXiv 0 2
visibility_off Strategies for Pretraining Neural Operators Anthony Y. Zhou, Cooper Lorsung, AmirPouya Hemmasian, A. Farimani 2024-06-12 ArXiv 0 33
visibility_off Modeling of DC-DC Converters with Neural Ordinary Differential Equations Hanchen Ge, Canjun Yuan, Yaofeng Liang, Jinpeng Lei, Zhicong Huang 2024-05-19 2024 IEEE International Symposium on Circuits and Systems (ISCAS) 0 0
visibility_off Godunov Loss Functions for Modelling of Hyperbolic Conservation Laws R. G. Cassia, R. Kerswell 2024-05-19 ArXiv 0 44
visibility_off Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations Ze Cheng, Zhongkai Hao, Xiaoqiang Wang, Jianing Huang, Youjia Wu, Xudan Liu, Yiru Zhao, Songming Liu, Hang Su 2024-05-27 ArXiv 1 12
visibility_off Linearization Turns Neural Operators into Function-Valued Gaussian Processes Emilia Magnani, Marvin Pförtner, Tobias Weber, Philipp Hennig 2024-06-07 ArXiv 0 3
visibility_off Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers Vladislav Trifonov, Alexander Rudikov, Oleg Iliev, I. Oseledets, Ekaterina A. Muravleva 2024-05-24 ArXiv 0 2
visibility_off Neural Residual Diffusion Models for Deep Scalable Vision Generation Zhiyuan Ma, Liangliang Zhao, Biqing Qi, Bowen Zhou 2024-06-19 ArXiv 0 6
visibility_off DeltaPhi: Learning Physical Trajectory Residual for PDE Solving Xihang Yue, Linchao Zhu, Yi Yang 2024-06-14 ArXiv 0 41
visibility_off A Finite Difference Informed Graph Network for Solving Steady-State Incompressible Flows on Block-Structured Grids Yiye Zou, Tianyu Li, Shufan Zou, Jingyu Wang, Laiping Zhang, Xiaogang Deng 2024-06-15 ArXiv 0 1
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 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 Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity Benjamin Shih, Ahmad Peyvan, Zhongqiang Zhang, G. Karniadakis 2024-05-29 ArXiv 0 127
visibility_off Gradient-based adaptive neural network technique for two-dimensional local fractional elliptic PDEs Navnit Jha, Ekansh Mallik 2024-05-24 Physica Scripta 0 0
visibility_off Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos, P. Koutsourelakis 2024-05-29 ArXiv 0 21
visibility_off Ensemble and Mixture-of-Experts DeepONets For Operator Learning Ramansh Sharma, Varun Shankar 2024-05-20 ArXiv 0 2
visibility_off Sparsifying dimensionality reduction of PDE solution data with Bregman learning T. J. Heeringa, Christoph Brune, Mengwu Guo 2024-06-18 ArXiv 0 1
visibility_off A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains Yusuke Yamazaki, Ali Harandi, Mayu Muramatsu, A. Viardin, Markus Apel, T. Brepols, Stefanie Reese, Shahed Rezaei 2024-05-21 ArXiv 1 18
visibility_off Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data B. Peters, Eldad Haber, Keegan Lensink 2024-06-30 ArXiv 0 9
visibility_off Exploiting Chaotic Dynamics as Deep Neural Networks Shuhong Liu, Nozomi Akashi, Qingyao Huang, Yasuo Kuniyoshi, Kohei Nakajima 2024-05-29 ArXiv 1 8
visibility_off Closed-form Symbolic Solutions: A New Perspective on Solving Partial Differential Equations Shu Wei, Yanjie Li, Lina Yu, Min Wu, Weijun Li, Meilan Hao, Wenqiang Li, Jingyi Liu, Yusong Deng 2024-05-23 ArXiv 0 13
visibility_off KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning Roman Bresson, Giannis Nikolentzos, G. Panagopoulos, Michail Chatzianastasis, Jun Pang, M. Vazirgiannis 2024-06-26 ArXiv 1 54
visibility_off Diffusion Bridge Implicit Models Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu 2024-05-24 ArXiv 0 21
visibility_off Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation Madison Cooley, Shandian Zhe, R. Kirby, Varun Shankar 2024-06-04 ArXiv 0 19
visibility_off Operator-informed score matching for Markov diffusion models Zheyang Shen, C. Oates 2024-06-13 ArXiv 0 24
visibility_off Variational Quantum Framework for Partial Differential Equation Constrained Optimization Amit Surana, Abeynaya Gnanasekaran 2024-05-26 ArXiv 0 4
visibility_off Learning dynamical systems from data: An introduction to physics-guided deep learning Rose Yu, Rui Wang 2024-06-24 Proceedings of the National Academy of Sciences of the United States of America 1 1
visibility_off Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems Katiana Kontolati, S. Goswami, G. Em Karniadakis, Michael D Shields 2024-06-14 Nature Communications 0 19
visibility_off DeepOKAN: Deep Operator Network Based on Kolmogorov Arnold Networks for Mechanics Problems D. Abueidda, Panos Pantidis, M. Mobasher 2024-05-29 ArXiv 7 24
visibility_off What's the score? Automated Denoising Score Matching for Nonlinear Diffusions Raghav Singhal, Mark Goldstein, Rajesh Ranganath 2024-07-10 ArXiv 0 7
visibility_off Physics-informed neural networks for tsunami inundation modeling Rudiger Brecht, E. Cardoso-Bihlo, Alex Bihlo 2024-06-23 ArXiv 0 7
visibility_off Generative Topological Networks Alona Levy-Jurgenson, Z. Yakhini 2024-06-21 ArXiv 0 53
visibility_off Tensor Network Space-Time Spectral Collocation Method for Solving the Nonlinear Convection Diffusion Equation Dibyendu Adak, M. E. Danis, Duc P. Truong, Kim Ø. Rasmussen, B. Alexandrov 2024-06-04 ArXiv 0 22
visibility_off Kolmogorov Arnold Informed neural network: A physics-informed deep learning framework for solving PDEs based on Kolmogorov Arnold Networks Yizheng Wang, Jia Sun, Jinshuai Bai, C. Anitescu, M. Eshaghi, X. Zhuang, T. Rabczuk, Yinghua Liu 2024-06-16 ArXiv 4 69
visibility_off Continuous Product Graph Neural Networks Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo 2024-05-29 ArXiv 0 17
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 Hamilton-Jacobi Based Policy-Iteration via Deep Operator Learning Jae Yong Lee, Yeoneung Kim 2024-06-16 ArXiv 1 5
visibility_off Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations Wei Zhou, Y. F. Xu 2024-07-15 ArXiv 0 2
visibility_off Convolutional neural network based reduced order modeling for multiscale problems Xuhan Zhang, Lijian Jiang 2024-06-24 ArXiv 0 0
visibility_off Weak Generative Sampler to Efficiently Sample Invariant Distribution of Stochastic Differential Equation Zhiqiang Cai, Yu Cao, Yuanfei Huang, Xiang Zhou 2024-05-29 ArXiv 0 1
visibility_off LaCoOT: Layer Collapse through Optimal Transport Victor Qu'etu, Nour Hezbri, Enzo Tartaglione 2024-06-13 ArXiv 0 11
visibility_off ImageFlowNet: Forecasting Multiscale Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images Chen Liu, Ke Xu, Liangbo L. Shen, Guillaume Huguet, Zilong Wang, Alexander Tong, Danilo Bzdok, Jay Stewart, Jay C. Wang, L. V. Priore, Smita Krishnaswamy 2024-06-20 ArXiv 0 4
visibility_off Astral: training physics-informed neural networks with error majorants V. Fanaskov, Tianchi Yu, Alexander Rudikov, I. Oseledets 2024-06-04 ArXiv 0 3
visibility_off C2M3: Cycle-Consistent Multi-Model Merging Donato Crisostomi, M. Fumero, Daniele Baieri, F. Bernard, Emanuele Rodolà 2024-05-28 ArXiv 0 1
visibility_off MBD-NODE: Physics-informed data-driven modeling and simulation of constrained multibody systems Jingquan Wang, Shu Wang, H. Unjhawala, Jinlong Wu, D. Negrut 2024-07-11 ArXiv 0 28
visibility_off CoNO: Complex Neural Operator for Continous Dynamical Physical Systems Karn Tiwari, N. M. A. Krishnan, P. PrathoshA 2024-06-01 ArXiv 0 0
visibility_off Physics informed cell representations for variational formulation of multiscale problems Yuxiang Gao, Soheil Kolouri, R. Duddu 2024-05-27 ArXiv 0 28
visibility_off FUSE: Fast Unified Simulation and Estimation for PDEs Levi E. Lingsch, Dana Grund, Siddhartha Mishra, Georgios Kissas 2024-05-23 ArXiv 0 1
visibility_off Lagrangian Neural Networks for Reversible Dissipative Evolution V. Sundararaghavan, Megna N. Shah, Jeff P. Simmons 2024-05-23 ArXiv 0 32
visibility_off Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers Guglielmo Gattiglio, Lyudmila Grigoryeva, M. Tamborrino 2024-05-20 ArXiv 0 11
visibility_off Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning D. Kunin, Allan Ravent'os, Cl'ementine Domin'e, Feng Chen, David Klindt, Andrew Saxe, Surya Ganguli 2024-06-10 ArXiv 1 12
visibility_off The capability of a deep learning based ODE solution for low temperature plasma chemistry Bo Yin, Yifei Zhu, Xiancong Chen, Yun Wu 2024-06-01 Physics of Plasmas 0 13
visibility_off Understanding the dynamics of the frequency bias in neural networks Juan Molina, Mircea Petrache, F. S. Costabal, Mat'ias Courdurier 2024-05-23 ArXiv 0 12
visibility_off Adaptive RKHS Fourier Features for Compositional Gaussian Process Models Xinxing Shi, Thomas Baldwin-McDonald, Mauricio A. 'Alvarez 2024-07-01 ArXiv 0 1
visibility_off DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents Yilun Xu, Gabriele Corso, T. Jaakkola, Arash Vahdat, Karsten Kreis 2024-07-03 ArXiv 0 97
visibility_off Non-Negative Universal Differential Equations With Applications in Systems Biology Maren Philipps, Antonia Korner, Jakob Vanhoefer, Dilan Pathirana, Jan Hasenauer 2024-06-20 ArXiv 0 6
visibility_off Physics-Informed Holomorphic Neural Networks (PIHNNs): Solving Linear Elasticity Problems Matteo Calafa, Emil Hovad, A. Engsig-Karup, T. Andriollo 2024-07-01 ArXiv 0 20
visibility_off Group and Shuffle: Efficient Structured Orthogonal Parametrization Mikhail Gorbunov, Nikolay Yudin, Vera Soboleva, Aibek Alanov, Alexey Naumov, Maxim Rakhuba 2024-06-14 ArXiv 0 6
visibility_off Solving Partial Differential Equations in Different Domains by Operator Learning method Based on Boundary Integral Equations Bin Meng, Yutong Lu, Ying Jiang 2024-06-04 ArXiv 0 0
visibility_off SGM-PINN: Sampling Graphical Models for Faster Training of Physics-Informed Neural Networks John Anticev, Ali Aghdaei, Wuxinlin Cheng, Zhuo Feng 2024-07-10 ArXiv 0 2
visibility_off Physics-guided Full Waveform Inversion using Encoder-Solver Convolutional Neural Networks Matan Goren, Eran Treister 2024-05-27 ArXiv 0 15
visibility_off Graph Neural Networks Do Not Always Oversmooth Bastian Epping, Alexandre Ren'e, M. Helias, Michael T. Schaub 2024-06-04 ArXiv 0 28
visibility_off Learning Diffusion at Lightspeed Antonio Terpin, Nicolas Lanzetti, Florian Dörfler 2024-06-18 ArXiv 0 10
visibility_off Towards Universal Mesh Movement Networks Mingrui Zhang, Chunyang Wang, Stephan Kramer, Joseph G. Wallwork, Siyi Li, Jiancheng Liu, Xiang Chen, M. Piggott 2024-06-29 ArXiv 0 38
visibility_off Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for space-time solutions of semilinear partial differential equations Julia Ackermann, Arnulf Jentzen, Benno Kuckuck, J. Padgett 2024-06-16 ArXiv 0 45
visibility_off Diffusion Models Are Innate One-Step Generators Bowen Zheng, Tianming Yang 2024-05-31 ArXiv 0 0
visibility_off RoPINN: Region Optimized Physics-Informed Neural Networks Haixu Wu, Huakun Luo, Yuezhou Ma, Jianmin Wang, Mingsheng Long 2024-05-23 ArXiv 0 65
visibility_off Simplified and Generalized Masked Diffusion for Discrete Data Jiaxin Shi, Kehang Han, Zhe Wang, Arnaud Doucet, Michalis K. Titsias 2024-06-06 ArXiv 1 32
visibility_off Combining physics-informed graph neural network and finite difference for solving forward and inverse spatiotemporal PDEs Hao Zhang, Longxiang Jiang, Xinkun Chu, Yong Wen, Luxiong Li, Yonghao Xiao, Liyuan Wang 2024-05-30 ArXiv 0 6
visibility_off Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Mart'inez, Joaquin Fontbona 2024-05-30 ArXiv 0 0
visibility_off DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon V. Mathis, Vincent Dutordoir, Riccardo Barbano, Emile Mathieu, U. J. Komorowska, Pietro Liò 2024-06-03 ArXiv 1 10
visibility_off Neural Approximate Mirror Maps for Constrained Diffusion Models Berthy T. Feng, Ricardo Baptista, Katherine L. Bouman 2024-06-18 ArXiv 0 5
visibility_off Graph neural networks informed locally by thermodynamics Alicia Tierz, Ic´ıar Alfaro, David Gonz'alez, Francisco Chinesta, Elías Cueto 2024-05-21 ArXiv 0 13
visibility_off A Priori Estimation of the Approximation, Optimization and Generalization Error of Random Neural Networks for Solving Partial Differential Equations Xianliang Xu, Zhongyi Huang 2024-06-05 ArXiv 0 1
visibility_off Exact Gauss-Newton Optimization for Training Deep Neural Networks Mikalai Korbit, Adeyemi Damilare Adeoye, Alberto Bemporad, Mario Zanon 2024-05-23 ArXiv 0 2
visibility_off Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff 2024-05-24 ArXiv 1 24
visibility_off Neural Incremental Data Assimilation Matthieu Blanke, R. Fablet, Marc Lelarge 2024-06-21 ArXiv 0 16
visibility_off Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEs Shahed Rezaei, Reza Najian Asl, Kianoosh Taghikhani, Ahmad Moeineddin, Michael Kaliske, Markus Apel 2024-07-04 ArXiv 0 18
visibility_off Paired Autoencoders for Inverse Problems Matthias Chung, Emma Hart, Julianne Chung, B. Peters, Eldad Haber 2024-05-21 ArXiv 0 13
visibility_off Efficiently Parameterized Neural Metriplectic Systems Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask 2024-05-25 ArXiv 0 2
visibility_off Improving Generalization of Deep Neural Networks by Optimum Shifting Yuyan Zhou, Ye Li, Lei Feng, Sheng-Jun Huang 2024-05-23 ArXiv 0 1
visibility_off Enhancing lattice kinetic schemes for fluid dynamics with Lattice-Equivariant Neural Networks Giulio Ortali, Alessandro Gabbana, Imre Atmodimedjo, Alessandro Corbetta 2024-05-22 ArXiv 0 17
visibility_off VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification Paolo Conti, Jonas Kneifl, Andrea Manzoni, A. Frangi, Jörg Fehr, S. Brunton, J. Kutz 2024-05-31 ArXiv 0 63
visibility_off GPINN with Neural Tangent Kernel Technique for Nonlinear Two Point Boundary Value Problems Navnit Jha, Ekansh Mallik 2024-05-31 Neural Process. Lett. 0 0
visibility_off Flexible and Efficient Surrogate Gradient Modeling with Forward Gradient Injection Sebastian Otte 2024-05-31 ArXiv 0 0
visibility_off Convergence of Implicit Gradient Descent for Training Two-Layer Physics-Informed Neural Networks Xianliang Xu, Zhongyi Huang, Ye Li 2024-07-03 ArXiv 0 1
visibility_off Adapting Physics-Informed Neural Networks To Optimize ODEs in Mosquito Population Dynamics D. V. Cuong, Branislava Lali'c, Mina Petri'c, Binh Nguyen, M. Roantree 2024-06-07 ArXiv 0 17
visibility_off Recurrent neural chemical reaction networks that approximate arbitrary dynamics Alexander Dack, Benjamin Qureshi, T. Ouldridge, Tomislav Plesa 2024-06-05 ArXiv 0 32
visibility_off Hierarchical Neural Networks, p-Adic PDEs, and Applications to Image Processing W. A. Z'uniga-Galindo, B. A. Zambrano-Luna, Baboucarr Dibba 2024-06-12 ArXiv 0 3
visibility_off Training Dynamics of Nonlinear Contrastive Learning Model in the High Dimensional Limit Lineghuan Meng, Chuang Wang 2024-06-11 ArXiv 0 0
visibility_off Neural Laplace for learning Stochastic Differential Equations Adrien Carrel 2024-06-07 ArXiv 0 0
visibility_off Approximation and Gradient Descent Training with Neural Networks G. Welper 2024-05-19 ArXiv 0 1
visibility_off Error Analysis of Three-Layer Neural Network Trained with PGD for Deep Ritz Method Yuling Jiao, Yanming Lai, Yang Wang 2024-05-19 ArXiv 0 6
visibility_off Jacobian-Enhanced Neural Networks Steven H. Berguin 2024-06-13 ArXiv 0 5
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 Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems Amanda Howard, Bruno Jacob, Sarah H. Murphy, Alexander Heinlein, P. Stinis 2024-06-28 ArXiv 0 12
visibility_off A Nonoverlapping Domain Decomposition Method for Extreme Learning Machines: Elliptic Problems Chang-Ock Lee, Youngkyu Lee, Byungeun Ryoo 2024-06-22 ArXiv 0 0
visibility_off Nonlinear denoising score matching for enhanced learning of structured distributions Jeremiah Birrell, M. Katsoulakis, Luc Rey-Bellet, Benjamin J. Zhang, Wei Zhu 2024-05-24 ArXiv 0 31
visibility_off Scalable Optimization in the Modular Norm Tim Large, Yang Liu, Minyoung Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein 2024-05-23 ArXiv 0 9
visibility_off Structured and Balanced Multi-component and Multi-layer Neural Networks Shijun Zhang, Hongkai Zhao, Yimin Zhong, Haomin Zhou 2024-06-30 ArXiv 0 3
visibility_off Provable Statistical Rates for Consistency Diffusion Models Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang 2024-06-23 ArXiv 0 4
visibility_off AdaFisher: Adaptive Second Order Optimization via Fisher Information Damien Martins Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini 2024-05-26 ArXiv 0 7
visibility_off Bridging pharmacology and neural networks: A deep dive into neural ordinary differential equations. Idris Bachali Losada, N. Terranova 2024-07-11 CPT: pharmacometrics & systems pharmacology 0 12
visibility_off WgLaSDI: Weak-Form Greedy Latent Space Dynamics Identification Xiaolong He, April Tran, David M. Bortz, Youngsoo Choi 2024-06-29 ArXiv 0 3
visibility_off HyperInterval: Hypernetwork approach to training weight interval regions in continual learning Patryk Krukowski, Anna Bielawska, Kamil Ksiazek, Pawel Wawrzy'nski, Pawel Batorski, Przemyslaw Spurek 2024-05-24 ArXiv 0 1
visibility_off Nuclear Norm Regularization for Deep Learning Christopher Scarvelis, Justin Solomon 2024-05-23 ArXiv 0 3
visibility_off Enhancing Multiscale Simulations with Constitutive Relations-Aware Deep Operator Networks Hamidreza Eivazi, Mahyar Alikhani, Jendrik-Alexander Tröger, Stefan H. A. Wittek, Stefan Hartmann, Andreas Rausch 2024-05-22 ArXiv 0 10
visibility_off Negative order Sobolev cubatures: preconditioners of partial differential equation learning tasks circumventing numerical stiffness Juan-Esteban Suarez Cardona, Phil-Alexander Hofmann, Michael Hecht 2024-07-12 Machine Learning: Science and Technology 0 1
visibility_off Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations Chuqi Chen, Yahong Yang, Yang Xiang, Wenrui Hao 2024-05-23 ArXiv 0 1
visibility_off Bounds on the approximation error for deep neural networks applied to dispersive models: Nonlinear waves Claudio Munoz, Nicol'as Valenzuela 2024-05-22 ArXiv 0 2
visibility_off Stratified Sampling Algorithms for Machine Learning Methods in Solving Two-scale Partial Differential Equations Eddel El'i Ojeda Avil'es, Daniel Olmos-Liceaga, Jae-Hun Jung 2024-05-24 ArXiv 0 4
visibility_off VS-PINN: A Fast and efficient training of physics-informed neural networks using variable-scaling methods for solving PDEs with stiff behavior Seungchan Ko, Sang Hyeon Park 2024-06-10 ArXiv 0 0
visibility_off An Efficient Approach to Regression Problems with Tensor Neural Networks Yongxin Li 2024-06-14 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 Simplicits: Mesh-Free, Geometry-Agnostic, Elastic Simulation Vismay Modi, Nicholas Sharp, Or Perel, S. Sueda, David I. W. Levin 2024-06-09 ArXiv 0 19
visibility_off APTT: An accuracy-preserved tensor-train method for the Boltzmann-BGK equation Zhitao Zhu, Chuanfu Xiao, Keju Tang, Jizu Huang, Chao Yang 2024-05-21 ArXiv 0 7
visibility_off pythOS: A Python library for solving IVPs by operator splitting Victoria Guenter, Siqi Wei, Raymond J. Spiteri 2024-07-07 ArXiv 0 3
visibility_off On the estimation rate of Bayesian PINN for inverse problems Yi Sun, Debarghya Mukherjee, Yves Atchadé 2024-06-21 ArXiv 0 7
visibility_off Enhancing neural operator learning with invariants to simultaneously learn various physical mechanisms Siran Li, Chong Liu, Hao Ni 2024-06-06 National Science Review 0 1
visibility_off An Unconstrained Formulation of Some Constrained Partial Differential Equations and its Application to Finite Neuron Methods Jiwei Jia, Young Ju Lee, Ruitong Shan 2024-05-27 ArXiv 0 0
visibility_off Infinite Limits of Multi-head Transformer Dynamics Blake Bordelon, Hamza Tahir Chaudhry, C. Pehlevan 2024-05-24 ArXiv 0 24
visibility_off Out-of-Distribution Detection with a Single Unconditional Diffusion Model Alvin Heng, Alexandre H. Thiery, Harold Soh 2024-05-20 ArXiv 0 4
visibility_off Learning unbounded-domain spatiotemporal differential equations using adaptive spectral methods Mingtao Xia, Xiangting Li, Qijing Shen, Tom Chou 2024-06-03 Journal of Applied Mathematics and Computing 0 9
visibility_off On the Hardness of Probabilistic Neurosymbolic Learning Jaron Maene, Vincent Derkinderen, L. D. Raedt 2024-06-06 ArXiv 0 66
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 Constrained or Unconstrained? Neural-Network-Based Equation Discovery from Data Grant Norman, Jacqueline Wentz, H. Kolla, K. Maute, Alireza Doostan 2024-05-30 ArXiv 0 51
visibility_off A discretization-free deep neural network-based approach for advection-dispersion-reaction mechanisms Hande Uslu Tuna, Murat Sari, Tahir Cosgun 2024-05-30 Physica Scripta 0 3
visibility_off RBF-Assisted Hybrid Neural Network for Solving Partial Differential Equations Ying Li, Wei Gao, Shihui Ying 2024-05-21 Mathematics 0 3
visibility_off Glauber Generative Model: Discrete Diffusion Models via Binary Classification Harshit Varma, Dheeraj M. Nagaraj, Karthikeyan Shanmugam 2024-05-27 ArXiv 0 13
visibility_off Enhancing Fast Feed Forward Networks with Load Balancing and a Master Leaf Node Andreas Charalampopoulos, Nikolas Chatzis, Foivos Ntoulas-Panagiotopoulos, Charilaos Papaioannou, Alexandros Potamianos 2024-05-27 ArXiv 0 2
visibility_off Deep Learning without Weight Symmetry Ji-An Li, M. Benna 2024-05-31 ArXiv 0 14
visibility_off Multistep Distillation of Diffusion Models via Moment Matching Tim Salimans, Thomas Mensink, J. Heek, Emiel Hoogeboom 2024-06-06 ArXiv 1 30
visibility_off Deep Learning for Computing Convergence Rates of Markov Chains Yanlin Qu, Jose Blanchet, Peter Glynn 2024-05-30 ArXiv 0 3
visibility_off Enhancing Graph U-Nets for Mesh-Agnostic Spatio-Temporal Flow Prediction Sunwoong Yang, Ricardo Vinuesa, Namwoo Kang 2024-06-06 ArXiv 0 1
visibility_off Axiomatization of Gradient Smoothing in Neural Networks Linjiang Zhou, Xiaochuan Shi, Chao Ma, Zepeng Wang 2024-06-29 ArXiv 0 10
visibility_off Latent Neural Operator for Solving Forward and Inverse PDE Problems Tian Wang, Chuang Wang 2024-06-06 ArXiv 0 0
visibility_off Amortizing intractable inference in diffusion models for vision, language, and control S. Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Y. Bengio, Glen Berseth, Nikolay Malkin 2024-05-31 ArXiv 1 40
visibility_off Delay Embedding Theory of Neural Sequence Models Mitchell Ostrow, Adam J. Eisen, I. Fiete 2024-06-17 ArXiv 0 30
visibility_off Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure Can Pouliquen, Mathurin Massias, Titouan Vayer 2024-06-13 ArXiv 0 10
visibility_off Inference for Delay Differential Equations Using Manifold-Constrained Gaussian Processes Yuxuan Zhao, Samuel W. K. Wong 2024-06-21 ArXiv 0 1
visibility_off Asymptotic generalization errors in the online learning of random feature models Roman Worschech, Bernd Rosenow 2024-06-03 Physical Review Research 0 1
visibility_off Thermodynamic Natural Gradient Descent Kaelan Donatella, Samuel Duffield, Maxwell Aifer, Denis Melanson, Gavin Crooks, Patrick J. Coles 2024-05-22 ArXiv 0 4
visibility_off Neural networks in non-metric spaces Luca Galimberti 2024-06-13 ArXiv 0 0
visibility_off Physics and geometry informed neural operator network with application to acoustic scattering S. Nair, Timothy F. Walsh, Greg Pickrell, Fabio Semperlotti 2024-06-02 ArXiv 0 4
visibility_off Grokking Modular Polynomials Darshil Doshi, Tianyu He, Aritra Das, Andrey Gromov 2024-06-05 ArXiv 0 4
visibility_off How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing Keke Huang, Yu Guang Wang, Ming Li, Pietro Liò 2024-05-21 ArXiv 1 3
visibility_off Feature learning in finite-width Bayesian deep linear networks with multiple outputs and convolutional layers Federico Bassetti, M. Gherardi, Alessandro Ingrosso, M. Pastore, P. Rotondo 2024-06-05 ArXiv 1 14
visibility_off An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations Shengbo Wang, Jose Blanchet, Peter Glynn 2024-07-14 ArXiv 0 3
visibility_off Deep linear networks for regression are implicitly regularized towards flat minima Pierre Marion, L'enaic Chizat 2024-05-22 ArXiv 1 1
visibility_off Differentiable Cluster Graph Neural Network Yanfei Dong, Mohammed Haroon Dupty, Lambert Deng, Zhuanghua Liu, Yong Liang Goh, Wee Sun Lee 2024-05-25 ArXiv 0 4
visibility_off An Adaptive Sampling Algorithm with Dynamic Iterative Probability Adjustment Incorporating Positional Information Yanbing Liu, Liping Chen, Yu Chen, J. Ding 2024-05-26 Entropy 0 10
visibility_off Advancing Graph Generation through Beta Diffusion Yilin He, Xinyang Liu, Bo Chen, Mingyuan Zhou 2024-06-13 ArXiv 0 2
visibility_off Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids Saurabh Deshpande, Hussein Rappel, Mark Hobbs, Stéphane P. A. Bordas, Jakub Lengiewicz 2024-07-15 ArXiv 0 4
visibility_off Recurrent Deep Kernel Learning of Dynamical Systems N. Botteghi, Paolo Motta, Andrea Manzoni, P. Zunino, Mengwu Guo 2024-05-30 ArXiv 0 6
visibility_off Fast Iterative Solver For Neural Network Method: II. 1D Diffusion-Reaction Problems And Data Fitting Zhiqiang Cai, Anastassia Doktorova, R. Falgout, C'esar Herrera 2024-07-01 ArXiv 0 37
visibility_off Progressive Entropic Optimal Transport Solvers Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi 2024-06-07 ArXiv 0 8
visibility_off Invariant multiscale neural networks for data-scarce scientific applications I. Schurov, D. Alforov, M. Katsnelson, A. Bagrov, A. Itin 2024-06-12 ArXiv 0 0
visibility_off DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models Hengkang Wang, Xu Zhang, Taihui Li, Yuxiang Wan, Tiancong Chen, Ju Sun 2024-05-27 ArXiv 0 7
visibility_off Dreamguider: Improved Training free Diffusion-based Conditional Generation Nithin Gopalakrishnan Nair, Vishal M. Patel 2024-06-04 ArXiv 0 6
visibility_off Mix-DDPM: Enhancing Diffusion Models through Fitting Mixture Noise with Global Stochastic Offset Hanzhang Wang, Deming Zhai, Xiong Zhou, Junjun Jiang, Xianming Liu 2024-06-07 ACM Transactions on Multimedia Computing, Communications and Applications 0 15
visibility_off Neural Persistence Dynamics Sebastian Zeng, Florian Graf, M. Uray, Stefan Huber, R. Kwitt 2024-05-24 ArXiv 0 32
visibility_off Calibrating Neural Networks' parameters through Optimal Contraction in a Prediction Problem Valdes Gonzalo 2024-06-15 ArXiv 0 0
visibility_off Integrating GNN and Neural ODEs for Estimating Two-Body Interactions in Mixed-Species Collective Motion Masahito Uwamichi, S. Schnyder, Tetsuya J. Kobayashi, Satoshi Sawai 2024-05-26 ArXiv 0 10
visibility_off Equivariant Diffusion Policy Di Wang, Stephen M. Hart, David Surovik, Tarik Kelestemur, Hao Huang, Haibo Zhao, Mark Yeatman, Jiu-yao Wang, Robin G. Walters, Robert C. Platt 2024-07-01 ArXiv 0 0
visibility_off Poseidon: Efficient Foundation Models for PDEs Maximilian Herde, Bogdan Raoni'c, Tobias Rohner, R. Käppeli, Roberto Molinaro, Emmanuel de B'ezenac, Siddhartha Mishra 2024-05-29 ArXiv 1 11
visibility_off Derivatives of Stochastic Gradient Descent F. Iutzeler, Edouard Pauwels, Samuel Vaiter 2024-05-24 ArXiv 0 17
visibility_off Error estimates of physics-informed neural networks for approximating Boltzmann equation E. Abdo, Lihui Chai, Ruimeng Hu, Xu Yang 2024-07-11 ArXiv 0 1
visibility_off Neural Data-Enabled Predictive Control Mircea Lazar 2024-06-12 ArXiv 0 1
visibility_off Probabilistic Emulation of a Global Climate Model with Spherical DYffusion Salva Rühling Cachay, Brian Henn, Oliver Watt‐Meyer, Christopher S. Bretherton, Rose Yu 2024-06-21 ArXiv 0 11
visibility_off Evaluating the design space of diffusion-based generative models Yuqing Wang, Ye He, Molei Tao 2024-06-18 ArXiv 0 1
visibility_off Neural Operator-Based Proxy for Reservoir Simulations Considering Varying Well Settings, Locations, and Permeability Fields Daniel Badawi, Eduardo Gildin 2024-07-13 ArXiv 0 1
visibility_off NeurTV: Total Variation on the Neural Domain Yisi Luo, Xile Zhao, Kai Ye, Deyu Meng 2024-05-27 ArXiv 0 4
visibility_off Machine Learning Visualization Tool for Exploring Parameterized Hydrodynamics C. Jekel, D. Sterbentz, T. M. Stitt, P. Mocz, R. Rieben, D. A. White, J. Belof 2024-06-20 ArXiv 0 21
visibility_off Dataset-learning duality and emergent criticality Ekaterina Kukleva, V. Vanchurin 2024-05-27 ArXiv 0 19
visibility_off How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang, Sean P. Cornelius 2024-07-11 ArXiv 0 1
visibility_off Composite Graph Neural Networks for Molecular Property Prediction P. Bongini, Niccolò Pancino, Asma Bendjeddou, F. Scarselli, Marco Maggini, M. Bianchini 2024-06-01 International Journal of Molecular Sciences 0 27
visibility_off Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows Thorsten Buss, F. Gaede, G. Kasieczka, Claudius Krause, David Shih 2024-05-30 ArXiv 0 11
visibility_off Physics-constrained learning for PDE systems with uncertainty quantified port-Hamiltonian models Kaiyuan Tan, Peilun Li, Thomas Beckers 2024-06-17 DBLP, ArXiv 0 1
visibility_off Expressive Symbolic Regression for Interpretable Models of Discrete-Time Dynamical Systems Adarsh Iyer, N. Boddupalli, Jeff Moehlis 2024-06-05 ArXiv 0 5
visibility_off Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training Yunshu Wu, Yingtao Luo, Xianghao Kong, E. Papalexakis, G. V. Steeg 2024-07-12 ArXiv 0 34
visibility_off Identifying latent state transition in non-linear dynamical systems cCauglar Hizli, cCaugatay Yildiz, Matthias Bethge, ST John, Pekka Marttinen 2024-06-05 ArXiv 0 2
visibility_off Flexible Heteroscedastic Count Regression with Deep Double Poisson Networks Spencer Young, P. Jenkins, Lonchao Da, Jeffrey Dotson, Hua Wei 2024-06-13 ArXiv 0 5
visibility_off Learning Diffusion Priors from Observations by Expectation Maximization François Rozet, G'erome Andry, F. Lanusse, Gilles Louppe 2024-05-22 ArXiv 0 12
visibility_off Speeding up the Training of Neural Networks with the One-Step Procedure Wajd Meskini, Alexandre Brouste, Nicolas Dugué 2024-05-21 Neural Processing Letters 0 0
visibility_off Tensor networks enable the calculation of turbulence probability distributions Nikita Gourianov, P. Givi, Dieter Jaksch, Stephen B. Pope 2024-07-12 ArXiv 0 31
visibility_off Spatial acoustic properties recovery with deep learning. Ruixian Liu, Peter Gerstoft 2024-06-01 The Journal of the Acoustical Society of America 0 4
visibility_off Improved Particle Approximation Error for Mean Field Neural Networks Atsushi Nitanda 2024-05-24 ArXiv 0 0
visibility_off Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs Ziang Chen, Xiaohan Chen, Jialin Liu, Xinshang Wang, Wotao Yin 2024-06-09 ArXiv 0 10
visibility_off Machine Learning Conservation Laws of Dynamical systems Meskerem Abebaw Mebratie, Rudiger Nather, Guido Falk von Rudorff, Werner M. Seiler 2024-05-31 ArXiv 0 5
visibility_off Approximating G(t)/GI/1 queues with deep learning Eliran Sherzer, Opher Baron, Dmitry Krass, Yehezkel S. Resheff 2024-07-11 ArXiv 0 14
visibility_off Rényi Neural Processes Xuesong Wang, He Zhao, Edwin V. Bonilla 2024-05-25 ArXiv 0 2
visibility_off Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks Wenqian Chen, Amanda Howard, P. Stinis 2024-06-28 ArXiv 0 12
visibility_off Sparse deep neural networks for nonparametric estimation in high-dimensional sparse regression Dongya Wu, Xin Li 2024-06-26 ArXiv 0 6
visibility_off On Computation of Approximate Solutions to Large-Scale Backstepping Kernel Equations via Continuum Approximation Jukka-Pekka Humaloja, N. Bekiaris-Liberis 2024-06-19 ArXiv 0 31
visibility_off NIVeL: Neural Implicit Vector Layers for Text-to-Vector Generation Vikas Thamizharasan, Difan Liu, Matthew Fisher, Nanxuan Zhao, E. Kalogerakis, Michal Lukac 2024-05-24 ArXiv 0 37
visibility_off LInK: Learning Joint Representations of Design and Performance Spaces through Contrastive Learning for Mechanism Synthesis A. Nobari, Akash Srivastava, Dan Gutfreund, Kai Xu, Faez Ahmed 2024-05-31 ArXiv 0 20
visibility_off STEP: extraction of underlying physics with robust machine learning Karim K. Alaa El-Din, Alessandro Forte, Muhammad Firmansyah Kasim, Francesco Miniati, Sam M. Vinko 2024-06-01 Royal Society Open Science 0 1
visibility_off Stochastic Gradient Descent for Two-layer Neural Networks Dinghao Cao, Zheng-Chu Guo, Lei Shi 2024-07-10 ArXiv 0 0
visibility_off Magnetic Hysteresis Modeling with Neural Operators Abhishek Chandra, B. Daniels, M. Curti, K. Tiels, E. Lomonova 2024-07-03 ArXiv 0 24
visibility_off Inferring stochastic low-rank recurrent neural networks from neural data Matthijs Pals, A. E. Saugtekin, Felix Pei, Manuel Gloeckler, J. H. Macke 2024-06-24 ArXiv 0 3
visibility_off Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Kumar Avinava Dubey, Tamás Sarlós, Snigdha Chaturvedi 2024-06-22 ArXiv 0 24
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