PINNs
This page was last updated on 2024-07-17 08:46:30 UTC
Manually curated articles on PINNs
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
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visibility_off | Solving real-world optimization tasks using physics-informed neural computing | J. Seo | 2024-01-08 | Scientific Reports | 4 | 6 | open_in_new |
visibility_off | Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade | M. Przedborski, Munisha Smalley, S. Thiyagarajan, A. Goldman, M. Kohandel | 2021-07-15 | Communications Biology | 9 | 28 | open_in_new |
visibility_off | Physics-informed machine learning | G. Karniadakis, I. Kevrekidis, Lu Lu, P. Perdikaris, Sifan Wang, Liu Yang | 2021-05-24 | Nature Reviews Physics | 2001 | 127 | open_in_new |
visibility_off | Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations | M. Raissi, P. Perdikaris, G. Karniadakis | 2017-11-28 | arXiv.org, ArXiv | 751 | 127 | open_in_new |
visibility_off | Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations | M. Raissi, P. Perdikaris, G. Karniadakis | 2017-11-28 | arXiv.org, ArXiv | 550 | 127 | open_in_new |
visibility_off | Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems | M. Raissi, P. Perdikaris, G. Karniadakis | 2018-01-04 | arXiv: Dynamical Systems | 254 | 127 | open_in_new |
visibility_off | B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data | Liu Yang, Xuhui Meng, G. Karniadakis | 2020-03-13 | Journal of Computational Physics, ArXiv | 574 | 127 | open_in_new |
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
Recommended articles on PINNs
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |
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visibility_off | Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation | Yifei Zong, D. Barajas-Solano, A. Tartakovsky | 2024-07-05 | ArXiv | 0 | 41 |
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 | An extrapolation-driven network architecture for physics-informed deep learning | Yong Wang, Yanzhong Yao, Zhiming Gao | 2024-06-18 | ArXiv | 0 | 1 |
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 | 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 | Physics-informed neural networks for parameter learning of wildfire spreading | K. Vogiatzoglou, C. Papadimitriou, V. Bontozoglou, Konstantinos Ampountolas | 2024-06-20 | ArXiv | 0 | 45 |
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 | A novel discretized physics-informed neural network model applied to the Navier–Stokes equations | Amirhossein Khademi, Steven Dufour | 2024-06-07 | Physica Scripta | 0 | 1 |
visibility_off | Structural damage inverse detection from noisy vibration measurement with physics-informed neural networks | Lei Yuan, Yi-Qing Ni, En-Ze Rui, Weijia Zhang | 2024-06-01 | Journal of Physics: Conference Series | 0 | 2 |
visibility_off | Element-wise Multiplication Based Physics-informed Neural Networks | Feilong Jiang, Xiaonan Hou, Min Xia | 2024-06-06 | 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 | 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 | Inverse Physics-Informed Neural Networks for transport models in porous materials | Marco Berardi, F. Difonzo, Matteo Icardi | 2024-07-15 | ArXiv | 0 | 9 |
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 | Pi-fusion: Physics-informed diffusion model for learning fluid dynamics | Jing Qiu, Jiancheng Huang, Xiangdong Zhang, Zeng Lin, Minglei Pan, Zengding Liu, F. Miao | 2024-06-06 | ArXiv | 1 | 20 |
visibility_off | Robust parameter estimation and identifiability analysis with Hybrid Neural Ordinary Differential Equations in Computational Biology | Stefano Giampiccolo, Federico Reali, Anna Fochesato, Giovanni Iacca, Luca Marchetti | 2024-06-12 | bioRxiv | 0 | 6 |
visibility_off | Cell-Average Based Neural Network Method for Hunter-Saxton Equations | Chunjie Zhang, Changxin Qiu, Xiaofang Zhou and Xiaoming He | 2024-01-01 | Advances in Applied Mathematics and Mechanics | 0 | 0 |
visibility_off | Physics-Informed Neural Networks Application To Mass-Spring System Solution | Martin Muzelak, T. Skovranek, Marek Ruzicka | 2024-05-22 | 2024 25th International Carpathian Control Conference (ICCC) | 0 | 13 |
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 | 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 | Solving Differential Equations using Physics-Informed Deep Equilibrium Models | Bruno Machado Pacheco, E. Camponogara | 2024-06-05 | ArXiv | 0 | 22 |
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 | Neural Differentiable Modeling with Diffusion-Based Super-resolution for Two-Dimensional Spatiotemporal Turbulence | Xiantao Fan, Deepak Akhare, Jian-Xun Wang | 2024-06-28 | ArXiv | 0 | 1 |
visibility_off | Initialization-enhanced Physics-Informed Neural Network with Domain Decomposition (IDPINN) | Chenhao Si, Ming Yan | 2024-06-05 | ArXiv | 0 | 0 |
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 | Assessment of Uncertainty Quantification in Universal Differential Equations | Nina Schmid, David Fernandes del Pozo, Willem Waegeman, Jan Hasenauer | 2024-06-13 | ArXiv | 0 | 0 |
visibility_off | Physiology-informed regularization enables training of universal differential equation systems for biological applications | Max de Rooij, Balázs Erdős, N. V. van Riel, Shauna D. O’Donovan | 2024-06-01 | bioRxiv | 0 | 5 |
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 | An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study | Milad Ramezankhani, A. Deodhar, Rishi Parekh, Dagnachew Birru | 2024-06-20 | ArXiv | 0 | 7 |
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 | Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models | G. A. Padmanabha, J. Fuhg, C. Safta, Reese E. Jones, N. Bouklas | 2024-06-30 | ArXiv | 0 | 18 |
visibility_off | Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data | M. Velioglu, Song Zhai, Sophia Rupprecht, Alexander Mitsos, Andreas Jupke, M. Dahmen | 2024-06-03 | ArXiv | 0 | 13 |
visibility_off | FlamePINN-1D: Physics-informed neural networks to solve forward and inverse problems of 1D laminar flames | Jiahao Wu, Su Zhang, Yuxin Wu, Guihua Zhang, Xin Li, Hai Zhang | 2024-06-07 | ArXiv | 0 | 1 |
visibility_off | Data-Driven Computing Methods for Nonlinear Physics Systems with Geometric Constraints | Yunjin Tong | 2024-06-20 | ArXiv | 0 | 0 |
visibility_off | Foundation Model for Chemical Process Modeling: Meta-Learning with Physics-Informed Adaptation | Zihao Wang, Zhen Wu | 2024-05-20 | ArXiv | 0 | 1 |
visibility_off | Physics-Informed Neural Network based inverse framework for time-fractional differential equations for rheology | Sukirt Thakur, H. Mitra, A. Ardekani | 2024-06-06 | ArXiv | 0 | 8 |
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 | Jacobian-Enhanced Neural Networks | Steven H. Berguin | 2024-06-13 | ArXiv | 0 | 5 |
visibility_off | Interfacial conditioning in physics informed neural networks | Saykat Kumar Biswas, N. K. Anand | 2024-07-01 | Physics of Fluids | 0 | 1 |
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 | Principal Component Flow Map Learning of PDEs from Incomplete, Limited, and Noisy Data | Victor Churchill | 2024-07-15 | ArXiv | 0 | 0 |
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 | Bayesian Entropy Neural Networks for Physics-Aware Prediction | R. Rathnakumar, Jiayu Huang, Hao Yan, Yongming Liu | 2024-07-01 | ArXiv | 0 | 3 |
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 | Auto-PICNN: Automated machine learning for physics-informed convolutional neural networks | Wanyun Zhou, Xiaowen Chu | 2024-07-08 | ArXiv | 0 | 0 |
visibility_off | Pseudo grid-based physics-informed convolutional-recurrent network solving the integrable nonlinear lattice equations | Zhenyu Lin, Yong Chen | 2024-06-25 | ArXiv | 0 | 1 |
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 | Reservoir History Matching of the Norne field with generative exotic priors and a coupled Mixture of Experts - Physics Informed Neural Operator Forward Model | C. Etienam, Juntao Yang, O. Ovcharenko, Issam Said | 2024-06-02 | ArXiv | 0 | 4 |
visibility_off | Sparse identification of quasipotentials via a combined data-driven method | Bo Lin, P. Belardinelli | 2024-07-06 | ArXiv | 0 | 12 |
visibility_off | A Short Note on Physics-Guided GAN to Learn Physical Models without Gradients | Kazuo Yonekura | 2024-06-26 | Algorithms | 0 | 12 |
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 | MgFNO: Multi-grid Architecture Fourier Neural Operator for Parametric Partial Differential Equations | Zi-Hao Guo, Hou-Biao Li | 2024-07-11 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | Physics-Informed Neural Networks for the Numerical Modeling of Steady-State and Transient Electromagnetic Problems with Discontinuous Media | Michel Nohra, Steven Dufour | 2024-06-06 | ArXiv | 0 | 1 |
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 | 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 | 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 | Adaptive Interface-PINNs (AdaI-PINNs): An Efficient Physics-informed Neural Networks Framework for Interface Problems | Sumanta Roy, C. Annavarapu, P. Roy, A. K. Sarma | 2024-06-07 | ArXiv | 1 | 1 |
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 | 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 | Generalizable Physics-Informed Learning for Stochastic Safety-Critical Systems | Zhuoyuan Wang, Albert Chern, Yorie Nakahira | 2024-07-11 | ArXiv | 0 | 10 |
visibility_off | Identification of Physical Properties in Acoustic Tubes Using Physics-Informed Neural Networks | Kazuya Yokota, Masataka Ogura, Masajiro Abe | 2024-06-17 | ArXiv | 0 | 1 |
visibility_off | Optimization Under Uncertainty Using Physics-Based Label-Free Machine Learning | Xiaoping Du | 2024-05-23 | 2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) | 0 | 0 |
visibility_off | Stochastic Inference of Plate Bending from Heterogeneous Data: Physics-informed Gaussian Processes via Kirchhoff-Love Theory | I. Kavrakov, Gledson Rodrigo Tondo, Guido Morgenthal | 2024-05-21 | ArXiv | 0 | 11 |
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 | 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 | A numerical method to solve PDE through PINN based on ODENet | Ziyi Wang | 2024-06-24 | Applied and Computational Engineering | 0 | 0 |
visibility_off | Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks | Alan A. Lahoud, Erik Schaffernicht, J. A. Stork | 2024-06-05 | ArXiv | 0 | 19 |
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 | 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 | 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 | 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 | 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 | Discovery of differential equations using sparse state and parameter regression | Teddy Meissner, Karl Glasner | 2024-06-10 | ArXiv | 0 | 0 |
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 | Application of physics encoded neural networks to improve predictability of properties of complex multi-scale systems | M. Meinders, Jack Yang, Erik van der Linden | 2024-07-01 | Scientific Reports | 0 | 29 |
visibility_off | Physics Informed Machine Learning (PIML) methods for estimating the remaining useful lifetime (RUL) of aircraft engines | Sriram Nagaraj, Truman Hickok | 2024-06-21 | ArXiv | 0 | 0 |
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 | Neural Network with Local Converging Input for Unstructured-Grid Computational Fluid Dynamics | Weiming Ding, Haoxiang Huang, T. Lee, Yingjie Liu, Vigor Yang | 2024-07-01 | AIAA Journal | 0 | 1 |
visibility_off | Enhancing the accuracy of physics-informed neural networks for indoor airflow simulation with experimental data and Reynolds-averaged Navier–Stokes turbulence model | Chi Zhang, Chihyung Wen, Yuan Jia, Y. Juan, Yee-Ting Lee, Zhengwei Chen, , Zhengtong Li | 2024-06-01 | Physics of Fluids | 0 | 14 |
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 | PhyGICS – A Physics-informed Graph Neural Network-based Intelligent HVAC Controller for Open-plan Spaces | S. Nagarathinam, Arunchandar Vasan | 2024-05-31 | Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems | 0 | 15 |
visibility_off | Deep Bayesian Filter for Bayes-faithful Data Assimilation | Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda | 2024-05-29 | ArXiv | 0 | 0 |
visibility_off | fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions | A. Aghaei | 2024-06-11 | ArXiv | 4 | 4 |
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 | 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 | 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 | 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 blended physics-based and black-box identification approach for spacecraft inertia estimation - EXTENDED VERSION | Martina Mammarella, Cesare Donati, F. Dabbene, C. Novara, C. Lagoa | 2024-05-28 | ArXiv | 0 | 24 |
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 | An Efficient Approach to Regression Problems with Tensor Neural Networks | Yongxin Li | 2024-06-14 | ArXiv | 0 | 0 |
visibility_off | System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization | Jixiang Qing, Becky D Langdon, Robert M. Lee, B. Shafei, Mark van der Wilk, Calvin Tsay, Ruth Misener | 2024-06-04 | ArXiv | 0 | 22 |
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 | Convolutional neural network based reduced order modeling for multiscale problems | Xuhan Zhang, Lijian Jiang | 2024-06-24 | ArXiv | 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 | DeltaPhi: Learning Physical Trajectory Residual for PDE Solving | Xihang Yue, Linchao Zhu, Yi Yang | 2024-06-14 | ArXiv | 0 | 41 |
visibility_off | A brief review of Reduced Order Models using intrusive and non-intrusive techniques | Guglielmo Padula, M. Girfoglio, G. Rozza | 2024-06-01 | ArXiv | 0 | 49 |
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 | GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications | Ois'in M. Morrison, F. Pichi, J. Hesthaven | 2024-06-05 | ArXiv | 0 | 64 |
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 | 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 | 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 | Physics‐informed neural operator solver and super‐resolution for solid mechanics | Chawit Kaewnuratchadasorn, Jiaji Wang, Chul‐Woo Kim | 2024-07-11 | Computer-Aided Civil and Infrastructure Engineering | 0 | 1 |
visibility_off | Learning the Hodgkin-Huxley Model with Operator Learning Techniques | Edoardo Centofanti, Massimiliano Ghiotto, L. Pavarino | 2024-06-04 | ArXiv | 0 | 20 |
visibility_off | Probabilistic Bayesian Neural Networks for Efficient Inference | Mohammed Alawad, Md Ishak | 2024-06-12 | Proceedings of the Great Lakes Symposium on VLSI 2024 | 0 | 0 |
visibility_off | Parametric Intrusive Reduced Order Models enhanced with Machine Learning Correction Terms | Anna Ivagnes, G. Stabile, G. Rozza | 2024-06-06 | ArXiv | 0 | 49 |
visibility_off | Physics-Informed Online Learning for Temperature Prediction in Metal AM | Pouyan Sajadi, M. Rahmani Dehaghani, Yifan Tang, G. G. Wang | 2024-07-01 | Materials | 0 | 2 |
visibility_off | Introducing a Physics-informed Deep Learning Framework for Bridge Scour Prediction | N. Yousefpour, Bo Wang | 2024-07-01 | ArXiv | 0 | 6 |
visibility_off | Knowledge-Guided Learning of Temporal Dynamics and its Application to Gas Turbines | Pawel Bielski, Aleksandr Eismont, Jakob Bach, Florian Leiser, D. Kottonau, Klemens Böhm | 2024-05-31 | Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems | 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 | Solving Poisson Equations using Neural Walk-on-Spheres | Hong Chul Nam, Julius Berner, A. Anandkumar | 2024-06-05 | ArXiv | 2 | 5 |
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 | Godunov Loss Functions for Modelling of Hyperbolic Conservation Laws | R. G. Cassia, R. Kerswell | 2024-05-19 | ArXiv | 0 | 44 |
visibility_off | Bridging Operator Learning and Conditioned Neural Fields: A Unifying Perspective | Sifan Wang, Jacob H. Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas, P. Perdikaris | 2024-05-22 | ArXiv | 1 | 43 |
visibility_off | Scaling up Probabilistic PDE Simulators with Structured Volumetric Information | Tim Weiland, Marvin Pförtner, Philipp Hennig | 2024-06-07 | ArXiv | 0 | 1 |
visibility_off | Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes | Peter Zaspel, Michael Gunther | 2024-06-26 | ArXiv | 0 | 0 |
visibility_off | BeamVQ: Aligning Space-Time Forecasting Model via Self-training on Physics-aware Metrics | Hao Wu, Xingjian Shi, Ziyue Huang, Penghao Zhao, Wei Xiong, Jinbao Xue, Yangyu Tao, Xiaomeng Huang, Weiyan Wang | 2024-05-27 | ArXiv | 0 | 1 |
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 | PINNs-MPF: A Physics-Informed Neural Network Framework for Multi-Phase-Field Simulation of Interface Dynamics | Seifallah Elfetni, R. D. Kamachali | 2024-07-02 | ArXiv | 0 | 14 |
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 | Application of Neural Networks to Solve the Dirichlet Problem for Areas of Complex | Sh. A. Galaburdin | 2024-07-05 | Computational Mathematics and Information Technologies | 0 | 0 |
visibility_off | Meshfree Variational Physics Informed Neural Networks (MF-VPINN): an adaptive training strategy | S. Berrone, Moreno Pintore | 2024-06-28 | ArXiv | 0 | 23 |
visibility_off | Variationally Correct Neural Residual Regression for Parametric PDEs: On the Viability of Controlled Accuracy | M. Bachmayr, Wolfgang Dahmen, Mathias Oster | 2024-05-30 | ArXiv | 0 | 17 |
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 | Graph Neural PDE Solvers with Conservation and Similarity-Equivariance | Masanobu Horie, Naoto Mitsume | 2024-05-25 | ArXiv | 0 | 0 |
visibility_off | Symplectic Methods in Deep Learning | S. Maslovskaya, S. Ober-Blöbaum | 2024-06-06 | ArXiv | 0 | 22 |
visibility_off | Data-driven discovery of self-similarity using neural networks | Ryota Watanabe, Takanori Ishii, Yuji Hirono, Hirokazu Maruoka | 2024-06-06 | 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 | 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 | Hamilton-Jacobi Based Policy-Iteration via Deep Operator Learning | Jae Yong Lee, Yeoneung Kim | 2024-06-16 | ArXiv | 1 | 5 |
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 | Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification | Christian Offen | 2024-07-10 | ArXiv | 0 | 0 |
visibility_off | Neural Green's Operators for Parametric Partial Differential Equations | Hugo Melchers, Joost Prins, Michael Abdelmalik | 2024-06-04 | ArXiv | 1 | 0 |
visibility_off | Uncertainty Quantification for Deep Learning | Peter Jan van Leeuwen, J. C. Chiu, C. Yang | 2024-05-31 | ArXiv | 0 | 2 |
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 | Physics-guided Full Waveform Inversion using Encoder-Solver Convolutional Neural Networks | Matan Goren, Eran Treister | 2024-05-27 | ArXiv | 0 | 15 |
visibility_off | Variational Quantum Framework for Partial Differential Equation Constrained Optimization | Amit Surana, Abeynaya Gnanasekaran | 2024-05-26 | ArXiv | 0 | 4 |
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 | Lagrangian Neural Networks for Reversible Dissipative Evolution | V. Sundararaghavan, Megna N. Shah, Jeff P. Simmons | 2024-05-23 | ArXiv | 0 | 32 |
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 | Magnetic Hysteresis Modeling with Neural Operators | Abhishek Chandra, B. Daniels, M. Curti, K. Tiels, E. Lomonova | 2024-07-03 | ArXiv | 0 | 24 |
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 | Gaussian process kernels for partial physical insight | Matthew R. Jones, D. J. Pitchforth, E. J. Cross | 2024-07-01 | e-Journal of Nondestructive Testing | 0 | 3 |
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 | Deep learning in data science: Theoretical foundations, practical applications, and comparative analysis | Yingxuan Chai, Liangning Jin | 2024-06-21 | Applied and Computational Engineering | 0 | 0 |
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 | 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 | 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 | Shallow Recurrent Decoder for Reduced Order Modeling of Plasma Dynamics | J. Kutz, M. Reza, F. Faraji, A. Knoll | 2024-05-20 | ArXiv | 1 | 31 |
visibility_off | A generative machine learning surrogate model of plasma turbulence | B. Clavier, D. Zarzoso, D. del-Castillo-Negrete, E. Frenord | 2024-05-21 | ArXiv | 0 | 0 |
visibility_off | A Deep-Learning-Based Reservoir Surrogate for Performance Forecast and Nonlinearly Constrained Life-Cycle Production Optimization Under Geological Uncertainty | Q. Nguyen, Mustafa Onur | 2024-06-26 | Day 3 Fri, June 28, 2024 | 0 | 4 |
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 | 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 | Output Range Analysis for Deep Neural Networks based on Simulated Annealing Processes | Helder Rojas, Nilton Rojas, B. EspinozaJ., Luis Huamanchumo | 2024-07-02 | ArXiv | 0 | 0 |
visibility_off | Spectral-Refiner: Fine-Tuning of Accurate Spatiotemporal Neural Operator for Turbulent Flows | Shuhao Cao, Francesco Brarda, Ruipeng Li, Yuanzhe Xi | 2024-05-27 | ArXiv | 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 | How Inductive Bias in Machine Learning Aligns with Optimality in Economic Dynamics | Mahdi Ebrahimi Kahou, James Yu, Jesse Perla, Geoff Pleiss | 2024-06-04 | ArXiv | 0 | 2 |
visibility_off | A hybrid FEM-NN optimization method to learn the physics-constrained constitutive relations from full-field data | Xinxin Wu Kaiqiang Sun, Shaohua Yang, Huan Wang, Ye Xu, Yin Zhang, Sheng Mao | 2024-06-24 | ArXiv | 0 | 0 |
visibility_off | Gradient matching accelerates mixed-effects inference for biochemical networks | Yulan B van Oppen, Andreas Milias-Argeitis | 2024-06-12 | bioRxiv | 0 | 15 |
visibility_off | Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction | Zhiming Zhang, Shangce Gao, Mengchu Zhou, Mengtao Yan, Shuyang Cao | 2024-06-01 | IEEE/CAA Journal of Automatica Sinica | 0 | 14 |
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 | Accelerating Phase Field Simulations Through a Hybrid Adaptive Fourier Neural Operator with U-Net Backbone | Christophe Bonneville, N. Bieberdorf, Arun Hegde, Mark Asta, H. Najm, Laurent Capolungo, C. Safta | 2024-06-24 | ArXiv | 0 | 44 |
visibility_off | Realizability-Informed Machine Learning for Turbulence Anisotropy Mappings | R. McConkey, Eugene Yee, F. Lien | 2024-06-17 | ArXiv | 0 | 36 |
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 | A generalized neural tangent kernel for surrogate gradient learning | Luke Eilers, Raoul-Martin Memmesheimer, Sven Goedeke | 2024-05-24 | ArXiv | 0 | 22 |
visibility_off | Predicting AI Agent Behavior through Approximation of the Perron-Frobenius Operator | Shiqi Zhang, D. Gadginmath, Fabio Pasqualetti | 2024-06-04 | ArXiv | 0 | 3 |
visibility_off | A physics-constrained and data-driven method for modeling supersonic flow | Tong Zhao, Jian An, Yuming Xu, Guoqiang He, Fei Qin | 2024-06-01 | Physics of Fluids | 0 | 0 |
visibility_off | Comparing AI versus Optimization Workflows for Simulation-Based Inference of Spatial-Stochastic Systems | Michael A. Ramirez-Sierra, T. Sokolowski | 2024-07-15 | ArXiv | 0 | 7 |
visibility_off | Graph Structure Learning with Interpretable Bayesian Neural Networks | Max Wasserman, Gonzalo Mateos | 2024-06-20 | ArXiv | 0 | 3 |
visibility_off | Explainable Bayesian Recurrent Neural Smoother to Capture Global State Evolutionary Correlations | Shi Yan, Yan Liang, Huayu Zhang, Le Zheng, Difan Zou, Binglu Wang | 2024-06-17 | ArXiv | 0 | 3 |
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 | Inferring the time-varying coupling of dynamical systems with temporal convolutional autoencoders | Josuan Calderon, Gordon J. Berman | 2024-06-05 | ArXiv | 0 | 1 |
visibility_off | Modeling Power-Bus Structures with Physics-Informed Neural Networks | Kazuhiro Fujita | 2024-05-20 | 2024 IEEE Joint International Symposium on Electromagnetic Compatibility, Signal & Power Integrity: EMC Japan / Asia-Pacific International Symposium on Electromagnetic Compatibility (EMC Japan/APEMC Okinawa) | 0 | 0 |
visibility_off | Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows | Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart | 2024-06-25 | ArXiv | 0 | 2 |
visibility_off | Machine learning in biological physics: From biomolecular prediction to design | Jonathan Martin, Marcos Lequerica Mateos, J. Onuchic, Ivan Coluzza, F. Morcos | 2024-06-24 | Proceedings of the National Academy of Sciences of the United States of America | 1 | 95 |
visibility_off | Learning Diffusion at Lightspeed | Antonio Terpin, Nicolas Lanzetti, Florian Dörfler | 2024-06-18 | ArXiv | 0 | 10 |
visibility_off | Distributed computing for physics-based data-driven reduced modeling at scale: Application to a rotating detonation rocket engine | Ionut-Gabriel Farcas, Rayomand P. Gundevia, R. Munipalli, Karen E. Willcox | 2024-07-13 | ArXiv | 0 | 13 |
visibility_off | Symmetry-Informed Governing Equation Discovery | Jianwei Yang, Wang Rao, Nima Dehmamy, R. Walters, Rose Yu | 2024-05-27 | ArXiv | 0 | 20 |
visibility_off | Visual Analysis of Prediction Uncertainty in Neural Networks for Deep Image Synthesis. | Soumya Dutta, Faheem Nizar, Ahmad Amaan, Ayan Acharya | 2024-05-22 | IEEE transactions on visualization and computer graphics | 0 | 0 |
visibility_off | Neural Network Representations of Multiphase Equations of State | George A. Kevrekidis, Daniel A. Serino, Alexander Kaltenborn, J. Gammel, J. Burby, Marc L. Klasky | 2024-06-28 | ArXiv | 0 | 16 |
visibility_off | Ensemble and Mixture-of-Experts DeepONets For Operator Learning | Ramansh Sharma, Varun Shankar | 2024-05-20 | ArXiv | 0 | 2 |
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 | Strategies for Pretraining Neural Operators | Anthony Y. Zhou, Cooper Lorsung, AmirPouya Hemmasian, A. Farimani | 2024-06-12 | ArXiv | 0 | 33 |
visibility_off | An improved physical information network for forecasting the motion response of ice floes under waves | Xiao Peng, Chunhui Wang, Guihua Xia, Fenglei Han, Zhuoyan Liu, Wangyuan Zhao, Jianfeng Yang, Qi Lin | 2024-07-01 | Physics of Fluids | 0 | 7 |
visibility_off | Removing 65 Years of Approximation in Rotating Ring Disk Electrode Theory with Physics-Informed Neural Networks | Haotian Chen, Bedřich Smetana, V. Novák, Yuanmin Zhang, S. Sokolov, Enno Kätelhön, Zhiyao Luo, Mingcheng Zhu, Richard G. Compton | 2024-06-10 | The Journal of Physical Chemistry Letters | 0 | 24 |
visibility_off | Promising directions of machine learning for partial differential equations. | Steve Brunton, J. Kutz | 2024-06-28 | Nature computational science | 2 | 1 |
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 | 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 | Optimal deep learning of holomorphic operators between Banach spaces | Ben Adcock, N. Dexter, S. Moraga | 2024-06-20 | ArXiv | 0 | 9 |
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 | Rényi Neural Processes | Xuesong Wang, He Zhao, Edwin V. Bonilla | 2024-05-25 | ArXiv | 0 | 2 |
visibility_off | Differential Transform Method and Neural Network for Solving Variational Calculus Problems | R. Brociek, M. Pleszczyński | 2024-07-11 | Mathematics | 0 | 9 |
visibility_off | On instabilities in neural network-based physics simulators | Daniel Floryan | 2024-06-18 | ArXiv | 0 | 0 |
visibility_off | Minimum Reduced-Order Models via Causal Inference | Nan Chen, Honghu Liu | 2024-06-29 | ArXiv | 0 | 0 |
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 | Bayesian Inference with Deep Weakly Nonlinear Networks | Boris Hanin, Alexander Zlokapa | 2024-05-26 | ArXiv | 0 | 10 |
visibility_off | On the generalization discrepancy of spatiotemporal dynamics-informed graph convolutional networks | Yue Sun, Chao Chen, Yuesheng Xu, Sihong Xie, Rick S. Blum, Parv Venkitasubramaniam | 2024-07-12 | Frontiers in Mechanical Engineering | 0 | 1 |
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 | Enhancing Bayesian model updating in structural health monitoring via learnable mappings | Matteo Torzoni, Andrea Manzoni, Stefano Mariani | 2024-05-22 | ArXiv | 0 | 6 |
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 | Enhancing autonomous driving systems with deep learning and spatial channel attention mechanisms: an experimental study | Yao Yao | 2024-05-22 | None | 0 | 0 |
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 | Strategies for multi-case physics-informed neural networks for tube flows: a study using 2D flow scenarios. | Hong Shen Wong, Wei Xuan Chan, Bing Huan Li, C. Yap | 2024-05-21 | Scientific reports | 0 | 24 |
visibility_off | Lattice physics approaches for neural networks | G. Bardella, Simone Franchini, P. Pani, S. Ferraina | 2024-05-20 | ArXiv | 0 | 35 |
visibility_off | Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models | Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao | 2024-06-06 | ArXiv | 0 | 6 |
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 | Physics-Informed Critic in an Actor-Critic Reinforcement Learning for Swimming in Turbulence | Christopher Koh, Laurent Pagnier, Michael Chertkov | 2024-06-05 | ArXiv | 0 | 7 |
visibility_off | A novel machine learning framework informed by the fractional calculus dynamic model of hybrid glass/jute woven composite | Xiaomeng Wang, Michal Petrů | 2024-06-15 | Journal of Applied Polymer Science | 0 | 0 |
visibility_off | Transfer Learning based High-Speed Link Transient Modeling Method | Jiarui Qiu, Hanzhi Ma, Fengzhao Zhang, Guangyu Sheng, Er-ping Li | 2024-05-20 | 2024 IEEE Joint International Symposium on Electromagnetic Compatibility, Signal & Power Integrity: EMC Japan / Asia-Pacific International Symposium on Electromagnetic Compatibility (EMC Japan/APEMC Okinawa) | 0 | 8 |
visibility_off | On examining the predictive capabilities of two variants of PINN in validating localised wave solutions in the generalized nonlinear Schr\"{o}dinger equation | K. Thulasidharan, N. Sinthuja, N. VishnuPriya, M. Senthilvelan | 2024-07-10 | ArXiv | 0 | 3 |
visibility_off | ElastoGen: 4D Generative Elastodynamics | Yutao Feng, Yintong Shang, Xiang Feng, Lei Lan, Shandian Zhe, Tianjia Shao, Hongzhi Wu, Kun Zhou, Hao Su, Chenfanfu Jiang, Yin Yang | 2024-05-23 | ArXiv | 1 | 21 |
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 | Bayesian vs. PAC-Bayesian Deep Neural Network Ensembles | Nick Hauptvogel, Christian Igel | 2024-06-08 | ArXiv | 0 | 0 |
visibility_off | Deep Koopman Learning using the Noisy Data | Wenjian Hao, Devesh Upadhyay, Shaoshuai Mou | 2024-05-26 | ArXiv | 0 | 3 |
visibility_off | A physics-inspired evolutionary machine learning method: from the Schr\"odinger equation to an orbital-free-DFT kinetic energy functional | Juan I Rodríguez, Ulises A Vergara-Beltran | 2024-05-28 | ArXiv | 0 | 1 |
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 | Benign overfitting in Fixed Dimension via Physics-Informed Learning with Smooth Inductive Bias | Honam Wong, Wendao Wu, Fanghui Liu, Yiping Lu | 2024-06-13 | ArXiv | 0 | 0 |
visibility_off | Investigating embedded data distribution strategy on reconstruction accuracy of flow field around the crosswind-affected train based on physics-informed neural networks | Guangqing Zeng, Zhengwei Chen, Yi-Qing Ni, En-Ze Rui | 2024-05-28 | International Journal of Numerical Methods for Heat & Fluid Flow | 0 | 3 |
visibility_off | Probing the effects of broken symmetries in machine learning | Marcel F. Langer, S. Pozdnyakov, Michele Ceriotti | 2024-06-25 | ArXiv | 0 | 9 |
visibility_off | Learning deformable linear object dynamics from a single trajectory | Shamil Mamedov, A. R. Geist, Ruan Viljoen, Sebastian Trimpe, Jan Swevers | 2024-07-03 | ArXiv | 0 | 6 |
visibility_off | A Best-Fitting B-Spline Neural Network Approach to the Prediction of Advection–Diffusion Physical Fields with Absorption and Source Terms | Xuedong Zhu, Jianhua Liu, Xiaohui Ao, Sen He, Lei Tao, Feng Gao | 2024-07-04 | Entropy | 0 | 6 |
visibility_off | Large language models, physics-based modeling, experimental measurements: the trinity of data-scarce learning of polymer properties | Ning Liu, S. Jafarzadeh, B. Lattimer, Shuna Ni, Jim Lua, Yue Yu | 2024-07-03 | ArXiv | 0 | 30 |
visibility_off | Fast Inference Using Automatic Differentiation and Neural Transport in Astroparticle Physics | Dorian W. P. Amaral, Shixiao Liang, Juehang Qin, Christopher Tunnell | 2024-05-23 | ArXiv | 0 | 0 |
visibility_off | A variational deep-learning approach to modeling memory T cell dynamics | C. V. van Dorp, Joshua I. Gray, Daniel H. Paik, Donna L. Farber, Andrew J. Yates | 2024-07-11 | bioRxiv | 0 | 10 |
visibility_off | Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems | Jiawei Zhang, Jiaxin Zhuang, Cheng Jin, Gen Li, Yuantao Gu | 2024-06-11 | ArXiv | 0 | 13 |
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 | Exploring the dynamics of monkeypox transmission with data-driven methods and a deterministic model | Haridas K. Das | 2024-05-22 | Frontiers in Epidemiology | 0 | 0 |
visibility_off | Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments | Yeonju Go, D. Torbunov, T. Rinn, Yi Huang, Haiwang Yu, B. Viren, Meifeng Lin, Yihui Ren, Jin-zhi Huang | 2024-05-23 | ArXiv | 0 | 28 |
visibility_off | Precipitation Nowcasting Using Physics Informed Discriminator Generative Models | Junzhe Yin, Cristian Meo, Ankush Roy, Zeineh Bou Cher, Yanbo Wang, R. Imhoff, R. Uijlenhoet, Justin Dauwels | 2024-06-14 | ArXiv | 0 | 55 |
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 | Robust and highly scalable estimation of directional couplings from time-shifted signals | Luca Ambrogioni, Louis Rouillard, Demian Wassermann | 2024-06-04 | ArXiv | 0 | 2 |
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 | Exploring the Global Dynamics of Networks Trained through Equilibrium Propagation | Gianluca Zoppo, F. Corinto, M. Gilli | 2024-05-19 | 2024 IEEE International Symposium on Circuits and Systems (ISCAS) | 0 | 26 |
visibility_off | Glassy dynamics in deep neural networks: A structural comparison | Max Kerr Winter, Liesbeth M. C. Janssen | 2024-05-21 | ArXiv | 0 | 0 |
visibility_off | Latent Neural Operator for Solving Forward and Inverse PDE Problems | Tian Wang, Chuang Wang | 2024-06-06 | ArXiv | 0 | 0 |
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 | 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 | Calibrating Neural Networks' parameters through Optimal Contraction in a Prediction Problem | Valdes Gonzalo | 2024-06-15 | ArXiv | 0 | 0 |
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 | A Generative Approach to Control Complex Physical Systems | Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu | 2024-07-09 | ArXiv | 0 | 1 |
visibility_off | A non-anticipative learning-optimization framework for solving multi-stage stochastic programs | Dogacan Yilmaz, I. E. Büyüktahtakin | 2024-07-03 | Annals of Operations Research | 0 | 17 |
visibility_off | Exploration of methods for computing sensitivities in ODE models at dynamic and steady states | Polina Lakrisenko, Dilan Pathirana, Daniel Weindl, J. Hasenauer | 2024-05-26 | ArXiv | 0 | 36 |
visibility_off | Dynamical Mean-Field Theory of Self-Attention Neural Networks | 'Angel Poc-L'opez, Miguel Aguilera | 2024-06-11 | ArXiv | 0 | 0 |
visibility_off | Unsteady flow-field forecasting leveraging a hybrid deep-learning architecture | Chunyu Guo, Yonghao Wang, Yang Han, Minglei Ji, Yanyuan Wu | 2024-06-01 | Physics of Fluids | 0 | 5 |
visibility_off | Accelerating wavepacket propagation with machine learning | Kanishka Singh, Ka Hei Lee, Daniel Peláez, A. Bande | 2024-06-21 | Journal of Computational Chemistry | 0 | 12 |
visibility_off | Physics-Informed Geometric Operators to Support Surrogate, Dimension Reduction and Generative Models for Engineering Design | Shahroz Khan, Zahid Masood, Muhammad Usama, Konstantinos V. Kostas, P. Kaklis, Wei Chen | 2024-07-10 | ArXiv | 0 | 21 |
visibility_off | Calibration of stochastic, agent-based neuron growth models with Approximate Bayesian Computation | Tobias Duswald, Lukas Breitwieser, Thomas Thorne, Barbara Wohlmuth, Roman Bauer | 2024-05-22 | ArXiv | 0 | 5 |
visibility_off | Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity | Arif Masud, Shoaib A. Goraya | 2024-07-04 | International Journal for Numerical Methods in Engineering | 0 | 3 |
visibility_off | Reduced-Order Modeling of Steady and Unsteady Flows with Deep Neural Networks | Bryan Barraza, Andreas Gross | 2024-06-24 | Aerospace | 0 | 1 |
visibility_off | Recurrent Stochastic Configuration Networks for Temporal Data Analytics | Dianhui Wang, Gang Dang | 2024-06-21 | ArXiv | 0 | 1 |
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 | 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 | 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 |
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Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |