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Thermodynamics of learning physical phenomena

26 July 2022

Papers citing "Thermodynamics of learning physical phenomena"

50 / 53 papers shown

Title
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research Fabian Eitel Marc-Andre Schulz Moritz Seiler Henrik Walter K. Ritter AI4CE 52 44 0 20 Jan 2023
Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 74 13 0 03 Nov 2022
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces Sølve Eidnes Alexander J. Stasik Camilla Sterud Eivind Bøhn S. Riemer-Sørensen 65 20 0 06 Jun 2022
NN-EUCLID: deep-learning hyperelasticity without stress data Prakash Thakolkaran Akshay Joshi Yiwen Zheng Moritz Flaschel L. Lorenzis Siddhant Kumar 68 102 0 04 May 2022
Simulating Liquids with Graph Networks Jonathan Klimesch Philipp Holl Nils Thuerey GNN AI4CE 70 8 0 14 Mar 2022
A Thermodynamics-informed Active Learning Approach to Perception and Reasoning about Fluids B. Moya Alberto Badías D. González Francisco Chinesta Elías Cueto AI4CE 49 12 0 11 Mar 2022
Thermodynamics-informed graph neural networks Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto AI4CE PINN 69 31 0 03 Mar 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 64 16 0 28 Feb 2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks Nate Gruver Marc Finzi Samuel Stanton A. Wilson AI4CE 50 41 0 10 Feb 2022
Physical Design using Differentiable Learned Simulators Kelsey R. Allen Tatiana López-Guevara Kimberly L. Stachenfeld Alvaro Sanchez-Gonzalez Peter W. Battaglia Jessica B. Hamrick Tobias Pfaff AI4CE 91 44 0 01 Feb 2022
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics Rui Wang Robin Walters Rose Yu 88 80 0 28 Jan 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 112 1,264 0 14 Jan 2022
Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach Luca Furieri C. Galimberti M. Zakwan Giancarlo Ferrari-Trecate 65 21 0 16 Dec 2021
Lagrangian Neural Network with Differentiable Symmetries and Relational Inductive Bias Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 75 4 0 07 Oct 2021
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 114 640 0 02 Sep 2021
GFINNs: GENERIC Formalism Informed Neural Networks for Deterministic and Stochastic Dynamical Systems Zhen Zhang Yeonjong Shin George Karniadakis AI4CE 62 52 0 31 Aug 2021
Multiscale modeling of inelastic materials with Thermodynamics-based Artificial Neural Networks (TANN) Filippo Masi I. Stefanou AI4CE 74 90 0 30 Aug 2021
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems Shaan Desai M. Mattheakis David Sondak P. Protopapas Stephen J. Roberts AI4CE 66 47 0 16 Jul 2021
Physics perception in sloshing scenes with guaranteed thermodynamic consistency B. Moya Alberto Badías D. González Francisco Chinesta Elías Cueto 59 14 0 24 Jun 2021
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 84 45 0 23 Jun 2021
Symplectic Learning for Hamiltonian Neural Networks M. David Florian Méhats 56 40 0 22 Jun 2021
Hamiltonian Deep Neural Networks Guaranteeing Non-vanishing Gradients by Design C. Galimberti Luca Furieri Liang Xu Giancarlo Ferrari-Trecate 56 33 0 27 May 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 73 1,189 0 20 May 2021
A unified framework for Hamiltonian deep neural networks C. Galimberti Liang Xu Giancarlo Ferrari-Trecate 68 5 0 27 Apr 2021
Adaptable Hamiltonian neural networks Chen-Di Han Bryan Glaz Mulugeta Haile Y. Lai AI4TS 61 26 0 25 Feb 2021
E(n) Equivariant Graph Neural Networks Victor Garcia Satorras Emiel Hoogeboom Max Welling 111 1,020 0 19 Feb 2021
Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN AI4CE 77 48 0 03 Dec 2020
NeuralSim: Augmenting Differentiable Simulators with Neural Networks Eric Heiden David Millard Erwin Coumans Yizhou Sheng Gaurav Sukhatme 56 139 0 09 Nov 2020
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints Marc Finzi Ke Alexander Wang A. Wilson AI4CE 70 129 0 26 Oct 2020
LagNetViP: A Lagrangian Neural Network for Video Prediction Christine Allen-Blanchette Sushant Veer Anirudha Majumdar Naomi Ehrich Leonard 79 31 0 24 Oct 2020
Machine Learning and Computational Mathematics Weinan E PINN AI4CE 64 61 0 23 Sep 2020
Mastering high-dimensional dynamics with Hamiltonian neural networks Scott T. Miller J. Lindner A. Choudhary S. Sinha W. Ditto PINN AI4CE 23 6 0 28 Jul 2020
Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control Yaofeng Desmond Zhong Naomi Ehrich Leonard DRL AI4CE 65 43 0 03 Jul 2020
Deep learning of thermodynamics-aware reduced-order models from data Quercus Hernandez Alberto Badías D. González Francisco Chinesta Elías Cueto PINN AI4CE 47 79 0 03 Jul 2020
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers Kiwon Um R. Brand Yun Fei Fei Philipp Holl N. Thürey AI4CE 52 271 0 30 Jun 2020
Sparse Symplectically Integrated Neural Networks Daniel M. DiPietro S. Xiong Bo Zhu 42 31 0 10 Jun 2020
Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics Manuel A. Roehrl Thomas Runkler Veronika Brandtstetter Michel Tokic Stefan Obermayer PINN 59 80 0 29 May 2020
Structure-preserving neural networks Quercus Hernandez Alberto Badías D. González Francisco Chinesta Elías Cueto PINN 116 71 0 09 Apr 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 173 435 0 10 Mar 2020
Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN AI4CE 66 80 0 20 Feb 2020
Hamiltonian neural networks for solving equations of motion M. Mattheakis David Sondak Akshunna S. Dogra P. Protopapas 76 59 0 29 Jan 2020
Physics-Informed Neural Networks for Power Systems George S. Misyris Andreas Venzke Spyros Chatzivasileiadis PINN AI4CE 67 219 0 09 Nov 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 64 217 0 30 Sep 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 209 225 0 29 Sep 2019
Port-Hamiltonian Approach to Neural Network Training Stefano Massaroli Michael Poli Federico Califano Angela Faragasso Jinkyoo Park Atsushi Yamashita Hajime Asama 47 14 0 06 Sep 2019
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M. Lutter Christian Ritter Jan Peters PINN AI4CE 60 379 0 10 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 118 894 0 04 Jun 2019
Universal Invariant and Equivariant Graph Neural Networks Nicolas Keriven Gabriel Peyré 189 292 0 13 May 2019
Model Reduction with Memory and the Machine Learning of Dynamical Systems Chao Ma Jianchun Wang E. Weinan 39 83 0 10 Aug 2018
SPNets: Differentiable Fluid Dynamics for Deep Neural Networks Connor Schenck Dieter Fox PINN 3DPC AI4CE 233 162 0 15 Jun 2018