Automatic differentiation in machine learning: a survey

20 February 2015

Papers citing "Automatic differentiation in machine learning: a survey"

50 / 333 papers shown

Title
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
Astronomia ex machina: a history, primer, and outlook on neural networks in astronomy Michael J. Smith James E. Geach 35 32 0 07 Nov 2022
A Deep Double Ritz Method (D $^2$ RM) for solving Partial Differential Equations using Neural Networks C. Uriarte David Pardo I. Muga J. Muñoz‐Matute 42 18 0 07 Nov 2022
Physics-informed neural networks for gravity currents reconstruction from limited data Mickaël G. Delcey Y. Cheny S. Richter PINN AI4CE 27 11 0 03 Nov 2022
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 29 18 0 27 Oct 2022
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain Pu Ren Chengping Rao Su Chen Jian-Xun Wang Hao Sun Yang Liu 44 41 0 25 Oct 2022
Graphically Structured Diffusion Models Christian D. Weilbach William Harvey Frank Wood DiffM 35 7 0 20 Oct 2022
Neural ODEs as Feedback Policies for Nonlinear Optimal Control I. O. Sandoval Panagiotis Petsagkourakis Ehecatl Antonio del Rio Chanona 25 9 0 20 Oct 2022
$r-$ Adaptive Deep Learning Method for Solving Partial Differential Equations Ángel J. Omella David Pardo AI4CE 31 4 0 19 Oct 2022
On Learning Fairness and Accuracy on Multiple Subgroups Changjian Shui Gezheng Xu Qi Chen Jiaqi Li Charles Ling Tal Arbel Boyu Wang Christian Gagné 46 37 0 19 Oct 2022
Asymptotic-Preserving Neural Networks for hyperbolic systems with diffusive scaling Giulia Bertaglia AI4CE 24 5 0 17 Oct 2022
Automatic Differentiation of Programs with Discrete Randomness Gaurav Arya Moritz Schauer Frank Schafer Chris Rackauckas 23 34 0 16 Oct 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations Alexander New B. Eng A. Timm A. Gearhart 20 4 0 14 Oct 2022
A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade C. Hill Lalit Ghule Jay Pathak AI4CE 33 7 0 11 Oct 2022
DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning Mengge Du Yuntian Chen Dong-juan Zhang 33 0 0 04 Oct 2022
MSRL: Distributed Reinforcement Learning with Dataflow Fragments Huanzhou Zhu Bo Zhao Gang Chen Weifeng Chen Yijie Chen Liang Shi Yaodong Yang Peter R. Pietzuch Lei Chen OffRL MoE 16 6 0 03 Oct 2022
Belief propagation generalizes backpropagation F. Eaton 3DV AI4CE 8 0 0 02 Oct 2022
On Physics-Informed Neural Networks for Quantum Computers Stefano Markidis PINN 32 18 0 28 Sep 2022
Neural Networks Based on Power Method and Inverse Power Method for Solving Linear Eigenvalue Problems Qihong Yang Yangtao Deng Yu Yang Qiaolin He Shiquan Zhang 16 13 0 22 Sep 2022
Compressing Sign Information in DCT-based Image Coding via Deep Sign Retrieval Kei Suzuki Chihiro Tsutake Keita Takahashi T. Fujii 26 3 0 21 Sep 2022
RAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed Neural Network Sourav Sanyal Kaushik Roy PINN 42 22 0 19 Sep 2022
Computing Anti-Derivatives using Deep Neural Networks D. Chakraborty S. Gopalakrishnan PINN 14 0 0 19 Sep 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 44 9 0 13 Sep 2022
W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecasting Zakaria Elabid Tanujit Chakraborty Abdenour Hadid AI4TS 40 20 0 08 Sep 2022
Inverse modeling of nonisothermal multiphase poromechanics using physics-informed neural networks Daniel Amini E. Haghighat R. Juanes PINN AI4CE 25 32 0 07 Sep 2022
How important are activation functions in regression and classification? A survey, performance comparison, and future directions Ameya Dilip Jagtap George Karniadakis AI4CE 37 71 0 06 Sep 2022
Differentiable Programming for Earth System Modeling Maximilian Gelbrecht Alistair J R White S. Bathiany Niklas Boers 21 16 0 29 Aug 2022
Grasp'D: Differentiable Contact-rich Grasp Synthesis for Multi-fingered Hands Dylan Turpin Liquang Wang Eric Heiden Yun-Chun Chen Miles Macklin Stavros Tsogkas Sven J. Dickinson Animesh Garg 24 67 0 25 Aug 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 29 11 0 25 Aug 2022
A physically-informed Deep-Learning approach for locating sources in a waveguide Adar Kahana Symeon Papadimitropoulos Eli Turkel Dmitry Batenkov 26 3 0 07 Aug 2022
Fixed-Point Automatic Differentiation of Forward--Backward Splitting Algorithms for Partly Smooth Functions Sheheryar Mehmood Peter Ochs 33 3 0 05 Aug 2022
Neural network layers as parametric spans M. Bergomi Pietro Vertechi AI4CE 33 2 0 01 Aug 2022
High Dynamic Range and Super-Resolution from Raw Image Bursts Bruno Lecouat Thomas Eboli Jean Ponce Julien Mairal 13 22 0 29 Jul 2022
A Theoretical Framework for Inference and Learning in Predictive Coding Networks Beren Millidge Yuhang Song Tommaso Salvatori Thomas Lukasiewicz Rafal Bogacz 34 12 0 21 Jul 2022
Formal Algorithms for Transformers Mary Phuong Marcus Hutter 24 71 0 19 Jul 2022
Heuristic-free Optimization of Force-Controlled Robot Search Strategies in Stochastic Environments Bastian Alt Darko Katic Rainer Jäkel Michael Beetz 23 6 0 15 Jul 2022
Physics Informed Symbolic Networks Ritam Majumdar Vishal Sudam Jadhav A. Deodhar Shirish S. Karande L. Vig Venkataramana Runkana PINN 26 0 0 11 Jul 2022
Automatic differentiation and the optimization of differential equation models in biology S. Frank 22 6 0 10 Jul 2022
Predicting Opinion Dynamics via Sociologically-Informed Neural Networks Maya Okawa Tomoharu Iwata AI4CE PINN 26 20 0 07 Jul 2022
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems Manuela Brenner Florian Hess Jonas M. Mikhaeil Leonard Bereska Zahra Monfared Po-Chen Kuo Daniel Durstewitz AI4CE 37 29 0 06 Jul 2022
A Deep Learning Approach for the solution of Probability Density Evolution of Stochastic Systems S. Pourtakdoust Amir H. Khodabakhsh 36 12 0 05 Jul 2022
Approximating Discontinuous Nash Equilibrial Values of Two-Player General-Sum Differential Games Lei Zhang Mukesh Ghimire Wenlong Zhang Zhenni Xu Yi Ren 30 7 0 05 Jul 2022
TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing Z. Liu Xinling Yu Zheng-Wei Zhang PINN 16 7 0 04 Jul 2022
Memory Safe Computations with XLA Compiler A. Artemev Tilman Roeder Mark van der Wilk 29 8 0 28 Jun 2022
A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method Shahed Rezaei Ali Harandi Ahmad Moeineddin Bai-Xiang Xu Stefanie Reese 21 112 0 27 Jun 2022
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning Thomas O'Leary-Roseberry Peng Chen Umberto Villa Omar Ghattas AI4CE 32 39 0 21 Jun 2022
Fast Simulation of Particulate Suspensions Enabled by Graph Neural Network Zhan Ma Zisheng Ye Wenxiao Pan 34 14 0 17 Jun 2022
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks R. Ballester-Ripoll Manuele Leonelli 18 8 0 17 Jun 2022
Hybrid thermal modeling of additive manufacturing processes using physics-informed neural networks for temperature prediction and parameter identification Shuheng Liao Tianju Xue Jihoon Jeong Samantha Webster K. Ehmann Jian Cao AI4CE 32 46 0 15 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael E. Sander Pierre Ablin Gabriel Peyré 35 25 0 29 May 2022