Automatic differentiation in machine learning: a survey

20 February 2015

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

50 / 319 papers shown

Title
QuadraLib: A Performant Quadratic Neural Network Library for Architecture Optimization and Design Exploration Zirui Xu Fuxun Yu Jinjun Xiong Xiang Chen 33 23 0 01 Apr 2022
Certified machine learning: A posteriori error estimation for physics-informed neural networks Birgit Hillebrecht B. Unger PINN 19 15 0 31 Mar 2022
Differentiable, learnable, regionalized process-based models with physical outputs can approach state-of-the-art hydrologic prediction accuracy D. Feng Jiangtao Liu K. Lawson Chaopeng Shen BDL AI4CE 12 117 0 28 Mar 2022
JAX-FLUIDS: A fully-differentiable high-order computational fluid dynamics solver for compressible two-phase flows Deniz A. Bezgin Aaron B. Buhendwa Nikolaus A. Adams AI4CE 13 67 0 25 Mar 2022
On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 36 17 0 25 Mar 2022
Constrained Parameter Inference as a Principle for Learning Nasir Ahmad Ellen Schrader Marcel van Gerven 13 10 0 22 Mar 2022
Investigation of Physics-Informed Deep Learning for the Prediction of Parametric, Three-Dimensional Flow Based on Boundary Data Philipp Heger Markus Full Daniel Hilger N. Hosters AI4CE 27 9 0 17 Mar 2022
Bayesian inference via sparse Hamiltonian flows Na Chen Zuheng Xu Trevor Campbell 35 14 0 11 Mar 2022
Bathymetry Inversion using a Deep-Learning-Based Surrogate for Shallow Water Equations Solvers Xiaofeng Liu Yalan Song Chaopeng Shen AI4CE 25 9 0 05 Mar 2022
Physics-informed neural network solution of thermo-hydro-mechanical (THM) processes in porous media Daniel Amini E. Haghighat R. Juanes PINN AI4CE 24 23 0 03 Mar 2022
Extension of Dynamic Mode Decomposition for dynamic systems with incomplete information based on t-model of optimal prediction Aleksandr Katrutsa S. Utyuzhnikov Ivan V. Oseledets 25 4 0 23 Feb 2022
Gradients without Backpropagation A. G. Baydin Barak A. Pearlmutter Don Syme Frank D. Wood Philip H. S. Torr 32 66 0 17 Feb 2022
Physics-informed neural networks for solving parametric magnetostatic problems Andrés Beltrán-Pulido Ilias Bilionis D. Aliprantis 24 34 0 08 Feb 2022
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process Thi Nguyen Khoa Nguyen T. Dairay Raphael Meunier Mathilde Mougeot PINN AI4CE 81 29 0 31 Jan 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao Sun AI4CE 43 27 0 28 Jan 2022
Meta-learning Spiking Neural Networks with Surrogate Gradient Descent Kenneth Stewart Emre Neftci 27 25 0 26 Jan 2022
Efficient Automatic Differentiation of Implicit Functions C. Margossian M. Betancourt 24 2 0 28 Dec 2021
Supervised learning of analysis-sparsity priors with automatic differentiation Hashem Ghanem Joseph Salmon Nicolas Keriven Samuel Vaiter 35 2 0 15 Dec 2021
A Sparse Expansion For Deep Gaussian Processes Liang Ding Rui Tuo Shahin Shahrampour 13 6 0 11 Dec 2021
Surrogate-data-enriched Physics-Aware Neural Networks Raphael Leiteritz Patrick Buchfink B. Haasdonk Dirk Pflüger PINN AI4CE 17 3 0 10 Dec 2021
Scaling Up Influence Functions Andrea Schioppa Polina Zablotskaia David Vilar Artem Sokolov TDI 30 90 0 06 Dec 2021
Hierarchical Learning to Solve Partial Differential Equations Using Physics-Informed Neural Networks Jihun Han Yoonsang Lee AI4CE 24 10 0 02 Dec 2021
CIRCLE: Convolutional Implicit Reconstruction and Completion for Large-scale Indoor Scene Haoxiang Chen Jiahui Huang Tai-Jiang Mu Shimin Hu 3DPC 16 7 0 25 Nov 2021
Neural Fields in Visual Computing and Beyond Yiheng Xie Towaki Takikawa Shunsuke Saito Or Litany Shiqin Yan Numair Khan Federico Tombari James Tompkin Vincent Sitzmann Srinath Sridhar 3DH 49 615 0 22 Nov 2021
Efficient Neural Network Training via Forward and Backward Propagation Sparsification Xiao Zhou Weizhong Zhang Zonghao Chen Shizhe Diao Tong Zhang 32 46 0 10 Nov 2021
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series Daniel Kramer P. Bommer Carlo Tombolini G. Koppe Daniel Durstewitz BDL AI4TS AI4CE 22 18 0 04 Nov 2021
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods Desi R. Ivanova Adam Foster Steven Kleinegesse Michael U. Gutmann Tom Rainforth OffRL 13 46 0 03 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 33 93 0 02 Nov 2021
Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks Xiang Huang Hongsheng Liu Beiji Shi Zidong Wang Kan Yang ... Jing Zhou Fan Yu Bei Hua Lei Chen Bin Dong 11 20 0 02 Nov 2021
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu Lu Lu Xuhui Meng George Karniadakis PINN AI4CE 26 451 0 01 Nov 2021
An extended physics informed neural network for preliminary analysis of parametric optimal control problems N. Demo M. Strazzullo G. Rozza PINN 31 33 0 26 Oct 2021
Fast PDE-constrained optimization via self-supervised operator learning Sizhuang He Mohamed Aziz Bhouri P. Perdikaris 47 28 0 25 Oct 2021
Data-driven approaches for predicting spread of infectious diseases through DINNs: Disease Informed Neural Networks Sagi Shaier M. Raissi P. Seshaiyer PINN AI4CE 11 25 0 11 Oct 2021
A composable autoencoder-based iterative algorithm for accelerating numerical simulations Rishikesh Ranade C. Hill Haiyang He Amir Maleki Norman Chang Jay Pathak AI4CE 41 6 0 07 Oct 2021
Optical secret sharing with cascaded metasurface holography P. Georgi Qunshuo Wei B. Sain C. Schlickriede Yongtian Wang Lingling Huang T. Zentgraf 13 188 0 07 Oct 2021
Coarsening Optimization for Differentiable Programming Xipeng Shen Guoqiang Zhang Irene Dea S. Andow Emilio Arroyo-Fang ... E. Meijer Steffi Stumpos Alanna Tempest Christy Warden Shannon Yang 26 2 0 05 Oct 2021
Improved architectures and training algorithms for deep operator networks Sizhuang He Hanwen Wang P. Perdikaris AI4CE 49 105 0 04 Oct 2021
Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations Li Cheng Ekhi Ajuria Illarramendi Guillaume Bogopolsky M. Bauerheim B. Cuenot 45 19 0 27 Sep 2021
Revisit Geophysical Imaging in A New View of Physics-informed Generative Adversarial Learning Fangshu Yang Jianwei Ma 20 8 0 23 Sep 2021
Dynamic Mixture of Experts Models for Online Prediction Parfait Munezero M. Villani Robert Kohn 21 1 0 23 Sep 2021
Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators Jonas Nicodemus Jonas Kneifl Jörg Fehr B. Unger PINN AI4CE 29 52 0 22 Sep 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 18 76 0 20 Sep 2021
Variational Physics Informed Neural Networks: the role of quadratures and test functions S. Berrone C. Canuto Moreno Pintore 23 40 0 05 Sep 2021
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization Yao Shu Shaofeng Cai Zhongxiang Dai Beng Chin Ooi K. H. Low 22 43 0 02 Sep 2021
Physics-informed Neural Network for Nonlinear Dynamics in Fiber Optics Xiaotian Jiang Danshi Wang Qirui Fan Min Zhang Chao Lu A. Lau AI4CE PINN 11 79 0 01 Sep 2021
Acceleration Method for Learning Fine-Layered Optical Neural Networks K. Aoyama H. Sawada 21 1 0 01 Sep 2021
Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yihang Gao Michael K. Ng 38 28 0 30 Aug 2021
Auxiliary Task Update Decomposition: The Good, The Bad and The Neutral Lucio Dery Yann N. Dauphin David Grangier MoMe 13 29 0 25 Aug 2021
m-RevNet: Deep Reversible Neural Networks with Momentum Duo Li Shangqi Gao 16 5 0 12 Aug 2021
Data-Driven Constitutive Relation Reveals Scaling Law for Hydrodynamic Transport Coefficients Candi Zheng Yang Wang Shiying Chen 25 4 0 01 Aug 2021