Automatic differentiation in machine learning: a survey

20 February 2015

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

50 / 341 papers shown

Title
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 77 0 20 Sep 2021
Variational Physics Informed Neural Networks: the role of quadratures and test functions S. Berrone C. Canuto Moreno Pintore 31 41 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 16 79 0 01 Sep 2021
Acceleration Method for Learning Fine-Layered Optical Neural Networks K. Aoyama H. Sawada 27 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 18 29 0 25 Aug 2021
m-RevNet: Deep Reversible Neural Networks with Momentum Duo Li Shangqi Gao 36 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
Functorial String Diagrams for Reverse-Mode Automatic Differentiation Mario Alvarez-Picallo D. Ghica David Sprunger Fabio Zanasi 18 16 0 28 Jul 2021
Physics-constrained Deep Learning for Robust Inverse ECG Modeling Jianxin Xie B. Yao 30 21 0 26 Jul 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 85 455 0 13 Jul 2021
Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential Equations Zhiming Zhang Yongming Liu 8 11 0 08 Jul 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 20 7 0 30 Jun 2021
AutoEKF: Scalable System Identification for COVID-19 Forecasting from Large-Scale GPS Data Francisco Barreras Mikhail Hayhoe Hamed Hassani V. Preciado 28 1 0 28 Jun 2021
Legendre Deep Neural Network (LDNN) and its application for approximation of nonlinear Volterra Fredholm Hammerstein integral equations Z. Hajimohammadi Kourosh Parand A. Ghodsi 33 4 0 27 Jun 2021
Transient Stability Analysis with Physics-Informed Neural Networks Jochen Stiasny Georgios S. Misyris Spyros Chatzivasileiadis PINN 26 13 0 25 Jun 2021
Polyconvex anisotropic hyperelasticity with neural networks Dominik K. Klein Mauricio Fernández Robert J. Martin P. Neff Oliver Weeger 41 151 0 20 Jun 2021
Differentiable Particle Filtering without Modifying the Forward Pass Adam Scibior Frank Wood 28 19 0 18 Jun 2021
Long-time integration of parametric evolution equations with physics-informed DeepONets Sizhuang He P. Perdikaris AI4CE 24 117 0 09 Jun 2021
Automatically Differentiable Random Coefficient Logistic Demand Estimation Andrew Chia 21 0 0 08 Jun 2021
Inverse design of two-dimensional materials with invertible neural networks Victor Fung Jiaxin Zhang Guoxiang Hu P. Ganesh B. Sumpter 28 41 0 06 Jun 2021
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting Stephan Thaler Julija Zavadlav 22 66 0 02 Jun 2021
Decomposing reverse-mode automatic differentiation Roy Frostig Matthew J. Johnson D. Maclaurin Adam Paszke Alexey Radul 14 8 0 20 May 2021
Deep learning in physics: a study of dielectric quasi-cubic particles in a uniform electric field Zhe Wang C. Guet 19 5 0 11 May 2021
Deep reinforcement learning-designed radiofrequency waveform in MRI Dongmyung Shin Younghoon Kim Chung‐Hyok Oh Hongjun An Juhyung Park Jiye G. Kim Jongho Lee 23 20 0 07 May 2021
Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 23 39 0 03 May 2021
A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media B. Yan D. Harp Bailian Chen R. Pawar AI4CE 15 72 0 30 Apr 2021
A Gradient-based Deep Neural Network Model for Simulating Multiphase Flow in Porous Media B. Yan D. Harp R. Pawar AI4CE 25 63 0 30 Apr 2021
Adversarial Multi-task Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Pongpisit Thanasutives M. Numao Ken-ichi Fukui AI4CE 30 24 0 29 Apr 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 71 223 0 26 Apr 2021
Inductive biases and Self Supervised Learning in modelling a physical heating system C. Vicas AI4CE 28 0 0 23 Apr 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 274 0 20 Apr 2021
Randomized Algorithms for Scientific Computing (RASC) A. Buluç T. Kolda Stefan M. Wild M. Anitescu Anthony Degennaro ... D. Vrabie B. Wohlberg Stephen J. Wright Chao Yang Peter Zwart AI4CE 43 10 0 19 Apr 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 27 74 0 15 Apr 2021
Fast Jacobian-Vector Product for Deep Networks Randall Balestriero Richard Baraniuk 31 4 0 01 Apr 2021
Learning to Solve the AC-OPF using Sensitivity-Informed Deep Neural Networks M. Singh V. Kekatos G. Giannakis 11 69 0 27 Mar 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets Sizhuang He Hanwen Wang P. Perdikaris AI4CE 40 667 0 19 Mar 2021
The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? Stefano Markidis PINN 39 182 0 12 Mar 2021
Implicit energy regularization of neural ordinary-differential-equation control Lucas Böttcher Nino Antulov-Fantulin Thomas Asikis 21 67 0 11 Mar 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 28 78 0 03 Mar 2021
Momentum Residual Neural Networks Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 27 57 0 15 Feb 2021
Fast and Memory Efficient Differentially Private-SGD via JL Projections Zhiqi Bu Sivakanth Gopi Janardhan Kulkarni Y. Lee J. Shen U. Tantipongpipat FedML 34 41 0 05 Feb 2021
Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic César Quilodrán-Casas Vinicius L. S. Silva Rossella Arcucci Claire E. Heaney Yike Guo Christopher C. Pain 42 40 0 03 Feb 2021
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond Risheng Liu Jiaxin Gao Jin Zhang Deyu Meng Zhouchen Lin AI4CE 59 223 0 27 Jan 2021
Data-driven peakon and periodic peakon travelling wave solutions of some nonlinear dispersive equations via deep learning Li Wang Zhenya Yan 81 47 0 12 Jan 2021
Can Transfer Neuroevolution Tractably Solve Your Differential Equations? Jian Cheng Wong Abhishek Gupta Yew-Soon Ong 28 21 0 06 Jan 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 131 439 0 18 Dec 2020