Automatic differentiation in machine learning: a survey

20 February 2015

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

50 / 319 papers shown

Title
Unnormalized Variational Bayes Saeed Saremi BDL 81 1 0 29 Jul 2020
Incremental Without Replacement Sampling in Nonconvex Optimization Edouard Pauwels 38 5 0 15 Jul 2020
On the Iteration Complexity of Hypergradient Computation Riccardo Grazzi Luca Franceschi Massimiliano Pontil Saverio Salzo 48 192 0 29 Jun 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 19 22 0 26 Jun 2020
Approximate Cross-Validation for Structured Models S. Ghosh William T. Stephenson Tin D. Nguyen Sameer K. Deshpande Tamara Broderick 8 15 0 23 Jun 2020
Neural Ordinary Differential Equation Control of Dynamics on Graphs Thomas Asikis Lucas Böttcher Nino Antulov-Fantulin 33 43 0 17 Jun 2020
Dynamic Tensor Rematerialization Marisa Kirisame Steven Lyubomirsky Altan Haan Jennifer Brennan Mike He Jared Roesch Tianqi Chen Zachary Tatlock 18 93 0 17 Jun 2020
On Correctness of Automatic Differentiation for Non-Differentiable Functions Wonyeol Lee Hangyeol Yu Xavier Rival Hongseok Yang 17 40 0 12 Jun 2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning Sijia Liu Pin-Yu Chen B. Kailkhura Gaoyuan Zhang A. Hero III P. Varshney 21 224 0 11 Jun 2020
Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao Hao Sun Yang Liu PINN AI4CE 17 222 0 10 Jun 2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs Beren Millidge Alexander Tschantz Christopher L. Buckley 30 118 0 07 Jun 2020
Deep learning of free boundary and Stefan problems Sizhuang He P. Perdikaris 24 80 0 04 Jun 2020
Transfer learning based multi-fidelity physics informed deep neural network S. Chakraborty PINN OOD AI4CE 12 163 0 19 May 2020
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization Rishikesh Ranade C. Hill Jay Pathak AI4CE 54 123 0 17 May 2020
SciANN: A Keras/Tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks E. Haghighat R. Juanes AI4CE PINN 12 21 0 11 May 2020
Automatic Differentiation in ROOT V. Vassilev A. Efremov O. Shadura PINN 9 5 0 09 Apr 2020
A deep learning framework for solution and discovery in solid mechanics E. Haghighat M. Raissi A. Moure H. Gómez R. Juanes AI4CE PINN 8 56 0 14 Feb 2020
Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications Yun Yuan X. Yang Zhao Zhang Shandian Zhe AI4CE 34 95 0 06 Feb 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 23 291 0 13 Jan 2020
Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach H. Hwang Jin Woo Jang Hyeontae Jo Jae Yong Lee 149 36 0 22 Nov 2019
A Simple Differentiable Programming Language M. Abadi G. Plotkin 14 65 0 11 Nov 2019
Physics-Informed Neural Networks for Power Systems George S. Misyris Andreas Venzke Spyros Chatzivasileiadis PINN AI4CE 14 212 0 09 Nov 2019
Deep Learning of Subsurface Flow via Theory-guided Neural Network Nanzhe Wang Dongxiao Zhang Haibin Chang Heng Li AI4CE 25 226 0 24 Oct 2019
Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe H. Qin 29 30 0 22 Oct 2019
Uncertainty-aware Sensitivity Analysis Using Rényi Divergences Topi Paananen Michael Riis Andersen Aki Vehtari 14 3 0 17 Oct 2019
Backpropagation in the Simply Typed Lambda-calculus with Linear Negation Aloïs Brunel Damiano Mazza Michele Pagani 14 46 0 27 Sep 2019
Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks Ameya Dilip Jagtap Kenji Kawaguchi George Karniadakis ODL 13 85 0 25 Sep 2019
Machine Discovery of Partial Differential Equations from Spatiotemporal Data Ye Yuan Junlin Li Liang Li Frank Jiang Xiuchuan Tang ... J. Gonçalves H. Voss Xiuting Li J. Kurths Han Ding AI4CE 9 9 0 15 Sep 2019
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations Jan Stühmer Richard Turner Sebastian Nowozin DRL BDL CoGe 114 25 0 05 Sep 2019
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data Hao Xu Haibin Chang Dongxiao Zhang AI4CE 12 69 0 13 Aug 2019
Distributed physics informed neural network for data-efficient solution to partial differential equations Vikas Dwivedi N. Parashar Balaji Srinivasan PINN 8 81 0 21 Jul 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 22 1,485 0 10 Jul 2019
Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations Vikas Dwivedi Balaji Srinivasan PINN 11 190 0 08 Jul 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 43 397 0 25 Jun 2019
Declarative Learning-Based Programming as an Interface to AI Systems Parisa Kordjamshidi Dan Roth Kristian Kersting 17 4 0 18 Jun 2019
Parameterized quantum circuits as machine learning models Marcello Benedetti Erika Lloyd Stefan H. Sack Mattia Fiorentini 27 869 0 18 Jun 2019
A general method for regularizing tensor decomposition methods via pseudo-data Omer Gottesman Weiwei Pan Finale Doshi-Velez 11 0 0 24 May 2019
Deep Neural Networks for Marine Debris Detection in Sonar Images Matias Valdenegro-Toro 27 25 0 13 May 2019
Effective Estimation of Deep Generative Language Models Tom Pelsmaeker Wilker Aziz BDL 22 27 0 17 Apr 2019
Least Squares Auto-Tuning Shane T. Barratt Stephen P. Boyd MoMe 19 23 0 10 Apr 2019
Feature Engineering for Mid-Price Prediction with Deep Learning Adamantios Ntakaris G. Mirone Juho Kanniainen Moncef Gabbouj Alexandros Iosifidis OOD 25 44 0 10 Apr 2019
On the Equivalence of Automatic and Symbolic Differentiation Soeren Laue 12 4 0 05 Apr 2019
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Yuanshuo Zhou Bradley Gram-Hansen Tobias Kohn Tom Rainforth Hongseok Yang Frank D. Wood 31 24 0 06 Mar 2019
Neural Empirical Bayes Saeed Saremi Aapo Hyvarinen 12 65 0 06 Mar 2019
Action Robust Reinforcement Learning and Applications in Continuous Control Chen Tessler Yonathan Efroni Shie Mannor 30 230 0 26 Jan 2019
Autoencoder Based Residual Deep Networks for Robust Regression Prediction and Spatiotemporal Estimation Lianfa Li Ying Fang Jun Wu Jinfeng Wang 22 13 0 29 Dec 2018
Physics-informed deep generative models Yibo Yang P. Perdikaris AI4CE PINN 19 57 0 09 Dec 2018
A Spectral Regularizer for Unsupervised Disentanglement Aditya A. Ramesh Youngduck Choi Yann LeCun DRL 19 42 0 04 Dec 2018
Truncated Back-propagation for Bilevel Optimization Amirreza Shaban Ching-An Cheng Nathan Hatch Byron Boots 24 261 0 25 Oct 2018
Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis M. A. Nabian Hadi Meidani PINN AI4CE 21 57 0 11 Oct 2018