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A Review of automatic differentiation and its efficient implementation

12 November 2018

Papers citing "A Review of automatic differentiation and its efficient implementation"

29 / 79 papers shown

Title
GPU-Accelerated Policy Optimization via Batch Automatic Differentiation of Gaussian Processes for Real-World Control Abdolreza Taheri Joni Pajarinen R. Ghabcheloo GP 54 3 0 28 Feb 2022
Adjoint-aided inference of Gaussian process driven differential equations Paterne Gahungu Christopher W. Lanyon Mauricio A. Alvarez Engineer Bainomugisha M. Smith Richard D. Wilkinson 57 5 0 09 Feb 2022
Efficient Automatic Differentiation of Implicit Functions C. Margossian M. Betancourt 58 2 0 28 Dec 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 120 93 0 10 Nov 2021
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu Lu Lu Xuhui Meng George Karniadakis PINN AI4CE 91 475 0 01 Nov 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 40 2 0 05 Oct 2021
Differentiable 3D CAD Programs for Bidirectional Editing Dan Cascaval Mira Shalah Phillip Quinn Rastislav Bodík Maneesh Agrawala Adriana Schulz 61 33 0 04 Oct 2021
Individual Survival Curves with Conditional Normalizing Flows Guillaume Ausset Tom Ciffreo François Portier Stéphan Clémenccon Timothée Papin 55 4 0 27 Jul 2021
A Wasserstein Minimax Framework for Mixed Linear Regression Theo Diamandis Yonina C. Eldar Alireza Fallah Farzan Farnia Asuman Ozdaglar 73 7 0 14 Jun 2021
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting Eric Heiden Miles Macklin Yashraj S. Narang Dieter Fox Animesh Garg Fabio Ramos 65 96 0 25 May 2021
gradSim: Differentiable simulation for system identification and visuomotor control Krishna Murthy Jatavallabhula Miles Macklin Florian Golemo Vikram S. Voleti Petrini ... Erleben Liam Paull Florian Shkurti Derek Nowrouzezahrai Sanja Fidler 54 104 0 06 Apr 2021
Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds Alexander Novikov M. Rakhuba Ivan Oseledets 39 8 0 27 Mar 2021
Differentiable Agent-Based Simulation for Gradient-Guided Simulation-Based Optimization Philipp Andelfinger 141 14 0 23 Mar 2021
Modeling Extremes with d-max-decreasing Neural Networks Ali Hasan Khalil Elkhalil Yuting Ng João M. Pereira Sina Farsiu Jose H. Blanchet Vahid Tarokh 64 6 0 17 Feb 2021
FastAD: Expression Template-Based C++ Library for Fast and Memory-Efficient Automatic Differentiation Jie Yang VLM 10 1 0 06 Feb 2021
Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley 41 1 0 13 Oct 2020
Second-order Neural Network Training Using Complex-step Directional Derivative Siyuan Shen Tianjia Shao Kun Zhou Chenfanfu Jiang Feng Luo Yin Yang ODL 27 2 0 15 Sep 2020
Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley ODL 81 17 0 11 Sep 2020
Differentiable model-based adaptive optics with transmitted and reflected light Ivan Vishniakou Johannes D. Seelig MedIm 23 3 0 27 Jul 2020
Model-based Clustering using Automatic Differentiation: Confronting Misspecification and High-Dimensional Data Siva Rajesh Kasa Vaibhav Rajan 41 0 0 08 Jul 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 76 22 0 26 Jun 2020
On Correctness of Automatic Differentiation for Non-Differentiable Functions Wonyeol Lee Hangyeol Yu Xavier Rival Hongseok Yang 86 41 0 12 Jun 2020
Cross-entropy-based importance sampling with failure-informed dimension reduction for rare event simulation Felipe Uribe I. Papaioannou Youssef M. Marzouk D. Štraub 53 40 0 09 Jun 2020
Bayesian workflow for disease transmission modeling in Stan Léo Grinsztajn Elizaveta Semenova C. Margossian J. Riou 59 62 0 23 May 2020
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond C. Margossian Aki Vehtari Daniel P. Simpson Raj Agrawal BDL 20 0 0 27 Apr 2020
The Discrete Adjoint Method: Efficient Derivatives for Functions of Discrete Sequences M. Betancourt C. Margossian Vianey Leos‐Barajas 23 11 0 02 Feb 2020
Automatic Differentiable Monte Carlo: Theory and Application Shi-Xin Zhang Z. Wan H. Yao 57 17 0 20 Nov 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 161 1,555 0 10 Jul 2019
A Geometric Theory of Higher-Order Automatic Differentiation M. Betancourt AI4CE 54 25 0 30 Dec 2018