A Review of automatic differentiation and its efficient implementation

12 November 2018

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

19 / 19 papers shown

Title
A Common Interface for Automatic Differentiation Guillaume Dalle Adrian Hill PINN VLM 47 0 0 08 May 2025
A Real-Time Control Barrier Function-Based Safety Filter for Motion Planning with Arbitrary Road Boundary Constraints Jianye Xu Chang Che Bassam Alrifaee 24 0 0 05 May 2025
Coherence-based Approximate Derivatives via Web of Affine Spaces Optimization Daniel Rakita Chen Liang Qian Wang 24 0 0 26 Apr 2025
Optimizing Automatic Differentiation with Deep Reinforcement Learning Jamie Lohoff Emre Neftci 55 1 0 28 Jan 2025
Shadow Program Inversion with Differentiable Planning: A Framework for Unified Robot Program Parameter and Trajectory Optimization Benjamin Alt Claudius Kienle Darko Katic Rainer Jäkel Michael Beetz 49 1 0 13 Sep 2024
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms Måns Magnusson Jakob Torgander Paul-Christian Burkner Lu Zhang Bob Carpenter Aki Vehtari 42 6 0 06 Jul 2024
A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks Hyeonjung Jung Jung Jayant Gupta B. Jayaprakash Matthew J. Eagon Harish Selvam Carl Molnar W. Northrop Shashi Shekhar AI4CE 35 5 0 26 Apr 2023
A Fully First-Order Method for Stochastic Bilevel Optimization Jeongyeol Kwon Dohyun Kwon S. Wright Robert D. Nowak 27 67 0 26 Jan 2023
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 29 17 0 07 Nov 2022
Automatic differentiation and the optimization of differential equation models in biology S. Frank 14 6 0 10 Jul 2022
Differentiable solver for time-dependent deformation problems with contact Zizhou Huang Davi C. Tozoni Arvi Gjoka Z. Ferguson T. Schneider Daniele Panozzo Denis Zorin AI4CE 21 18 0 26 May 2022
Optimizing differential equations to fit data and predict outcomes S. Frank 22 4 0 16 Apr 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 16 5 0 09 Feb 2022
Efficient Automatic Differentiation of Implicit Functions C. Margossian M. Betancourt 17 2 0 28 Dec 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 28 92 0 10 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 15 2 0 05 Oct 2021
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 8 22 0 26 Jun 2020
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 20 1,483 0 10 Jul 2019
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,262 0 09 Jun 2012