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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"

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Title
Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning Ananyae Kumar Bhartari Vinayak Vinayak Vivek B Shenoy AI4CE 216 0 0 16 May 2025
A Common Interface for Automatic Differentiation Guillaume Dalle Adrian Hill PINN VLM 142 1 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 92 0 0 05 May 2025
Coherence-based Approximate Derivatives via Web of Affine Spaces Optimization Daniel Rakita Chen Liang Qian Wang 64 0 0 26 Apr 2025
ad-trait: A Fast and Flexible Automatic Differentiation Library in Rust Chen Liang Qian Wang Andy Xu Daniel Rakita PINN 26 1 0 22 Apr 2025
Implicit Neural Differential Model for Spatiotemporal Dynamics Deepak Akhare P. Du Tengfei Luo Jian-Xun Wang PINN AI4CE 74 0 0 03 Apr 2025
Optimizing Automatic Differentiation with Deep Reinforcement Learning Jamie Lohoff Emre Neftci 205 2 0 28 Jan 2025
Poor Man's Training on MCUs: A Memory-Efficient Quantized Back-Propagation-Free Approach Yequan Zhao Hai Li Ian Young Zheng Zhang MQ 104 3 0 07 Nov 2024
Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs? Son Luu Zuheng Xu Nikola Surjanovic Miguel Biron-Lattes Trevor Campbell Alexandre Bouchard-Côté 60 0 0 04 Oct 2024
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 116 1 0 13 Sep 2024
Two-stage initial-value iterative physics-informed neural networks for simulating solitary waves of nonlinear wave equations Jin Song Ming Zhong George Karniadakis Zhenya Yan PINN 77 14 0 02 Sep 2024
Separable Operator Networks Xinling Yu S. Hooten Ziyue Liu Yequan Zhao M. Fiorentino T. Van Vaerenbergh Zheng Zhang 107 4 0 15 Jul 2024
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms Måns Magnusson Jakob Torgander Paul-Christian Bürkner Lu Zhang Bob Carpenter Aki Vehtari 119 6 0 06 Jul 2024
Extremization to Fine Tune Physics Informed Neural Networks for Solving Boundary Value Problems A. Thiruthummal Sergiy Shelyag Eun-Jin Kim 55 2 0 07 Jun 2024
Neural force functional for non-equilibrium many-body colloidal systems Toni Zimmerman Florian Sammüller Sophie Hermann Matthias Schmidt D. de las Heras 22 7 0 05 Jun 2024
Elastic Locomotion with Mixed Second-order Differentiation Siyuan Shen Tianjia Shao Kun Zhou Chenfanfu Jiang Sheldon Andrews Victor Zordan Yin Yang 58 1 0 23 May 2024
A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms Hao Wang Angel E. Rodriguez-Fernandez L. Uribe A. Deutz Oziel Cortés-Pina Oliver Schütze 27 1 0 09 May 2024
The Inefficiency of Genetic Programming for Symbolic Regression -- Extended Version G. Kronberger Fabrício Olivetti de França Harry Desmond Deaglan J. Bartlett Lukas Kammerer 78 5 0 26 Apr 2024
Towards Learning Stochastic Population Models by Gradient Descent J. N. Kreikemeyer Philipp Andelfinger A. Uhrmacher 68 1 0 10 Apr 2024
Automatic Gradient Estimation for Calibrating Crowd Models with Discrete Decision Making Philipp Andelfinger J. N. Kreikemeyer 71 1 0 06 Apr 2024
Proof-of-concept: Using ChatGPT to Translate and Modernize an Earth System Model from Fortran to Python/JAX Anthony Zhou Linnia Hawkins Pierre Gentine 48 2 0 13 Feb 2024
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems Dan MacKinlay Russell Tsuchida Dan Pagendam Petra M. Kuhnert 70 2 0 13 Feb 2024
JAX-Fluids 2.0: Towards HPC for Differentiable CFD of Compressible Two-phase Flows Deniz A. Bezgin Aaron B. Buhendwa Nikolaus A. Adams 51 11 0 07 Feb 2024
The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations Matthias Lehmann 79 0 0 24 Jan 2024
A conservative hybrid physics-informed neural network method for Maxwell-Ampère-Nernst-Planck equations Cheng Chang Zhouping Xin Tieyong Zeng 61 0 0 10 Dec 2023
Operator Learning for Continuous Spatial-Temporal Model with Gradient-Based and Derivative-Free Optimization Methods Chuanqi Chen Jin-Long Wu AI4CE 68 0 0 20 Nov 2023
Smoothing Methods for Automatic Differentiation Across Conditional Branches J. N. Kreikemeyer Philipp Andelfinger 77 7 0 05 Oct 2023
Deep learning soliton dynamics and complex potentials recognition for 1D and 2D PT-symmetric saturable nonlinear Schrödinger equations Jin Song Ilya Shenbin 133 27 0 29 Sep 2023
csSampling: An R Package for Bayesian Models for Complex Survey Data Ryan Hornby Matthew R. Williams T. Savitsky Mahmoud Elkasabi 26 1 0 13 Aug 2023
Variational Inference with Gaussian Score Matching Chirag Modi C. Margossian Yuling Yao Robert Mansel Gower David M. Blei Lawrence K. Saul 83 13 0 15 Jul 2023
General adjoint-differentiated Laplace approximation C. Margossian 33 0 0 26 Jun 2023
Understanding Automatic Differentiation Pitfalls Jan Huckelheim Harshitha Menon William S. Moses Bruce Christianson P. Hovland Laurent Hascoet PINN 70 4 0 12 May 2023
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 102 5 0 26 Apr 2023
DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets Isabella Huang Yashraj S. Narang R. Bajcsy Fabio Ramos Tucker Hermans Dieter Fox 54 11 0 28 Mar 2023
An Analysis of Physics-Informed Neural Networks E. Small PINN 43 1 0 06 Mar 2023
Physics informed WNO N. N. Tapas Tripura S. Chakraborty 75 33 0 12 Feb 2023
A Fully First-Order Method for Stochastic Bilevel Optimization Jeongyeol Kwon Dohyun Kwon S. Wright Robert D. Nowak 103 78 0 26 Jan 2023
Inference in Marginal Structural Models by Automatic Targeted Bayesian and Minimum Loss-Based Estimation Herbert Susmann Antoine Chambaz CML 28 1 0 25 Jan 2023
Low-Variance Forward Gradients using Direct Feedback Alignment and Momentum Florian Bacho Dominique F. Chu 61 8 0 14 Dec 2022
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 103 18 0 07 Nov 2022
Probabilistic partition of unity networks for high-dimensional regression problems Tiffany Fan N. Trask M. DÉlia Eric F. Darve 63 1 0 06 Oct 2022
Optimization without Backpropagation Gabriel Belouze 106 7 0 13 Sep 2022
Learning Sparsity-Promoting Regularizers using Bilevel Optimization Avrajit Ghosh Michael T. McCann Madeline Mitchell S. Ravishankar 71 5 0 18 Jul 2022
Automatic differentiation and the optimization of differential equation models in biology S. Frank 53 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 76 20 0 26 May 2022
An importance sampling approach for reliable and efficient inference in Bayesian ordinary differential equation models Juho Timonen Nikolas Siccha Benjamin B. Bales Harri Lähdesmäki Aki Vehtari 61 4 0 18 May 2022
Visual Analysis of Multiple Dynamic Sensitivities along Ascending Trajectories in the Atmosphere Christoph Neuhauser M. Hieronymus M. Kern M. Rautenhaus A. Oertel Rüdiger Westermann 15 0 0 02 May 2022
SymForce: Symbolic Computation and Code Generation for Robotics Hayk Martiros Aaron Miller Nathan Bucki Bradley Solliday Ryan Kennedy ... Gareth Cross Josiah T. Vandermey A. Sun Samuel Wang Kristen Holtz 48 14 0 17 Apr 2022
Optimizing differential equations to fit data and predict outcomes S. Frank 42 4 0 16 Apr 2022
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting Eric Heiden Miles Macklin Yashraj S. Narang Dieter Fox Animesh Garg Fabio Ramos 109 11 0 19 Mar 2022