Automatic differentiation in machine learning: a survey

20 February 2015

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

50 / 277 papers shown

Title
A Common Interface for Automatic Differentiation Guillaume Dalle Adrian Hill PINN VLM 47 0 0 08 May 2025
Learning and Transferring Physical Models through Derivatives Alessandro Trenta Andrea Cossu Davide Bacciu AI4CE 34 0 0 02 May 2025
Smooth Integer Encoding via Integral Balance Stanislav Semenov 105 1 0 28 Apr 2025
Coherence-based Approximate Derivatives via Web of Affine Spaces Optimization Daniel Rakita Chen Liang Qian Wang 24 0 0 26 Apr 2025
Data Cleansing for GANs Naoyuki Terashita Hiroki Ohashi Satoshi Hara AAML 56 0 0 01 Apr 2025
Solving 2-D Helmholtz equation in the rectangular, circular, and elliptical domains using neural networks D. Veerababu Prasanta K. Ghosh 68 0 0 26 Mar 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
Unraveling particle dark matter with Physics-Informed Neural Networks M.P. Bento H.B. Câmara J.F. Seabra 55 0 0 24 Feb 2025
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness Emanuele Ballarin A. Ansuini Luca Bortolussi AAML 62 0 0 20 Feb 2025
Kolmogorov-Arnold Fourier Networks Jusheng Zhang Yijia Fan Kaitong Cai Keze Wang 63 0 0 09 Feb 2025
Physics-Grounded Differentiable Simulation for Soft Growing Robots Lucas Chen Yitian Gao Sicheng Wang Francesco Fuentes Laura H. Blumenschein Zachary Kingston 38 0 0 29 Jan 2025
Optimizing Automatic Differentiation with Deep Reinforcement Learning Jamie Lohoff Emre Neftci 53 1 0 28 Jan 2025
The Finite Element Neural Network Method: One Dimensional Study Mohammed Abda Elsa Piollet Christopher Blake Frédérick P. Gosselin 61 0 0 21 Jan 2025
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning Nilo Schwencke Cyril Furtlehner 64 1 0 14 Dec 2024
Influence functions and regularity tangents for efficient active learning Frederik Eaton TDI 89 0 0 22 Nov 2024
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 32 4 0 15 Oct 2024
Scientific Machine Learning Seismology Tomohisa Okazaki PINN AI4CE 46 0 0 27 Sep 2024
Cartan moving frames and the data manifolds Eliot Tron Rita Fioresi Nicolas Couellan Stéphane Puechmorel 51 1 0 18 Sep 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 49 1 0 13 Sep 2024
Practical Aspects on Solving Differential Equations Using Deep Learning: A Primer Georgios Is. Detorakis 23 0 0 21 Aug 2024
The Energy Cost of Artificial Intelligence Lifecycle in Communication Networks Shih-Kai Chou Jernej Hribar William Alberto Cruz Castañeda M. Mohorčič Carolina Fortuna 48 1 0 01 Aug 2024
Trade-off between Gradient Measurement Efficiency and Expressivity in Deep Quantum Neural Networks Koki Chinzei Shinichiro Yamano Quoc-Hoan Tran Yasuhiro Endo H. Oshima 50 1 0 26 Jun 2024
BrowNNe: Brownian Nonlocal Neurons & Activation Functions Sriram Nagaraj Truman Hickok 21 0 0 21 Jun 2024
Physics-informed neural networks for parameter learning of wildfire spreading K. Vogiatzoglou C. Papadimitriou V. Bontozoglou Konstantinos Ampountolas 21 1 0 20 Jun 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 31 3 0 29 May 2024
Deterministic and statistical calibration of constitutive models from full-field data with parametric physics-informed neural networks D. Anton Jendrik-Alexander Tröger Henning Wessels Ulrich Römer Alexander Henkes Stefan Hartmann AI4CE 31 4 0 28 May 2024
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations Chuqi Chen Yahong Yang Yang Xiang Wenrui Hao 26 2 0 23 May 2024
Reducing Spatial Discretization Error on Coarse CFD Simulations Using an OpenFOAM-Embedded Deep Learning Framework Jesus Gonzalez-Sieiro David Pardo Vincenzo Nava V. M. Calo Markus Towara AI4CE 32 1 0 13 May 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks R. Mattey Susanta Ghosh AI4CE 38 1 0 09 May 2024
Deep generative modelling of canonical ensemble with differentiable thermal properties Shuo-Hui Li Yao-Wen Zhang Ding Pan DRL SyDa 31 1 0 29 Apr 2024
Backpropagation through space, time, and the brain B. Ellenberger Paul Haider Jakob Jordan Kevin Max Ismael Jaras Laura Kriener Federico Benitez Mihai A. Petrovici 123 8 0 25 Mar 2024
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems Biao Yuan Ana Heitor He Wang Xiaohui Chen AI4CE PINN 29 1 0 08 Jan 2024
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective Sunwoong Yang Hojin Kim Y. Hong K. Yee R. Maulik Namwoo Kang PINN AI4CE 18 17 0 05 Jan 2024
Physics-Informed Multi-Agent Reinforcement Learning for Distributed Multi-Robot Problems Eduardo Sebastián T. Duong Nikolay A. Atanasov Eduardo Montijano C. Sagüés 23 2 0 30 Dec 2023
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model M. Hassanaly Peter J. Weddle Ryan N. King Subhayan De Alireza Doostan Corey R. Randall Eric J. Dufek Andrew M. Colclasure Kandler Smith 25 6 0 28 Dec 2023
Machine learning and domain decomposition methods -- a survey A. Klawonn M. Lanser J. Weber AI4CE 16 7 0 21 Dec 2023
What Can AutoML Do For Continual Learning? Mert Kilickaya Joaquin Vanschoren 28 1 0 20 Nov 2023
Solution of FPK Equation for Stochastic Dynamics Subjected to Additive Gaussian Noise via Deep Learning Approach Amir H. Khodabakhsh S. Pourtakdoust 11 6 0 08 Nov 2023
Density Matrix Emulation of Quantum Recurrent Neural Networks for Multivariate Time Series Prediction José Daniel Viqueira Daniel Faílde M. M. Juane Andrés Gómez David Mera 26 5 0 31 Oct 2023
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation Dzung Pham Shreyas Kulkarni Amir Houmansadr 25 0 0 29 Oct 2023
Randomized Forward Mode of Automatic Differentiation For Optimization Algorithms Khemraj Shukla Yeonjong Shin ODL 18 4 0 22 Oct 2023
A Mass-Conserving-Perceptron for Machine Learning-Based Modeling of Geoscientific Systems Yuan-Heng Wang Hoshin V. Gupta AI4CE 30 6 0 12 Oct 2023
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
Learning How to Propagate Messages in Graph Neural Networks Teng Xiao Zhengyu Chen Donglin Wang Suhang Wang GNN 26 76 0 01 Oct 2023
Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics Michael Kagan Lukas Heinrich 24 9 0 31 Aug 2023
Massively Parallel Continuous Local Search for Hybrid SAT Solving on GPUs Yunuo Cen Zhiwei Zhang Xuanyao Fong 14 1 0 29 Aug 2023
Warped geometric information on the optimisation of Euclidean functions M. Hartmann Bernardo Williams Hanlin Yu Mark Girolami Alessandro Barp Arto Klami 24 2 0 16 Aug 2023
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 11 0 08 Aug 2023
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities Jayanta Mandi James Kotary Senne Berden Maxime Mulamba Víctor Bucarey Tias Guns Ferdinando Fioretto AI4CE 24 54 0 25 Jul 2023
PI-VEGAN: Physics Informed Variational Embedding Generative Adversarial Networks for Stochastic Differential Equations R. Gao Yufeng Wang Min Yang Chuanjun Chen GAN 26 2 0 21 Jul 2023