Automatic differentiation in machine learning: a survey

20 February 2015

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

43 / 343 papers shown

Title
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 52 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 19 190 0 08 Jul 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 45 397 0 25 Jun 2019
Declarative Learning-Based Programming as an Interface to AI Systems Parisa Kordjamshidi Dan Roth Kristian Kersting 22 4 0 18 Jun 2019
Parameterized quantum circuits as machine learning models Marcello Benedetti Erika Lloyd Stefan H. Sack Mattia Fiorentini 27 870 0 18 Jun 2019
A general method for regularizing tensor decomposition methods via pseudo-data Omer Gottesman Weiwei Pan Finale Doshi-Velez 16 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 24 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 28 44 0 10 Apr 2019
On the Equivalence of Automatic and Symbolic Differentiation Soeren Laue 17 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 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 30 13 0 29 Dec 2018
Physics-informed deep generative models Yibo Yang P. Perdikaris AI4CE PINN 21 58 0 09 Dec 2018
A Spectral Regularizer for Unsupervised Disentanglement Aditya A. Ramesh Youngduck Choi Yann LeCun DRL 29 42 0 04 Dec 2018
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yibo Yang P. Perdikaris AI4CE PINN 15 355 0 09 Nov 2018
Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations Siyu Dai Shawn Schaffert Andreas G. Hofmann 12 355 0 05 Nov 2018
Truncated Back-propagation for Bilevel Optimization Amirreza Shaban Ching-An Cheng Nathan Hatch Byron Boots 36 262 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
GPdoemd: a Python package for design of experiments for model discrimination Simon Olofsson Lukas Hebing Sebastian Niedenführ M. Deisenroth Ruth Misener 27 18 0 05 Oct 2018
Stochastic Variational Optimization Thomas Bird Julius Kunze David Barber DRL 12 14 0 13 Sep 2018
Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data M. Raissi A. Yazdani George Karniadakis AI4CE PINN 19 158 0 13 Aug 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A. G. Baydin Lukas Heinrich W. Bhimji Lei Shao Saeid Naderiparizi ... Philip Torr Victor W. Lee P. Prabhat Kyle Cranmer Frank Wood 26 31 0 20 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 101 4,940 0 19 Jun 2018
Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations M. Raissi 20 183 0 19 Apr 2018
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks Qianxiao Li Shuji Hao 19 75 0 04 Mar 2018
Deep Generative Model for Joint Alignment and Word Representation Miguel Rios Wilker Aziz K. Simaán 36 4 0 16 Feb 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 26 745 0 20 Jan 2018
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 24 607 0 28 Nov 2017
Owl: A General-Purpose Numerical Library in OCaml Liang Wang 21 22 0 30 Jul 2017
A Discrete Bouncy Particle Sampler Chris Sherlock Alexandre Hoang Thiery 27 22 0 17 Jul 2017
Online Learning Rate Adaptation with Hypergradient Descent A. G. Baydin R. Cornish David Martínez-Rubio Mark W. Schmidt Frank Wood ODL 30 242 0 14 Mar 2017
Getting Started with Neural Models for Semantic Matching in Web Search Kezban Dilek Onal I. S. Altingövde Pinar Senkul Maarten de Rijke VLM 3DV 31 9 0 08 Nov 2016
AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models K. Krauth Edwin V. Bonilla Kurt Cutajar Maurizio Filippone GP BDL 16 54 0 18 Oct 2016
RETURNN: The RWTH Extensible Training framework for Universal Recurrent Neural Networks P. Doetsch Albert Zeyer P. Voigtlaender Ilya Kulikov Ralf Schluter Hermann Ney 20 74 0 02 Aug 2016
Higher-Order Factorization Machines Mathieu Blondel Akinori Fujino N. Ueda Masakazu Ishihata 28 198 0 25 Jul 2016
Asymptotically exact inference in differentiable generative models Matthew M. Graham Amos J. Storkey BDL 21 33 0 25 May 2016
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation James Townsend Niklas Koep S. Weichwald 30 244 0 10 Mar 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 38 709 0 02 Mar 2016
Differentiation of the Cholesky decomposition Iain Murray 21 36 0 24 Feb 2016
A Primer on Neural Network Models for Natural Language Processing Yoav Goldberg AI4CE 50 1,128 0 02 Oct 2015