Automatic differentiation in machine learning: a survey

Automatic differentiation in machine learning: a survey

20 February 2015

Barak A. Pearlmutter

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

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Title
GPdoemd: a Python package for design of experiments for model discrimination Simon Olofsson Lukas Hebing Sebastian Niedenführ M. Deisenroth Ruth Misener 19 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 13 158 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 D. Wood 26 31 0 20 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 89 4,929 0 19 Jun 2018
Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations M. Raissi 15 183 0 19 Apr 2018
Deep Generative Model for Joint Alignment and Word Representation Miguel Rios Wilker Aziz K. Simaán 33 4 0 16 Feb 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 12 744 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
Online Learning Rate Adaptation with Hypergradient Descent A. G. Baydin R. Cornish David Martínez-Rubio Mark W. Schmidt Frank D. Wood ODL 22 242 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 18 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 14 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 13 74 0 02 Aug 2016
Higher-Order Factorization Machines Mathieu Blondel Akinori Fujino N. Ueda Masakazu Ishihata 20 196 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 22 244 0 10 Mar 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 27 708 0 02 Mar 2016
Differentiation of the Cholesky decomposition Iain Murray 16 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