Who Cited It

Automatic differentiation in machine learning: a survey

2017 · Maynooth University ePrints and eTheses Archive (Maynooth University) · 2,094 citations · 0 from inside this corpus

Atılım Güneş Baydin, Barak A. Pearlmutter, Alexey Radul, Jeffrey Mark Siskind

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Automatic differentiation in machine learning: a survey (2017)Automatic differentiation in …[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics… (2015)[No title in the source recor…Learning representations by back-propagating errors (1986)Learning representations by b…Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…Auto-Encoding Variational Bayes (2013)Auto-Encoding Variational Bay…Neural Machine Translation by Jointly Learning to Align and Translate (2014)Neural Machine Translation by…Automatic differentiation in PyTorch (2017)Automatic differentiation in …Gaussian Processes for Machine Learning (2005)Gaussian Processes for Machin…Numerical Recipes, The Art of Scientific Computing (1987)Numerical Recipes, The Art of…Adaptive Subgradient Methods for Online Learning and Stochastic Optimization (2010)Adaptive Subgradient Methods …Simple statistical gradient-following algorithms for connectionist reinforcement learning (1992)Simple statistical gradient-f…Large-Scale Machine Learning with Stochastic Gradient Descent (2010)Large-Scale Machine Learning …Stochastic Backpropagation and Approximate Inference in Deep Generative Models (2014)Stochastic Backpropagation an…Theory of the backpropagation neural network (1989)Theory of the backpropagation…A Fast and Accurate Dependency Parser using Neural Networks (2014)A Fast and Accurate Dependenc…Extensions of recurrent neural network language model (2011)Extensions of recurrent neura…
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What this paper cites, inside the corpus

PaperYearCited
[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…201550,396
Learning representations by back-propagating errors198631,688
Deep learning in neural networks: An overview201418,236
Auto-Encoding Variational Bayes201315,583
Neural Machine Translation by Jointly Learning to Align and Translate201414,615
Automatic differentiation in PyTorch201711,099
Gaussian Processes for Machine Learning200510,470
Numerical Recipes, The Art of Scientific Computing198710,092
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization20108,621
Simple statistical gradient-following algorithms for connectionist reinforcement learning19927,519
Large-Scale Machine Learning with Stochastic Gradient Descent20105,695
Stochastic Backpropagation and Approximate Inference in Deep Generative Models20142,647
Theory of the backpropagation neural network19892,239
A Fast and Accurate Dependency Parser using Neural Networks20141,884
Extensions of recurrent neural network language model20111,603

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Topics

Gaussian Processes and Bayesian InferenceComputer Science
Neural Networks and ApplicationsComputer Science
Computational Physics and Python ApplicationsComputer Science

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complete

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  • supports4 author record(s) attached.
  • supports165 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

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Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:51+00:00.

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