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automatic differentiation

77 papers

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Also known as

AUTODIFF AD

Co-occurring keywords

variational inference (2069) gradient computation (45) gradient estimation (150) gaussian process (1200) differentiable programming (102) probabilistic programming (87) partial differential equation (222) neural network optimization (1293) deep learning (2118) gradient descent (1144)

Papers

PyTorch: An Imperative Style, High-Performance Deep Learning Library NIPS 2019
Online Normalization for Training Neural Networks NIPS 2019
Reversible Jump Probabilistic Programming AISTATS 2019
Small Steps and Giant Leaps: Minimal Newton Solvers for Deep Learning ICCV 2019
Differentiable Convex Optimization Layers NIPS 2019
A Differentiable Augmented Lagrangian Method for Bilevel Nonlinear Optimization RSS 2019
Computing Higher Order Derivatives of Matrix and Tensor Expressions NIPS 2018
Analytical Derivatives of Rigid Body Dynamics Algorithms RSS 2018
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models AISTATS 2018
Backpropagation with Callbacks: Foundations for Efficient and Expressive Differentiable Programming NIPS 2018
Provably Correct Automatic Sub-Differentiation for Qualified Programs NIPS 2018
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming NIPS 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation NIPS 2018
Automatic differentiation in ML: Where we are and where we should be going NIPS 2018
DiCE: The Infinitely Differentiable Monte Carlo Estimator ICML 2018
Automatic Differentiation in Machine Learning: a Survey JMLR 2018
Turing: A Language for Flexible Probabilistic Inference AISTATS 2018
Learning in Integer Latent Variable Models with Nested Automatic Differentiation ICML 2018
Marian: Fast Neural Machine Translation in C++ ACL 2018
Automatic Differentiation Variational Inference JMLR 2017
GPflow: A Gaussian Process Library using TensorFlow JMLR 2017
DrMAD: Distilling Reverse-Mode Automatic Differentiation for Optimizing Hyperparameters of Deep Neural Networks IJCAI 2016
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation JMLR 2016
Black-Box Alpha Divergence Minimization ICML 2016
Gradient Estimation Using Stochastic Computation Graphs NIPS 2015