automatic differentiation

Computing Higher Order Derivatives of Matrix and Tensor Expressions NeurIPS 2018 DiCE: The Infinitely Differentiable Monte Carlo Estimator ICML 2018 Learning in Integer Latent Variable Models with Nested Automatic Differentiation ICML 2018 Lipschitz regularity of deep neural networks: analysis and efficient estimation NeurIPS 2018 Marian: Fast Neural Machine Translation in C++ ACL 2018 Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models AISTATS 2018 Provably Correct Automatic Sub-Differentiation for Qualified Programs NeurIPS 2018 Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming NeurIPS 2018 Turing: A Language for Flexible Probabilistic Inference AISTATS 2018 Automatic Differentiation Variational Inference JMLR 2017 GPflow: A Gaussian Process Library using TensorFlow JMLR 2017 Black-Box Alpha Divergence Minimization ICML 2016 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 Automatic Variational Inference in Stan NeurIPS 2015 Gradient Estimation Using Stochastic Computation Graphs NeurIPS 2015 Nonstandard Interpretations of Probabilistic Programs for Efficient Inference NeurIPS 2011