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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

Convexity Certificates from Hessians NIPS 2022
Optimization for Classical Machine Learning Problems on the GPU AAAI 2022
tntorch: Tensor Network Learning with PyTorch JMLR 2022
Automatic Differentiation of Programs with Discrete Randomness NIPS 2022
Variational inference for nonlinear ordinary differential equations AISTATS 2021
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics ICML 2021
Differentiable Spline Approximations NIPS 2021
Kernel Operations on the GPU, with Autodiff, without Memory Overflows JMLR 2021
Storchastic: A Framework for General Stochastic Automatic Differentiation NIPS 2021
RMP2: A Structured Composable Policy Class for Robot Learning RSS 2021
Using Physics Knowledge for Learning Rigid-body Forward Dynamics with Gaussian Process Force Priors CORL 2021
Automatic Differentiation of Some First-Order Methods in Parametric Optimization AISTATS 2020
A mathematical model for automatic differentiation in machine learning NIPS 2020
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients NIPS 2020
Deep Differentiable Grasp Planner for High-DOF Grippers RSS 2020
Automatic Differentiation of Sketched Regression AISTATS 2020
Tensor Train Decomposition on TensorFlow (T3F) JMLR 2020
Super-efficiency of automatic differentiation for functions defined as a minimum ICML 2020
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits ICML 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization ICML 2020
Learning Differential Equations that are Easy to Solve NIPS 2020
On Correctness of Automatic Differentiation for Non-Differentiable Functions NIPS 2020
A Simple and Efficient Tensor Calculus AAAI 2020
Neural Likelihoods via Cumulative Distribution Functions UAI 2020
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019