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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

An Interpretable Approach to the Solutions of High-Dimensional Partial Differential Equations AAAI 2024
Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs NIPS 2024
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks NIPS 2024
Optimizing Automatic Differentiation with Deep Reinforcement Learning NIPS 2024
Spectrum Extraction and Clipping for Implicitly Linear Layers AISTATS 2024
Federated Automatic Differentiation JMLR 2024
Gradients of Functions of Large Matrices NIPS 2024
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators NIPS 2024
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation AISTATS 2024
SynJax: Structured Probability Distributions for JAX EMNLP 2023
Backpropagation of Unrolled Solvers with Folded Optimization IJCAI 2023
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra NIPS 2023
Separable Physics-Informed Neural Networks NIPS 2023
PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers AAAI 2023
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters ICML 2023
One-step differentiation of iterative algorithms NIPS 2023
Automatic differentiation of nonsmooth iterative algorithms NIPS 2022
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks PGM 2022
Proppo: a Message Passing Framework for Customizable and Composable Learning Algorithms NIPS 2022
Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning JMLR 2022
Learning soft interventions in complex equilibrium systems UAI 2022
Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation ICML 2022
JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data JMLR 2022
Optimization for Classical Machine Learning Problems on the GPU AAAI 2022
tntorch: Tensor Network Learning with PyTorch JMLR 2022