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automatic differentiation

92 papers

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Also known as

AUTODIFF AD

Co-occurring keywords · papers mentioning both

variational inference (10) gradient computation (9) gradient estimation (8) differentiable programming (8) partial differential equation (8) gaussian process (7) gradient descent (5) probabilistic programming (5) physics-informed neural network (5) neural network optimization (5)

Papers

A Common Interface for Automatic Differentiation JMLR 2026 STDE++: Polynomial-Time Amortization for Linear Differential Operators JMLR 2026 Automatic Differentiation of Optimization Algorithms with Time-Varying Updates ICML 2025 Energy-consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations AISTATS 2025 An Interpretable Approach to the Solutions of High-Dimensional Partial Differential Equations AAAI 2024 Automatic Functional Differentiation in JAX ICLR 2024 fairret: a Framework for Differentiable Fairness Regularization Terms ICLR 2024 Federated Automatic Differentiation JMLR 2024 Fiber Monte Carlo ICLR 2024 Gradients of Functions of Large Matrices NeurIPS 2024 Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks NeurIPS 2024 Nonparametric Automatic Differentiation Variational Inference with Spline Approximation AISTATS 2024 Optimizing Automatic Differentiation with Deep Reinforcement Learning NeurIPS 2024 Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation ICML 2024 Spectrum Extraction and Clipping for Implicitly Linear Layers AISTATS 2024 Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators NeurIPS 2024 Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs NeurIPS 2024 Using Autodiff to Estimate Posterior Moments, Marginals and Samples UAI 2024 What does automatic differentiation compute for neural networks? ICLR 2024 Backpropagation of Unrolled Solvers with Folded Optimization IJCAI 2023 Betty: An Automatic Differentiation Library for Multilevel Optimization ICLR 2023 CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra NeurIPS 2023 One-step differentiation of iterative algorithms NeurIPS 2023 On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters ICML 2023 PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers AAAI 2023