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[LAFI'22] Programming Languages for Automatic Differentiation: What Now?

[LAFI'22] Programming Languages for Automatic Differentiation: What Now?

[LAFI'22] Probabilistic and Differentiable Programming in Scientific Simulators

[LAFI'22] Probabilistic and Differentiable Programming in Scientific Simulators

[LAFI'24] Abstract Interpretation for Automatic Differentiation

[LAFI'24] Abstract Interpretation for Automatic Differentiation

[LAFI'22] A Language and Smoothed Semantics for Convergent Stochastic Gradient Descent

[LAFI'22] A Language and Smoothed Semantics for Convergent Stochastic Gradient Descent

[LAFI'22] Towards Denotational Semantics of AD for Higher-Order, Recursive, Probabilistic

[LAFI'22] Towards Denotational Semantics of AD for Higher-Order, Recursive, Probabilistic

[POPL 2021] Automatic Differentiation in PCF (full)

[POPL 2021] Automatic Differentiation in PCF (full)

Lecture 2.4: Automatic Differentiation (DLVU)

Lecture 2.4: Automatic Differentiation (DLVU)

[POPL'22] Provably Correct, Asymptotically Efficient, Higher-Order Reverse-Mode Automatic

[POPL'22] Provably Correct, Asymptotically Efficient, Higher-Order Reverse-Mode Automatic

Keynote: Automatic Differentiation for Dummies

Keynote: Automatic Differentiation for Dummies

Provably Correct, Asymptotically Efficient, Higher-Order Reverse-Mode Automatic Differenti (Teaser)

Provably Correct, Asymptotically Efficient, Higher-Order Reverse-Mode Automatic Differenti (Teaser)

Transformations & AutoDiff | Lecture 3 | MIT Computational Thinking Spring 2021

Transformations & AutoDiff | Lecture 3 | MIT Computational Thinking Spring 2021

[LAFI'24] Reverse mode ADEV via YOLO: tangent estimators transpose to gradient estimators

[LAFI'24] Reverse mode ADEV via YOLO: tangent estimators transpose to gradient estimators