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06/13/2023
Differentiating Metropolis-Hastings to Optimize Intractable Densities
We develop an algorithm for automatic differentiation of Metropolis-Hast...
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03/13/2023
∇SD: Differentiable Programming for Sparse Tensors
Sparse tensors are prevalent in many data-intensive applications, yet ex...
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02/21/2023
ωPAP Spaces: Reasoning Denotationally About Higher-Order, Recursive Probabilistic and Differentiable Programs
We introduce a new setting, the category of ωPAP spaces, for reasoning d...
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12/20/2022
Efficient and Sound Differentiable Programming in a Functional Array-Processing Language
Automatic differentiation (AD) is a technique for computing the derivati...
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12/19/2022
Denotationally Correct, Purely Functional, Efficient Reverse-mode Automatic Differentiation
Reverse-mode differentiation is used for optimization, but it introduces...
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12/13/2022
ADEV: Sound Automatic Differentiation of Expected Values of Probabilistic Programs
Optimizing the expected values of probabilistic processes is a central p...
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11/18/2022
Compiling Structured Tensor Algebra
Tensor algebra is essential for data-intensive workloads in various comp...
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11/30/2021
Towards Denotational Semantics of AD for Higher-Order, Recursive, Probabilistic Languages
Automatic differentiation (AD) aims to compute derivatives of user-defin...
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03/10/2021
Functional Collection Programming with Semi-Ring Dictionaries
This paper introduces semi-ring dictionaries, a powerful class of compos...
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01/17/2021
Higher Order Automatic Differentiation of Higher Order Functions
We present semantic correctness proofs of automatic differentiation (AD)...
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01/07/2020
Correctness of Automatic Differentiation via Diffeologies and Categorical Gluing
We present semantic correctness proofs of Automatic Differentiation (AD)...
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04/21/2019
Quantum channels as a categorical completion
We propose a categorical foundation for the connection between pure and ...
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01/29/2019
