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10/10/2022
The Foil: Capture-Avoiding Substitution With No Sharp Edges
Correctly manipulating program terms in a compiler is surprisingly diffi...
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04/22/2022
You Only Linearize Once: Tangents Transpose to Gradients
Automatic differentiation (AD) is conventionally understood as a family ...
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10/14/2021
Parallel Algebraic Effect Handlers
Algebraic effects and handlers support composable and structured control...
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05/20/2021
Decomposing reverse-mode automatic differentiation
We decompose reverse-mode automatic differentiation into (forward-mode) ...
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04/12/2021
Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming
We present a novel programming language design that attempts to combine ...
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08/25/2020
Differentiating a Tensor Language
How does one compile derivatives of tensor programs, such that the resul...
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10/23/2019
Automatically Batching Control-Intensive Programs for Modern Accelerators
We present a general approach to batching arbitrary computations for acc...
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09/30/2015
Convolutional Networks on Graphs for Learning Molecular Fingerprints
We introduce a convolutional neural network that operates directly on gr...
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04/06/2015
Early Stopping is Nonparametric Variational Inference
We show that unconverged stochastic gradient descent can be interpreted ...
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02/11/2015
Gradient-based Hyperparameter Optimization through Reversible Learning
Tuning hyperparameters of learning algorithms is hard because gradients ...
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03/22/2014
