Dougal Maclaurin

According to our database, Dougal Maclaurin authored at least 14 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Parallel Algebraic Effect Handlers.

Ningning Xie, Daniel D. Johnson, Dougal Maclaurin, Adam Paszke

Proc. ACM Program. Lang., 2024

PartIR: Composing SPMD Partitioning Strategies for Machine Learning.

Sami Alabed, Bart Chrzaszcz, Juliana Franco, Dominik Grewe, Dougal Maclaurin, James Molloy, Tom Natan, Tamara Norman, Xiaoyue Pan, Adam Paszke, Norman A. Rink, Michael Schaarschmidt, Timur Sitdikov, Agnieszka Swietlik, Dimitrios Vytiniotis, Joel Wee

CoRR, 2024

2023

You Only Linearize Once: Tangents Transpose to Gradients.

Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin

Proc. ACM Program. Lang., January, 2023

2022

The Foil: Capture-Avoiding Substitution With No Sharp Edges.

Dougal Maclaurin, Alexey Radul, Adam Paszke

Proceedings of the 34th Symposium on Implementation and Application of Functional Languages, 2022

2021

Getting to the point: index sets and parallelism-preserving autodiff for pointful array programming.

Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin

Proc. ACM Program. Lang., 2021

Decomposing reverse-mode automatic differentiation.

Roy Frostig, Matthew J. Johnson, Dougal Maclaurin, Adam Paszke, Alexey Radul

CoRR, 2021

Parallelism-preserving automatic differentiation for second-order array languages.

Adam Paszke, Matthew J. Johnson, Roy Frostig, Dougal Maclaurin

Proceedings of the FHPNC 2021: Proceedings of the 9th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing, 2021

2020

Differentiating a Tensor Language.

Gilbert Bernstein, Michael Mara, Tzu-Mao Li, Dougal Maclaurin, Jonathan Ragan-Kelley

CoRR, 2020

Automatically batching control-intensive programs for modern accelerators.

Alexey Radul, Brian Patton, Dougal Maclaurin, Matthew D. Hoffman, Rif A. Saurous

Proceedings of the Third Conference on Machine Learning and Systems, 2020

2016

Early Stopping as Nonparametric Variational Inference.

David Duvenaud, Dougal Maclaurin, Ryan P. Adams

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Early Stopping is Nonparametric Variational Inference.

Dougal Maclaurin, David Duvenaud, Ryan P. Adams

CoRR, 2015

Convolutional Networks on Graphs for Learning Molecular Fingerprints.

David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Firefly Monte Carlo: Exact MCMC with Subsets of Data.

Dougal Maclaurin, Ryan Prescott Adams

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Gradient-based Hyperparameter Optimization through Reversible Learning.

Dougal Maclaurin, David Duvenaud, Ryan P. Adams

Proceedings of the 32nd International Conference on Machine Learning, 2015