Dougal Maclaurin

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 14

Top Topics

Epipolar Geometry

Variational Inference

Top Venues

Proc. ACM Program. Lang.

Publications

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
PartIR: Composing SPMD Partitioning Strategies for Machine Learning. CoRR (2024)
Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
You Only Linearize Once: Tangents Transpose to Gradients. Proc. ACM Program. Lang. 7 (POPL) (2023)
Dougal Maclaurin, Alexey Radul, Adam Paszke
The Foil: Capture-Avoiding Substitution With No Sharp Edges. CoRR (2022)
Dougal Maclaurin, Alexey Radul, Adam Paszke
The Foil: Capture-Avoiding Substitution With No Sharp Edges. IFL (2022)
Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
You Only Linearize Once: Tangents Transpose to Gradients. CoRR (2022)
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
Getting to the point: index sets and parallelism-preserving autodiff for pointful array programming. Proc. ACM Program. Lang. 5 (POPL) (2021)
Adam Paszke, Matthew J. Johnson, Roy Frostig, Dougal Maclaurin
Parallelism-preserving automatic differentiation for second-order array languages. FHPNC@ICFP (2021)
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming. CoRR (2021)
Roy Frostig, Matthew J. Johnson, Dougal Maclaurin, Adam Paszke, Alexey Radul
Decomposing reverse-mode automatic differentiation. CoRR (2021)
Ningning Xie, Daniel D. Johnson, Dougal Maclaurin, Adam Paszke
Parallel Algebraic Effect Handlers. CoRR (2021)
Gilbert Bernstein, Michael Mara, Tzu-Mao Li, Dougal Maclaurin, Jonathan Ragan-Kelley
Differentiating a Tensor Language. CoRR (2020)
Alexey Radul, Brian Patton, Dougal Maclaurin, Matthew D. Hoffman, Rif A. Saurous
Automatically batching control-intensive programs for modern accelerators. MLSys (2020)
Alexey Radul, Brian Patton, Dougal Maclaurin, Matthew D. Hoffman, Rif A. Saurous
Automatically Batching Control-Intensive Programs for Modern Accelerators. CoRR (2019)
David Duvenaud, Dougal Maclaurin, Ryan P. Adams
Early Stopping as Nonparametric Variational Inference. AISTATS (2016)
David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams
Convolutional Networks on Graphs for Learning Molecular Fingerprints. CoRR (2015)
David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams
Convolutional Networks on Graphs for Learning Molecular Fingerprints. NIPS (2015)
Dougal Maclaurin, Ryan Prescott Adams
Firefly Monte Carlo: Exact MCMC with Subsets of Data. IJCAI (2015)
Dougal Maclaurin, David Duvenaud, Ryan P. Adams
Gradient-based Hyperparameter Optimization through Reversible Learning. CoRR (2015)
Dougal Maclaurin, David Duvenaud, Ryan P. Adams
Early Stopping is Nonparametric Variational Inference. CoRR (2015)
Dougal Maclaurin, David Duvenaud, Ryan P. Adams
Gradient-based Hyperparameter Optimization through Reversible Learning. ICML (2015)
Dougal Maclaurin, Ryan P. Adams
Firefly Monte Carlo: Exact MCMC with Subsets of Data. UAI (2014)
Dougal Maclaurin, Ryan P. Adams
Firefly Monte Carlo: Exact MCMC with Subsets of Data. CoRR (2014)