Alexander K. Lew

According to our database, Alexander K. Lew authored at least 16 papers between 2019 and 2024.

Collaborative distances:

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

2024

GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables.

Mathieu Huot, Matin Ghavami, Alexander K. Lew, Ulrich Schaechtle, Cameron E. Freer, Zane Shelby, Martin C. Rinard, Feras A. Saad, Vikash K. Mansinghka

Proc. ACM Program. Lang., 2024

Probabilistic Programming with Programmable Variational Inference.

McCoy R. Becker, Alexander K. Lew, Xiaoyan Wang, Matin Ghavami, Mathieu Huot, Martin C. Rinard, Vikash K. Mansinghka

Proc. ACM Program. Lang., 2024

2023

ADEV: Sound Automatic Differentiation of Expected Values of Probabilistic Programs.

Alexander K. Lew, Mathieu Huot, Sam Staton, Vikash K. Mansinghka

Proc. ACM Program. Lang., January, 2023

Probabilistic Programming with Stochastic Probabilities.

Alexander K. Lew, Matin Ghavamizadeh, Martin C. Rinard, Vikash K. Mansinghka

Proc. ACM Program. Lang., 2023

From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought.

Lionel Wong, Gabriel Grand, Alexander K. Lew, Noah D. Goodman, Vikash K. Mansinghka, Jacob Andreas, Joshua B. Tenenbaum

CoRR, 2023

Differentiating Metropolis-Hastings to Optimize Intractable Densities.

Gaurav Arya, Ruben Seyer, Frank Schäfer, Alexander K. Lew, Mathieu Huot, Vikash K. Mansinghka, Chris Rackauckas, Kartik Chandra, Moritz Schauer

CoRR, 2023

Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs.

Alexander K. Lew, Tan Zhi-Xuan, Gabriel Grand, Vikash K. Mansinghka

CoRR, 2023

ωPAP Spaces: Reasoning Denotationally About Higher-Order, Recursive Probabilistic and Differentiable Programs.

Mathieu Huot, Alexander K. Lew, Vikash K. Mansinghka, Sam Staton

Proceedings of the 38th Annual ACM/IEEE Symposium on Logic in Computer Science, 2023

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals.

Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Recursive Monte Carlo and variational inference with auxiliary variables.

Alexander K. Lew, Marco F. Cusumano-Towner, Vikash K. Mansinghka

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Towards Denotational Semantics of AD for Higher-Order, Recursive, Probabilistic Languages.

Alexander K. Lew, Mathieu Huot, Vikash K. Mansinghka

CoRR, 2021

PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming.

Alexander K. Lew, Monica Agrawal, David A. Sontag, Vikash Mansinghka

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Trace types and denotational semantics for sound programmable inference in probabilistic languages.

Alexander K. Lew, Marco F. Cusumano-Towner, Benjamin Sherman, Michael Carbin, Vikash K. Mansinghka

Proc. ACM Program. Lang., 2020

Leveraging Unstructured Statistical Knowledge in a Probabilistic Language of Thought.

Alexander K. Lew, Michael Henry Tessler, Vikash Mansinghka, Josh Tenenbaum

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

2019

Bayesian causal inference via probabilistic program synthesis.

Sam Witty, Alexander K. Lew, David D. Jensen, Vikash Mansinghka

CoRR, 2019

Gen: a general-purpose probabilistic programming system with programmable inference.

Marco F. Cusumano-Towner, Feras A. Saad, Alexander K. Lew, Vikash K. Mansinghka

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2019