Luke B. Hewitt

According to our database, Luke B. Hewitt authored at least 7 papers between 2018 and 2021.

Collaborative distances:

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

2021

DreamCoder: bootstrapping inductive program synthesis with wake-sleep library learning.

Kevin Ellis, Catherine Wong, Maxwell I. Nye, Mathias Sablé-Meyer, Lucas Morales, Luke B. Hewitt, Luc Cary, Armando Solar-Lezama, Joshua B. Tenenbaum

Proceedings of the PLDI '21: 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2021

2020

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning.

Kevin Ellis, Catherine Wong, Maxwell I. Nye, Mathias Sablé-Meyer, Luc Cary, Lucas Morales, Luke B. Hewitt, Armando Solar-Lezama, Joshua B. Tenenbaum

CoRR, 2020

Learning to learn generative programs with Memoised Wake-Sleep.

Luke B. Hewitt, Tuan Anh Le, Joshua B. Tenenbaum

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Learning to Infer Program Sketches.

Maxwell I. Nye, Luke B. Hewitt, Joshua B. Tenenbaum, Armando Solar-Lezama

Proceedings of the 36th International Conference on Machine Learning, 2019

Inferring Structured Visual Concepts from Minimal Data.

Peng Qian, Luke B. Hewitt, Josh Tenenbaum, Roger Levy

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2018

The Variational Homoencoder: Learning to learn high capacity generative models from few examples.

Luke B. Hewitt, Maxwell I. Nye, Andreea Gane, Tommi S. Jaakkola, Joshua B. Tenenbaum

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Auditory scene analysis as Bayesian inference in sound source models.

Maddie Cusimano, Luke B. Hewitt, Josh Tenenbaum, Josh H. McDermott

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018