Luke B. Hewitt

Publication Activity (10 Years)

Years Active: 2018-2021
Publications (10 Years): 10

Top Topics

Novice Programmers

Generative Model

Bayesian Inference

Top Venues

Publications

Kevin Ellis, Catherine Wong, Maxwell I. Nye, Mathias Sablé-Meyer, Lucas Morales, Luke B. Hewitt, Luc Cary, Armando Solar-Lezama, Joshua B. Tenenbaum
DreamCoder: bootstrapping inductive program synthesis with wake-sleep library learning. PLDI (2021)
Luke B. Hewitt, Tuan Anh Le, Joshua B. Tenenbaum
Learning to learn generative programs with Memoised Wake-Sleep. CoRR (2020)
Luke B. Hewitt, Tuan Anh Le, Joshua B. Tenenbaum
Learning to learn generative programs with Memoised Wake-Sleep. UAI (2020)
Kevin Ellis, Catherine Wong, Maxwell I. Nye, Mathias Sablé-Meyer, Luc Cary, Lucas Morales, Luke B. Hewitt, Armando Solar-Lezama, Joshua B. Tenenbaum
DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning. CoRR (2020)
Maxwell I. Nye, Luke B. Hewitt, Joshua B. Tenenbaum, Armando Solar-Lezama
Learning to Infer Program Sketches. ICML (2019)
Peng Qian, Luke B. Hewitt, Josh Tenenbaum, Roger Levy
Inferring Structured Visual Concepts from Minimal Data. CogSci (2019)
Maxwell I. Nye, Luke B. Hewitt, Joshua B. Tenenbaum, Armando Solar-Lezama
Learning to Infer Program Sketches. CoRR (2019)
Luke B. Hewitt, Maxwell I. Nye, Andreea Gane, Tommi S. Jaakkola, Joshua B. Tenenbaum
The Variational Homoencoder: Learning to learn high capacity generative models from few examples. CoRR (2018)
Maddie Cusimano, Luke B. Hewitt, Josh Tenenbaum, Josh H. McDermott
Auditory scene analysis as Bayesian inference in sound source models. CogSci (2018)
Luke B. Hewitt, Maxwell I. Nye, Andreea Gane, Tommi S. Jaakkola, Joshua B. Tenenbaum
The Variational Homoencoder: Learning to learn high capacity generative models from few examples. UAI (2018)