Auditory scene analysis as Bayesian inference in sound source models. - Maddie Cusimano; Luke B. Hewitt; Josh Tenenbaum 001; Josh H. McDermott (CogSci, 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 (UAI, 2018)

Inferring Structured Visual Concepts from Minimal Data. - Peng Qian; Luke B. Hewitt; Josh Tenenbaum 001; Roger Levy (CogSci, 2019)

Learning to Infer Program Sketches. - Maxwell I. Nye; Luke B. Hewitt; Joshua B. Tenenbaum; Armando Solar-Lezama (ICML, 2019)

Learning to learn generative programs with Memoised Wake-Sleep. - Luke B. Hewitt; Tuan Anh Le 001; Joshua B. Tenenbaum (UAI, 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)

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 (PLDI, 2021)