Research InterestsWhat would it take to build a machine that can learn, reason, and perceive as flexibly and efficiently as a human? I investigate the hypothesis that at least part of the answer to this question involves program learning, which means inferring programs from data. Main themes of my research are:
Write, Execute, Assess: Program Synthesis with a REPL. Kevin Ellis*, Maxwell Nye*, Yewen Pu*, Felix Sosa*, Josh Tenenbaum, and Armando Solar-Lezama. (* equal contribution). NeurIPS 2019. Download paper.
Learning to Infer and Execute 3D Shape Programs. Tian, Yonglong, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, and Jiajun Wu. ICLR 2019. Download paper.
Willem Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Tim O'Donnell, Tim Sainburgh and Tim Gentner. Five ways in which computational modeling can help advance cognitive science: lessons from Artificial Grammar Learning. Topics in Cognitive Science. 2019.
Learning Libraries of Subroutines for Neurally-Guided Bayesian Program Induction. Kevin Ellis, Lucas Morales, Mathias Sablé-Meyer, Armando Solar-Lezama, Joshua B. Tenenbaum. NeurIPS 2018 Spotlight paper.. Download code and data.
Learning to Infer Graphics Programs from Hand-Drawn Images. Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Joshua B. Tenenbaum. NeurIPS 2018 Spotlight paper. arXiv link. Download code and data.
Learning to Learn Programs from Examples: Going Beyond Program Structure. Kevin Ellis, Sumit Gulwani. IJCAI 2017. Download paper.
Sampling for Bayesian Program Learning. Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum. NeurIPS 2016. Download paper. Download supplement. Download code.
Metareasoning in Symbolic Domains. Kevin Ellis, Owen Lewis. NeurIPS 2015 Workshop on Bounded Optimality and Rational Metareasoning. Download paper.
Unsupervised Learning by Program Synthesis. Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum. NeurIPS 2015. Download paper. Download supplement. Download poster. Download code.
Dimensionality Reduction via Program Induction. Kevin Ellis, Eyal Dechter, Joshua B. Tenenbaum. AAAI Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches. 2015: 48-52. Download paper.
Bias reformulation for one-shot function induction. Dianhuan Lin, Eyal Dechter, Kevin Ellis, Joshua B. Tenenbaum, Stephen Muggleton. ECAI 2014: 525-530. Download paper.
Learning Graphical Concepts. Kevin Ellis, Eyal Dechter, Ryan Adams, and Joshua Tenenbaum. NeurIPS 2013 workshop on Constructive Machine Learning. Download paper. Download slides. Download poster.