Note: Most up to date is always Google Scholar

WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment
    Hao Tang, Darren Key, Kevin Ellis
    NeurIPS 2024

Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning
    Wasu (Top) Piriyakulkij, Cassidy Lagenfeld, Tuan-Anh Le, Kevin Ellis
    NeurIPS 2024

Is Programming by Example Solved by LLMs?
    Wen-Ding Li, Kevin Ellis
    NeurIPS 2024

Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
    Hao Tang, Keya Hu, Jin Peng Zhou, Sicheng Zhong, Wei-Long Zheng, Xujie Si, Kevin Ellis
    NeurIPS 2024

Symbolic metaprogram search improves learning efficiency and explains rule learning in humans
    Joshua S. Rule, Steven T. Piantadosi, Andrew Cropper, Kevin Ellis, Maxwell Nye, Joshua B. Tenenbaum
    Nature Communications 2024

Rapid Motor Adaptation for Robotic Manipulator Arms
    Yichao Liang, Kevin Ellis, João Henriques
    CVPR 2024

Discovering quantum circuit components with program synthesis
    Leopoldo Sarra, Kevin Ellis, Florian Marquardt
    MLST 2024

Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language
    Kevin Ellis
    NeurIPS 2023 (Oral)

LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas
    Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
    NeurIPS 2023

Toward Trustworthy Neural Program Synthesis
    Wen-Ding Li, Darren Key, Kevin Ellis
    arXiv 2023

From Perception to Programs: Regularize, Overparameterize, and Amortize
    Hao Tang, Kevin Ellis
    ICML 2023

Top-Down Synthesis For Library Learning
    Matthew Bowers, Theo X. Olausson, Catherine Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama
    POPL 2023

A language of thought for the mental representation of geometric shapes
    Mathias Sablé-Meyer, Kevin Ellis, Josh Tenenbaum, Stanislas Dehaene
    Cognitive Psychology 2023

Synthesizing theories of human language with Bayesian program induction
    Kevin Ellis, Adam Albright, Armando Solar-Lezama, Joshua B. Tenenbaum, Timothy J. O’Donnell
    Nature Communications 2022

CrossBeam: Learning to Search in Bottom-Up Program Synthesis
    Kensen Shi*, Hanjun Dai*, Kevin Ellis, Charles Sutton
    ICLR 2022

Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface
    Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, Siddharth N, Samuel J. Gershman, Joshua B. Tenenbaum
    ICLR 2022

Scaling Neural Program Synthesis with Distribution-based Search
    Nathanaël Fijalkow, Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh Potta
    AAAI 2022

DreamCoder: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning
    Kevin Ellis, Catherine Wong, Maxwell Nye, Mathias Sablé-Meyer, Lucas Morales, Luke Hewitt, Luc Cary, Armando Solar-Lezama, Joshua B. Tenenbaum
    PLDI 2021

Neurosymbolic Programming
    Swarat Chaudhuri, Kevin Ellis, Oleksandr Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yue
    FnT in Programming Languages 2021

Making sense of raw input
    Richard Evans, Matko Bošnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek Sergot
    Artificial Intelligence 2021

Leveraging natural language for program search and abstraction learning
    Catherine Wong, Kevin Ellis, Josh Tenenbaum, Jacob Andreas
    ICML 2021

Phonological Interactions, Process Types, and Minimum Description Length Principles
    Christopher Yang, Kevin Ellis
    CogSci 2021

Learning abstract structure for drawing by efficient motor program induction
    Lucas Y. Tian, Kevin Ellis, Marta Kryven, Joshua B. Tenenbaum
    NeurIPS 2020 (Oral)

Program Synthesis with Pragmatic Communication
    Yewen Pu, Kevin Ellis, Marta Kryven, Joshua B. Tenenbaum, Armando Solar-Lezama
    NeurIPS 2020

Write, Execute, Assess: Program Synthesis with a REPL
    Kevin Ellis*, Maxwell Nye*, Yewen Pu*, Felix Sosa*, Joshua B. Tenenbaum, Armando Solar-Lezama
    NeurIPS 2019

Learning to Infer and Execute 3D Shape Programs
    Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
    ICLR 2019

Five ways in which computational modeling can help advance cognitive science: lessons from Artificial Grammar Learning
    Willem Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Tim O’Donnell, Tim Sainburgh, Tim Gentner
    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

Learning to Infer Graphics Programs from Hand-Drawn Images
    Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Joshua B. Tenenbaum
    NeurIPS 2018

Learning to Learn Programs from Examples: Going Beyond Program Structure
    Kevin Ellis, Sumit Gulwani
    IJCAI 2017

Sampling for Bayesian Program Learning
    Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum
    NeurIPS 2016

Unsupervised Learning by Program Synthesis
    Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum
    NeurIPS 2015

Dimensionality Reduction via Program Induction
    Kevin Ellis, Eyal Dechter, Joshua B. Tenenbaum
    AAAI Symposium 2015

Bias reformulation for one-shot function induction
    Dianhuan Lin, Eyal Dechter, Kevin Ellis, Joshua B. Tenenbaum, Stephen Muggleton
    ECAI 2014