Kevin Ellis

According to our database, Kevin Ellis authored at least 36 papers between 2014 and 2024.

Collaborative distances:

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

2024

WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment.

Hao Tang, Darren Key, Kevin Ellis

CoRR, 2024

Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning.

Top Piriyakulkij, Kevin Ellis

CoRR, 2024

2023

Top-Down Synthesis for Library Learning.

Matthew Bowers, Theo X. Olausson, Lionel Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama

Proc. ACM Program. Lang., January, 2023

Active Preference Inference using Language Models and Probabilistic Reasoning.

Top Piriyakulkij, Volodymyr Kuleshov, Kevin Ellis

CoRR, 2023

Rapid Motor Adaptation for Robotic Manipulator Arms.

Yichao Liang, Kevin Ellis, João Henriques

CoRR, 2023

Modeling Human-like Concept Learning with Bayesian Inference over Natural Language.

Kevin Ellis

CoRR, 2023

LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas.

Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language.

Kevin Ellis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

DeepSynth: Scaling Neural Program Synthesis with Distribution-based Search.

Théo Matricon, Nathanaël Fijalkow, Guillaume Lagarde, Kevin Ellis

J. Open Source Softw., October, 2022

Top-Down Synthesis for Library Learning.

Matthew Bowers, Theo X. Olausson, Catherine Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama

CoRR, 2022

I Speak, You Verify: Toward Trustworthy Neural Program Synthesis.

Darren Key, Wen-Ding Li, Kevin Ellis

CoRR, 2022

Efficient Pragmatic Program Synthesis with Informative Specifications.

Saujas Vaduguru, Kevin Ellis, Yewen Pu

CoRR, 2022

From perception to programs: regularize, overparameterize, and amortize.

Hao Tang, Kevin Ellis

Proceedings of the MAPS@PLDI 2022: 6th ACM SIGPLAN International Symposium on Machine Programming, 2022

Making Sense of Raw Input (Extended Abstract).

Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek J. Sergot

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

CrossBeam: Learning to Search in Bottom-Up Program Synthesis.

Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton

Proceedings of the Tenth International Conference on Learning Representations, 2022

Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface.

Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, Siddharth Narayanaswamy, Samuel Gershman, Joshua B. Tenenbaum

Proceedings of the Tenth International Conference on Learning Representations, 2022

Scaling Neural Program Synthesis with Distribution-Based Search.

Nathanaël Fijalkow, Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh Nayan Potta

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Neurosymbolic Programming.

Swarat Chaudhuri, Kevin Ellis, Oleksandr Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yue

Found. Trends Program. Lang., 2021

Making sense of raw input.

Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David P. Reichert, Pushmeet Kohli, Marek J. Sergot

Artif. Intell., 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

Leveraging Language to Learn Program Abstractions and Search Heuristics.

Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning.

Willem H. Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Timothy J. O'Donnell, Tim Sainburg, Timothy Gentner

Top. Cogn. Sci., 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 abstract structure for drawing by efficient motor program induction.

Lucas Yanan Tian, Kevin Ellis, Marta Kryven, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Program Synthesis with Pragmatic Communication.

Yewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum, Armando Solar-Lezama

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Write, Execute, Assess: Program Synthesis with a REPL.

Kevin Ellis, Maxwell I. Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando Solar-Lezama

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 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

Proceedings of the 7th International Conference on Learning Representations, 2019

Modeling Expertise with Neurally-Guided Bayesian Program Induction.

Catherine Wong, Kevin Ellis, Mathias Sablé-Meyer, Josh Tenenbaum

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

Parking Lot Occupancy Tracking Through Image Processing.

Marcos Lopez, Terry Griffin, Kevin Ellis, Anthony Enem, Christopher Duhan

Proceedings of 34th International Conference on Computers and Their Applications, 2019

2018

Learning to Infer Graphics Programs from Hand-Drawn Images.

Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Libraries of Subroutines for Neurally-Guided Bayesian Program Induction.

Kevin Ellis, Lucas Morales, Mathias Sablé-Meyer, Armando Solar-Lezama, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Learning to Learn Programs from Examples: Going Beyond Program Structure.

Kevin Ellis, Sumit Gulwani

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Sampling for Bayesian Program Learning.

Kevin Ellis, Armando Solar-Lezama, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Unsupervised Learning by Program Synthesis.

Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Dimensionality Reduction via Program Induction.

Kevin Ellis, Eyal Dechter, Joshua B. Tenenbaum

Proceedings of the 2015 AAAI Spring Symposia, 2015

2014

Bias reformulation for one-shot function induction.

Dianhuan Lin, Eyal Dechter, Kevin Ellis, Joshua B. Tenenbaum, Stephen H. Muggleton

Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014