Kevin Ellis

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 47

Top Topics

Dimensionality Reduction

Probabilistic Reasoning

Unsupervised Learning

Robotic Manipulator

Top Venues

Publications

Top Piriyakulkij, Kevin Ellis
Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning. CoRR (2024)
Hao Tang, Darren Key, Kevin Ellis
WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment. CoRR (2024)
Wen-Ding Li, Kevin Ellis
Is Programming by Example solved by LLMs? CoRR (2024)
Hao Tang, Keya Hu, Jin Peng Zhou, Sicheng Zhong, Wei-Long Zheng, Xujie Si, Kevin Ellis
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff. CoRR (2024)
Matthew Bowers, Theo X. Olausson, Lionel Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama
Top-Down Synthesis for Library Learning. Proc. ACM Program. Lang. 7 (POPL) (2023)
Kevin Ellis
Modeling Human-like Concept Learning with Bayesian Inference over Natural Language. CoRR (2023)
Top Piriyakulkij, Volodymyr Kuleshov, Kevin Ellis
Active Preference Inference using Language Models and Probabilistic Reasoning. CoRR (2023)
Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. CoRR (2023)
Kevin Ellis
Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language. NeurIPS (2023)
Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. NeurIPS (2023)
Hao Tang, Kevin Ellis
From Perception to Programs: Regularize, Overparameterize, and Amortize. ICML (2023)
Yichao Liang, Kevin Ellis, João Henriques
Rapid Motor Adaptation for Robotic Manipulator Arms. CoRR (2023)
Théo Matricon, Nathanaël Fijalkow, Guillaume Lagarde, Kevin Ellis
DeepSynth: Scaling Neural Program Synthesis with Distribution-based Search. J. Open Source Softw. 7 (78) (2022)
Darren Key, Wen-Ding Li, Kevin Ellis
I Speak, You Verify: Toward Trustworthy Neural Program Synthesis. CoRR (2022)
Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
CrossBeam: Learning to Search in Bottom-Up Program Synthesis. ICLR (2022)
Nathanaël Fijalkow, Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh Nayan Potta
Scaling Neural Program Synthesis with Distribution-Based Search. AAAI (2022)
Hao Tang, Kevin Ellis
From perception to programs: regularize, overparameterize, and amortize. MAPS@PLDI (2022)
Hao Tang, Kevin Ellis
From Perception to Programs: Regularize, Overparameterize, and Amortize. CoRR (2022)
Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
CrossBeam: Learning to Search in Bottom-Up Program Synthesis. CoRR (2022)
Saujas Vaduguru, Kevin Ellis, Yewen Pu
Efficient Pragmatic Program Synthesis with Informative Specifications. CoRR (2022)
Matthew Bowers, Theo X. Olausson, Catherine Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama
Top-Down Synthesis for Library Learning. CoRR (2022)
Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, Siddharth Narayanaswamy, Samuel Gershman, Joshua B. Tenenbaum
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface. ICLR (2022)
Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek J. Sergot
Making Sense of Raw Input (Extended Abstract). IJCAI (2022)
Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, N. Siddharth, Samuel J. Gershman, Joshua B. Tenenbaum
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface. CoRR (2021)
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)
Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas
Leveraging Language to Learn Program Abstractions and Search Heuristics. ICML (2021)
Nathanaël Fijalkow, Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh Potta
Scaling Neural Program Synthesis with Distribution-based Search. CoRR (2021)
Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David P. Reichert, Pushmeet Kohli, Marek J. Sergot
Making sense of raw input. Artif. Intell. 299 (2021)
Swarat Chaudhuri, Kevin Ellis, Oleksandr Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yue
Neurosymbolic Programming. Found. Trends Program. Lang. 7 (3) (2021)
Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas
Leveraging Language to Learn Program Abstractions and Search Heuristics. CoRR (2021)
Lucas Y. Tian, Kevin Ellis, Marta Kryven, Joshua B. Tenenbaum
Learning abstract structure for drawing by efficient motor program induction. CoRR (2020)
Yewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum, Armando Solar-Lezama
Program Synthesis with Pragmatic Communication. CoRR (2020)
Yewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum, Armando Solar-Lezama
Program Synthesis with Pragmatic Communication. NeurIPS (2020)
Willem H. Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Timothy J. O'Donnell, Tim Sainburg, Timothy Gentner
Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning. Top. Cogn. Sci. 12 (3) (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)
Lucas Y. Tian, Kevin Ellis, Marta Kryven, Josh Tenenbaum
Learning abstract structure for drawing by efficient motor program induction. NeurIPS (2020)
Kevin Ellis, Maxwell I. Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando Solar-Lezama
Write, Execute, Assess: Program Synthesis with a REPL. CoRR (2019)
Catherine Wong, Kevin Ellis, Mathias Sablé-Meyer, Josh Tenenbaum
Modeling Expertise with Neurally-Guided Bayesian Program Induction. CogSci (2019)
Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
Learning to Infer and Execute 3D Shape Programs. CoRR (2019)
Kevin Ellis, Maxwell I. Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando Solar-Lezama
Write, Execute, Assess: Program Synthesis with a REPL. NeurIPS (2019)
Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
Learning to Infer and Execute 3D Shape Programs. ICLR (Poster) (2019)
Marcos Lopez, Terry Griffin, Kevin Ellis, Anthony Enem, Christopher Duhan
Parking Lot Occupancy Tracking Through Image Processing. CATA (2019)
Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Josh Tenenbaum
Learning to Infer Graphics Programs from Hand-Drawn Images. NeurIPS (2018)
Kevin Ellis, Lucas Morales, Mathias Sablé-Meyer, Armando Solar-Lezama, Josh Tenenbaum
Learning Libraries of Subroutines for Neurally-Guided Bayesian Program Induction. NeurIPS (2018)
Kevin Ellis, Sumit Gulwani
Learning to Learn Programs from Examples: Going Beyond Program Structure. IJCAI (2017)
Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Joshua B. Tenenbaum
Learning to Infer Graphics Programs from Hand-Drawn Images. CoRR (2017)
Kevin Ellis, Armando Solar-Lezama, Josh Tenenbaum
Sampling for Bayesian Program Learning. NIPS (2016)
Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum
Unsupervised Learning by Program Synthesis. NIPS (2015)
Kevin Ellis, Eyal Dechter, Joshua B. Tenenbaum
Dimensionality Reduction via Program Induction. AAAI Spring Symposia (2015)
Dianhuan Lin, Eyal Dechter, Kevin Ellis, Joshua B. Tenenbaum, Stephen Muggleton
Bias reformulation for one-shot function induction. ECAI (2014)