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Journal Articles
- 2023
[j5]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): 1182-1213 (2023)- 2022
- [j4]Théo Matricon, Nathanaël Fijalkow, Guillaume Lagarde, Kevin Ellis:
DeepSynth: Scaling Neural Program Synthesis with Distribution-based Search. J. Open Source Softw. 7(78): 4151 (2022) - 2021
- [j3]Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David P. Reichert, Pushmeet Kohli, Marek J. Sergot:
Making sense of raw input. Artif. Intell. 299: 103521 (2021) - [j2]Swarat Chaudhuri, Kevin Ellis, Oleksandr Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yue:
Neurosymbolic Programming. Found. Trends Program. Lang. 7(3): 158-243 (2021) - 2020
- [j1]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): 925-941 (2020)
Conference and Workshop Papers
- 2024
- [c24]Yichao Liang, Kevin Ellis, João Henriques:
Rapid Motor Adaptation for Robotic Manipulator Arms. CVPR 2024: 16404-16413 - 2023
- [c23]Hao Tang, Kevin Ellis:
From Perception to Programs: Regularize, Overparameterize, and Amortize. ICML 2023: 33616-33631 - [c22]Kevin Ellis:
Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language. NeurIPS 2023 - [c21]Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton:
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. NeurIPS 2023 - 2022
- [c20]Nathanaël Fijalkow, Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh Nayan Potta:
Scaling Neural Program Synthesis with Distribution-Based Search. AAAI 2022: 6623-6630 - [c19]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 - [c18]Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton:
CrossBeam: Learning to Search in Bottom-Up Program Synthesis. ICLR 2022 - [c17]Richard Evans, Matko Bosnjak, Lars Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek J. Sergot:
Making Sense of Raw Input (Extended Abstract). IJCAI 2022: 5727-5731 - [c16]Hao Tang, Kevin Ellis:
From perception to programs: regularize, overparameterize, and amortize. MAPS@PLDI 2022: 30-39 - 2021
- [c15]Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas:
Leveraging Language to Learn Program Abstractions and Search Heuristics. ICML 2021: 11193-11204 - [c14]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: 835-850 - 2020
- [c13]Yewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum, Armando Solar-Lezama:
Program Synthesis with Pragmatic Communication. NeurIPS 2020 - [c12]Lucas Yanan Tian, Kevin Ellis, Marta Kryven, Josh Tenenbaum:
Learning abstract structure for drawing by efficient motor program induction. NeurIPS 2020 - 2019
- [c11]Marcos Lopez, Terry Griffin, Kevin Ellis, Anthony Enem, Christopher Duhan:
Parking Lot Occupancy Tracking Through Image Processing. CATA 2019: 265-270 - [c10]Catherine Wong, Kevin Ellis, Mathias Sablé-Meyer, Josh Tenenbaum:
Modeling Expertise with Neurally-Guided Bayesian Program Induction. CogSci 2019: 3114 - [c9]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 - [c8]Kevin Ellis, Maxwell I. Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando Solar-Lezama:
Write, Execute, Assess: Program Synthesis with a REPL. NeurIPS 2019: 9165-9174 - 2018
- [c7]Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Josh Tenenbaum:
Learning to Infer Graphics Programs from Hand-Drawn Images. NeurIPS 2018: 6062-6071 - [c6]Kevin Ellis, Lucas Morales, Mathias Sablé-Meyer, Armando Solar-Lezama, Josh Tenenbaum:
Learning Libraries of Subroutines for Neurally-Guided Bayesian Program Induction. NeurIPS 2018: 7816-7826 - 2017
- [c5]Kevin Ellis, Sumit Gulwani:
Learning to Learn Programs from Examples: Going Beyond Program Structure. IJCAI 2017: 1638-1645 - 2016
- [c4]Kevin Ellis, Armando Solar-Lezama, Josh Tenenbaum:
Sampling for Bayesian Program Learning. NIPS 2016: 1289-1297 - 2015
- [c3]Kevin Ellis, Eyal Dechter, Joshua B. Tenenbaum:
Dimensionality Reduction via Program Induction. AAAI Spring Symposia 2015 - [c2]Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum:
Unsupervised Learning by Program Synthesis. NIPS 2015: 973-981 - 2014
- [c1]Dianhuan Lin, Eyal Dechter, Kevin Ellis, Joshua B. Tenenbaum, Stephen H. Muggleton:
Bias reformulation for one-shot function induction. ECAI 2014: 525-530
Informal and Other Publications
- 2024
- [i22]Top Piriyakulkij, Kevin Ellis:
Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning. CoRR abs/2402.06025 (2024) - [i21]Hao Tang, Darren Key, Kevin Ellis:
WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment. CoRR abs/2402.12275 (2024) - [i20]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 abs/2405.17503 (2024) - [i19]Wen-Ding Li, Kevin Ellis:
Is Programming by Example solved by LLMs? CoRR abs/2406.08316 (2024) - 2023
- [i18]Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton:
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. CoRR abs/2306.02049 (2023) - [i17]Kevin Ellis:
Modeling Human-like Concept Learning with Bayesian Inference over Natural Language. CoRR abs/2306.02797 (2023) - [i16]Yichao Liang, Kevin Ellis, João Henriques:
Rapid Motor Adaptation for Robotic Manipulator Arms. CoRR abs/2312.04670 (2023) - [i15]Top Piriyakulkij, Volodymyr Kuleshov, Kevin Ellis:
Active Preference Inference using Language Models and Probabilistic Reasoning. CoRR abs/2312.12009 (2023) - 2022
- [i14]Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton:
CrossBeam: Learning to Search in Bottom-Up Program Synthesis. CoRR abs/2203.10452 (2022) - [i13]Saujas Vaduguru, Kevin Ellis, Yewen Pu:
Efficient Pragmatic Program Synthesis with Informative Specifications. CoRR abs/2204.02495 (2022) - [i12]Hao Tang, Kevin Ellis:
From Perception to Programs: Regularize, Overparameterize, and Amortize. CoRR abs/2206.05922 (2022) - [i11]Darren Key, Wen-Ding Li, Kevin Ellis:
I Speak, You Verify: Toward Trustworthy Neural Program Synthesis. CoRR abs/2210.00848 (2022) - [i10]Matthew Bowers, Theo X. Olausson, Catherine Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama:
Top-Down Synthesis for Library Learning. CoRR abs/2211.16605 (2022) - 2021
- [i9]Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas:
Leveraging Language to Learn Program Abstractions and Search Heuristics. CoRR abs/2106.11053 (2021) - [i8]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 abs/2107.06393 (2021) - [i7]Nathanaël Fijalkow, Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh Potta:
Scaling Neural Program Synthesis with Distribution-based Search. CoRR abs/2110.12485 (2021) - 2020
- [i6]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 abs/2006.08381 (2020) - [i5]Yewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum, Armando Solar-Lezama:
Program Synthesis with Pragmatic Communication. CoRR abs/2007.05060 (2020) - [i4]Lucas Yanan Tian, Kevin Ellis, Marta Kryven, Joshua B. Tenenbaum:
Learning abstract structure for drawing by efficient motor program induction. CoRR abs/2008.03519 (2020) - 2019
- [i3]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 abs/1901.02875 (2019) - [i2]Kevin Ellis, Maxwell I. Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando Solar-Lezama:
Write, Execute, Assess: Program Synthesis with a REPL. CoRR abs/1906.04604 (2019) - 2017
- [i1]Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Joshua B. Tenenbaum:
Learning to Infer Graphics Programs from Hand-Drawn Images. CoRR abs/1707.09627 (2017)
Coauthor Index
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