Research
Probabilistic Reasoning
Natural Language
Computational Modeling, Computer Model, Computational Models, Computational Model, Computer Models, Computer Modeling, Computation Modeling, Computer Modelling
Neural Program
List of Publications (54)
In 2024
54
Human-like few-shot learning via bayesian reasoning over natural language. K Ellis Advances in Neural Information Processing Systems 36, 2024.
Found on Publication Page
53
WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment. H Tang, D Key, K Ellis arXiv preprint arXiv:2402.12275, 2024.
Found on Publication Page
52
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. K Shi, H Dai, WD Li, K Ellis, C Sutton Advances in Neural Information Processing Systems 36, 2024.
Found on Publication Page
51
Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning. T Piriyakulkij, K Ellis arXiv preprint arXiv:2402.06025, 2024.
Found on Publication Page
In 2023
50
Dreamcoder: growing generalizable, interpretable knowledge with wake-sleep bayesian program learning. K Ellis, L Wong, M Nye, M Sable-Meyer, L Cary, L Anaya Pozo, L Hewitt, ... Philosophical Transactions of the Royal Society A 381 (2251), 20220050, 2023.
Found on Publication Page
49
Decomposing Quantum Unitaries into Circuits with Program Synthesis. L Sarra, F Marquardt, K Ellis APS March Meeting Abstracts 2023, B47. 009, 2023.
Found on Publication Page
48
Top-down synthesis for library learning. M Bowers, TX Olausson, L Wong, G Grand, JB Tenenbaum, K Ellis, ... Proceedings of the ACM on Programming Languages 7 (POPL), 1182-1213, 2023.
Found on Publication Page
47
From perception to programs: regularize, overparameterize, and amortize. H Tang, K Ellis International Conference on Machine Learning, 33616-33631, 2023.
Found on Publication Page
46
Active Preference Inference using Language Models and Probabilistic Reasoning. T Piriyakulkij, V Kuleshov, K Ellis arXiv preprint arXiv:2312.12009, 2023.
Found on Publication Page
45
Rapid Motor Adaptation for Robotic Manipulator Arms. Y Liang, K Ellis, J Henriques arXiv preprint arXiv:2312.04670, 2023.
Found on Publication Page
44
Discovering quantum circuit components with program synthesis. L Sarra, K Ellis, F Marquardt Machine Learning: Science and Technology, 2023.
Found on Publication Page
In 2022
43
Toward trustworthy neural program synthesis. D Key, WD Li, K Ellis arXiv preprint arXiv:2210.00848, 2022.
Found on Publication Page
42
A language of thought for the mental representation of geometric shapes. M Sable -Meyer, K Ellis, J Tenenbaum, S Dehaene Cognitive Psychology 139, 101527, 2022.
Found on Publication Page
41
Synthesizing theories of human language with Bayesian program induction. K Ellis, A Albright, A Solar-Lezama, JB Tenenbaum, TJ O'Donnell Nature communications 13 (1), 5024, 2022.
Found on Publication Page
40
CrossBeam: Learning to search in bottom-up program synthesis. K Shi, H Dai, K Ellis, C Sutton arXiv preprint arXiv:2203.10452, 2022.
Found on Publication Page
39
Scaling neural program synthesis with distribution-based search. N Fijalkow, G Lagarde, T Matricon, K Ellis, P Ohlmann, AN Potta Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6623-6630, 2022.
Found on Publication Page
38
DeepSynth: Scaling Neural Program Synthesis with Distribution-based Search. T Matricon, N Fijalkow, G Lagarde, K Ellis Journal of Open Source Software 7 (78), 4151, 2022.
Found on Publication Page
37
Efficient Pragmatic Program Synthesis with Informative Specifications. S Vaduguru, K Ellis, Y Pu arXiv preprint arXiv:2204.02495, 2022.
Found on Publication Page
In 2021
36
Leveraging language to learn program abstractions and search heuristics. C Wong, KM Ellis, J Tenenbaum, J Andreas International conference on machine learning, 11193-11204, 2021.
Found on Publication Page
35
Dreamcoder: Bootstrapping inductive program synthesis with wake-sleep library learning. K Ellis, C Wong, M Nye, M Sable -Meyer, L Morales, L Hewitt, L Cary, ... Proceedings of the 42nd acm sigplan international conference on programming ..., 2021.
Found on Publication Page
34
Neurosymbolic programming. S Chaudhuri, K Ellis, O Polozov, R Singh, A Solar-Lezama, Y Yue Foundations and Trends in Programming Languages 7 (3), 158-243, 2021.
Found on Publication Page
33
Making sense of raw input. R Evans, M Bos njak, L Buesing, K Ellis, D Pfau, P Kohli, M Sergot Artificial Intelligence 299, 103521, 2021.
Found on Publication Page
32
Hybrid memoised wake-sleep: approximate inference at the discrete-continuous interface. TA Le, KM Collins, L Hewitt, K Ellis, N Siddharth, SJ Gershman, ... arXiv preprint arXiv:2107.06393, 2021.
Found on Publication Page
In 2020
31
Learning abstract structure for drawing by efficient motor program induction. L Tian, K Ellis, M Kryven, J Tenenbaum Advances in Neural Information Processing Systems 33, 2686-2697, 2020.
Found on Publication Page
30
Program synthesis with pragmatic communication. Y Pu, K Ellis, M Kryven, J Tenenbaum, A Solar-Lezama Advances in Neural Information Processing Systems 33, 13249-13259, 2020.
Found on Publication Page
29
Five ways in which computational modeling can help advance cognitive science: Lessons from artificial grammar learning. W Zuidema, RM French, RG Alhama, K Ellis, TJ O'Donnell, T Sainburg, ... Topics in cognitive science 12 (3), 925-941, 2020.
Found on Publication Page
27
Record profiling for dataset sampling. DG Simmons, KDJ Grealish, S Gulwani, R Kumar, KM Ellis, S Padhi US Patent 10,846,298, 2020.
Found on Publication Page
26
Algorithms for learning to induce programs. K Ellis Massachusetts Institute of Technology, 2020.
Found on Publication Page
In 2019
25
Learning to infer and execute 3d shape programs. Y Tian, A Luo, X Sun, K Ellis, WT Freeman, JB Tenenbaum, J Wu arXiv preprint arXiv:1901.02875, 2019.
Found on Publication Page
24
Write, execute, assess: Program synthesis with a repl. K Ellis, M Nye, Y Pu, F Sosa, J Tenenbaum, A Solar-Lezama Advances in Neural Information Processing Systems 32, 2019.
Found on Publication Page
23
Five ways in which computational models can help advancing Artificial Grammar Learning research. WH Zuidema, R French, RG Alhama, K Ellis, T O'Donell, T Sainburgh, ... Topics in Cognitive Science, 2019.
Found on Publication Page
22
Modeling Expertise with Neurally-Guided Bayesian Program Induction. C Wong, K Ellis, M Sable -Meyer, J Tenenbaum CogSci, 3114, 2019.
Found on Publication Page
In 2018
21
Learning to infer graphics programs from hand-drawn images. K Ellis, D Ritchie, A Solar-Lezama, J Tenenbaum Advances in neural information processing systems 31, 2018.
Found on Publication Page
20
Learning libraries of subroutines for neurally-guided bayesian program induction. K Ellis, L Morales, M Sable -Meyer, A Solar-Lezama, J Tenenbaum Advances in Neural Information Processing Systems 31, 2018.
Found on Publication Page
In 2017
19
Learning to Learn Programs from Examples: Going Beyond Program Structure. K Ellis, S Gulwani IJCAI, 1638-1645, 2017.
Found on Publication Page
In 2016
18
Sampling for bayesian program learning. K Ellis, A Solar-Lezama, J Tenenbaum Advances in Neural Information Processing Systems 29, 2016.
Found on Publication Page
17
5 Discussion groups 5.1 Neuro-symbolic integration. R Evans, E Bingham, EL Mencia, H Ruess, J Rabold, K Ellis, U Schmid Approaches and Applications of Inductive Programming 107 (7), 83, 2016.
Found on Publication Page
16
5.2 Language primitive bias engineering for generality. US San Francisco, L Contreras-Ochando, A Cropper, K Ellis, T Kliegr, ... Approaches and Applications of Inductive Programming 107 (7), 84, 2016.
Found on Publication Page
In 2015
15
Unsupervised learning by program synthesis. K Ellis, A Solar-Lezama, J Tenenbaum Advances in neural information processing systems 28, 2015.
Found on Publication Page
14
Dimensionality reduction via program induction. K Ellis, E Dechter, JB Tenenbaum 2015 AAAI Spring Symposium Series, 2015.
Found on Publication Page
In 2014
13
Bias reformulation for one-shot function induction. D Lin, E Dechter, K Ellis, JB Tenenbaum, SH Muggleton IOS Press, 2014.
Found on Publication Page
In 2013
12
Learning graphical concepts. K Ellis, E Dechter, RP Adams, JB Tenenbaum NIPS Workshop on Constructive Machine Learning 2, 2013.
Found on Publication Page
In 2012
In 2011
9
System and method for providing an improved graphical user interface for search. K Ellis, C Wodtke, J Crakow, Q Lu US Patent 7,908,289, 2011.
Found on Publication Page
In 2009
Unspecified
7
Wang, l., Hao. S Tang A.: A Method for Terrain Rendering without Seams Based on Image. In: 2007 ..., 0.
Found on Publication Page
6
Supplement to: Learning abstract structure for drawing by efficient motor program induction. LY Tian, K Ellis, M Kryven, JB Tenenbaum .
Found on Publication Page
5
Supplement to: Library Learning for Neurally-Guided Bayesian Program Induction. K Ellis, L Morales, M Sable -Meyer, ENS Paris-Saclay, A Solar-Lezama, ... .
Found on Publication Page
4
Leveraging Language for Abstraction and Program Search. C Wong, K Ellis, J Andreas, JB Tenenbaum .
Found on Publication Page
3
Learning abstract structure in drawings by motor-efficient program induction. LY Tian, K Ellis, M Kryven, JB Tenenbaum .
Found on Publication Page
1
Supplement to: Learning to Infer Graphics Programs from Hand-Drawn Images. K Ellis, D Ritchie, A Solar-Lezama, JB Tenenbaum .
Found on Publication Page
