Publications
Lab publications by year: Preprints, 2021, 2020, 2019, 2018, 2017, and earlier.
Preprints
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Gandhi, K., Stojnic, G., Lake, B. M. and Dillon, M. R. (2021). Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others. Preprint available on arXiv:2102.11938.
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Vedantam, R., Szlam, A., Nickel M., Morcos, A., and Lake, B. M. (2020). CURI: A Benchmark for Productive Concept Learning Under Uncertainty. Preprint available on arXiv:2010.02855.
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Vong, W. K. and Lake, B. M. (2020). Learning word-referent mappings and concepts from raw inputs. Preprint available on arXiv:2003.05573.
2021
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Davidson, G. and Lake, B. M. (2021). Examining Infant Relation Categorization Through Deep Neural Networks. In Proceedings of the 43rd Annual Conference of the Cognitive Science Society.
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Johnson, A., Vong, W. K., Lake, B. M. and Gureckis, T. M. (2021). Fast and flexible: Human program induction in abstract reasoning tasks. In Proceedings of the 43rd Annual Conference of the Cognitive Science Society.
- Wang, Z. and Lake, B. M. (2019). Modeling question asking using neural program generation. In Proceedings of the 43rd Annual Conference of the Cognitive Science Society.
- Press: Knowable Magazine
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Lake, B. M. and Murphy, G. L. (in press). Word meaning in minds and machines. Psychological Review.
- Feinman, R. and Lake, B. M. (2021). Learning Task-General Representations with Generative Neuro-Symbolic Modeling. International Conference on Learning Representations (ICLR).
2020
- Orhan, A. E., Gupta, V. B., and Lake, B. M. (2020). Self-supervised learning through the eyes of a child. Advances in Neural Information Processing Systems 33.
[Supporting Info.]
[Code and pre-trained models]
- Press: New Scientist
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Ruis, L., Andreas, J., Baroni, M. Bouchacourt, D., and Lake, B. M. (2020). A Benchmark for Systematic Generalization in Grounded Language Understanding. Advances in Neural Information Processing Systems 33. [Supporting Info.] [Benchmark] [Baseline model]
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Nye, M., Solar-Lezama, A., Tenenbaum, J. B., and Lake, B. M. (2020). Learning Compositional Rules via Neural Program Synthesis. Advances in Neural Information Processing Systems 33. [Supporting Info.] [Code]
- Gandhi, K. and Lake, B. M. (2020). Mutual exclusivity as a challenge for deep neural networks. Advances in Neural Information Processing Systems 33.
[Supporting Info.]
- Press: New Scientist
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Feinman, R. and Lake, B. M. (2020). Generating new concepts with hybrid neuro-symbolic models. In Proceedings of the 42nd Annual Conference of the Cognitive Science Society. [Short video] [Supporting Info.]
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Davidson, G. and Lake, B. M. (2020). Investigating simple object representations in model-free deep reinforcement learning. In Proceedings of the 42nd Annual Conference of the Cognitive Science Society. [Short video]
- Lake, B. M. and Piantadosi, S. T. (2020). People infer recursive visual concepts from just a few examples. Computational Brain & Behavior, 3(1), 54-65. [Supporting Info.] [Experiments]
2019
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Lake, B. M. (2019). Compositional generalization through meta sequence-to-sequence learning. Advances in Neural Information Processing Systems 32. [Code]
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Lake, B. M., Salakhutdinov, R., and Tenenbaum, J. B. (2019). The Omniglot challenge: a 3-year progress report. Current Opinion in Behavioral Sciences, 29, 97-104.
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Feinman, R. and Lake, B. M. (2019). Learning a smooth kernel regularizer for convolutional neural networks. In Proceedings of the 41st Annual Conference of the Cognitive Science Society.
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Lake, B. M., Linzen, T., and Baroni, M. (2019). Human few-shot learning of compositional instructions. In Proceedings of the 41st Annual Conference of the Cognitive Science Society.
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Rothe, A., Lake, B. M., and Gureckis, T. M. (2019). Asking goal-oriented questions and learning from answers. In Proceedings of the 41st Annual Conference of the Cognitive Science Society.
2018
- Rothe, A., Lake, B. M., and Gureckis, T. M. (2018). Do people ask good questions? Computational Brain & Behavior, 1(1), 69-89.
- Outstanding paper award.
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Loula, J., Baroni, M., and Lake, B. M. (2018). Rearranging the familiar: Testing compositional generalization in recurrent networks. In Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP.
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Lake, B. M. and Baroni, M. (2018). Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks. International Conference on Machine Learning (ICML). [Supporting Info.] [Data set]
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Feinman, R. and Lake, B. M. (2018). Learning inductive biases with simple neural networks. In Proceedings of the 40th Annual Conference of the Cognitive Science Society.
- Lake, B. M., Lawrence, N. D., and Tenenbaum, J. B. (2018). The emergence of organizing structure in conceptual representation. Cognitive Science, 42(S3), 809-832. [Supporting Info.] [Code]
2017
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Lake, B. M., Ullman, T. D., Tenenbaum, J. B., and Gershman, S. J. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences, 40, E253.
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Rothe, A., Lake, B. M., and Gureckis, T. M. (2017). Question asking as program generation. Advances in Neural Information Processing Systems 30. [Supporting Info.]
- Press: MIT Technology Review
Selected earlier papers
- Lake, B. M., Salakhutdinov, R., and Tenenbaum, J. B. (2015). Human-level concept learning through probabilistic program induction. Science, 350(6266), 1332-1338. [Supporting Info.] [visual Turing tests] [Omniglot data set] [Bayesian Program Learning code]
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Lake, B. M., Zaremba, W., Fergus, R. and Gureckis, T. M. (2015). Deep Neural Networks Predict Category Typicality Ratings for Images. In Proceedings of the 37th Annual Conference of the Cognitive Science Society. [Data]
- Lake, B. M., Lee, C.-y., Glass, J. R., and Tenenbaum, J. B. (2014). One-shot learning of generative speech concepts. In Proceedings of the 36th Annual Conference of the Cognitive Science Society. [Supporting Info.]