| 2025 | CogSci | Goal Inference using Reward-Producing Programs in a Novel Physics Environment. | Guy Davidson, Graham Todd, Cdric Colas, Junyi Chu, Julian Togelius, Joshua B. Tenenbaum, Todd M. Gureckis, Brenden M. Lake |
| 2025 | CogSci | Do Large Language Models Reason Causally Like Us? Even Better? | Hanna M. Dettki, Brenden M. Lake, Charley M. Wu, Bob Rehder |
| 2025 | CogSci | A Neurosymbolic Model of Human Reasoning on the Abstraction and Reasoning Corpus. | Solim LeGris, Brenden M. Lake, Todd M. Gureckis |
| 2025 | EMNLP | Rapid Word Learning Through Meta In-Context Learning. | Wentao Wang, Guangyuan Jiang, Tal Linzen, Brenden M. Lake |
| 2024 | CogSci | Comparing Abstraction in Humans and Machines Using Multimodal Serial Reproduction. | Sreejan Kumar, Raja Marjieh, Byron Zhang, Declan Campbell, Michael Y. Hu, Umang Bhatt, Brenden M. Lake, Tom Griffiths |
| 2024 | CogSci | Predicting Insight during Physical Reasoning. | Solim LeGris, Brenden M. Lake, Todd M. Gureckis |
| 2024 | CogSci | Prompting invokes expert-like downward shifts in GPT-4V's conceptual hierarchies. | Cara Su-Yi Leong, Brenden M. Lake |
| 2024 | CogSci | An Infant-Cognition Inspired Machine Benchmark for Identifying Agency, Affiliation, Belief, and Intention. | Wenjie Li, Shannon C. Yasuda, Moira R. Dillon, Brenden M. Lake |
| 2024 | CogSci | Finding Unsupervised Alignment of Conceptual Systems in Image-Word Representations. | Kexin Luo, Bei Zhang, Yajie Xiao, Brenden M. Lake |
| 2024 | CogSci | Self-supervised learning of video representations from a child's perspective. | A. Emin Orhan, Wentao Wang, Alex N. Wang, Mengye Ren, Brenden M. Lake |
| 2024 | CogSci | A systematic investigation of learnability from single child linguistic input. | Yulu Qin, Wentao Wang, Brenden M. Lake |
| 2024 | CogSci | Is Deep Learning the Answer for Understanding Human Cognitive Dynamics? | John P. Spencer, Brenden M. Lake, Raul Grieben, Gregor Schner, Mariya Toneva, Gina R. Kuperberg |
| 2024 | CogSci | Compositional learning of functions in humans and machines. | Yanli Zhou, Brenden M. Lake, Adina Williams |
| 2022 | CogSci | Creativity, Compositionality, and Common Sense in Human Goal Generation. | Guy Davidson, Todd M. Gureckis, Brenden M. Lake |
| 2022 | CogSci | Evaluating locality in NMT models. | Itay Itzhak, Koustuv Sinha, Brenden M. Lake, Adina Williams, Dieuwke Hupkes |
| 2022 | CogSci | Improving Systematic Generalization Through Modularity and Augmentation. | Laura Ruis, Brenden M. Lake |
| 2022 | CogSci | A Developmentally-Inspired Examination of Shape versus Texture Bias in Machines. | Alexa R. Tartaglini, Wai Keen Vong, Brenden M. Lake |
| 2022 | CogSci | Categorising images by generating natural language rules. | Wai Keen Vong, Brenden M. Lake |
| 2021 | CogSci | Examining Infant Relation Categorization Through Deep Neural Networks. | Guy Davidson, Brenden M. Lake |
| 2021 | CogSci | Fast and Flexible: Human program induction in abstract reasoning tasks. | Aysja Johnson, Wai Keen Vong, Brenden M. Lake, Todd M. Gureckis |
| 2021 | CogSci | The Omniglot Jr. challenge; Can a model achieve child-level character generation and classification? | Eliza Kosoy, Masha Belyi, Charlie Snell, Brenden M. Lake, Josh Tenenbaum, Alison Gopnik |
| 2021 | CogSci | Evaluating infants' reasoning about agents using the Baby Intuitions Benchmark (BIB). | Gala Stojnic, Kanishk Gandhi, Brenden M. Lake, Moira R. Dillon |
| 2021 | CogSci | Modeling artificial category learning from pixels: Revisiting Shepard, Hovland, and Jenkins (1961) with deep neural networks. | Alexa R. Tartaglini, Wai Keen Vong, Brenden M. Lake |
| 2021 | CogSci | Modeling Question Asking Using Neural Program Generation. | Ziyun Wang, Brenden M. Lake |
| 2021 | ICLR | Learning Task-General Representations with Generative Neuro-Symbolic Modeling. | Reuben Feinman, Brenden M. Lake |
| 2021 | ICML | CURI: A Benchmark for Productive Concept Learning Under Uncertainty. | Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel, Ari Morcos, Brenden M. Lake |
| 2020 | CogSci | Investigating Simple Object Representations in Model-Free Deep Reinforcement Learning. | Guy Davidson, Brenden M. Lake |
| 2020 | CogSci | Generating new concepts with hybrid neuro-symbolic models. | Reuben Feinman, Brenden M. Lake |
| 2020 | CogSci | Extending the Rogers and McClelland Model of Semantic Cognition (2003) to work with Raw Pixel Information. | Arihant Jain, Brenden M. Lake, Todd M. Gureckis |
| 2020 | CogSci | Learning word-referent mappings and concepts from raw inputs. | Wai Keen Vong, Brenden M. Lake |
| 2019 | CogSci | Learning a smooth kernel regularizer for convolutional neural networks. | Reuben Feinman, Brenden M. Lake |
| 2019 | CogSci | Human few-shot learning of compositional instructions. | Brenden M. Lake, Tal Linzen, Marco Baroni |
| 2019 | CogSci | Asking goal-oriented questions and learning from answers. | Anselm Rothe, Brenden M. Lake, Todd M. Gureckis |
| 2018 | CogSci | Learning Inductive Biases with Simple Neural Networks. | Reuben Feinman, Brenden M. Lake |
| 2018 | EMNLP | Rearranging the Familiar: Testing Compositional Generalization in Recurrent Networks. | Joo Loula, Marco Baroni, Brenden M. Lake |
| 2018 | ICML | Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks. | Brenden M. Lake, Marco Baroni |
| 2017 | CogSci | One-shot Learning and Classification in Children. | Eliza Kosoy, Brenden M. Lake, Josh Tenenbaum |
| 2017 | CogSci | Progress in building a machine that can ask interesting and informative questions. | Anselm Rothe, Brenden M. Lake, Todd M. Gureckis |
| 2016 | CogSci | Searching large hypothesis spaces by asking questions. | Alexander Cohen, Brenden M. Lake |
| 2016 | CogSci | Asking and evaluating natural language questions. | Anselm Rothe, Brenden M. Lake, Todd M. Gureckis |
| 2015 | CogSci | Deep Neural Networks Predict Category Typicality Ratings for Images. | Brenden M. Lake, Wojciech Zaremba, Rob Fergus, Todd M. Gureckis |
| 2015 | CogSci | Asking useful questions: Active learning with rich queries. | Anselm Rothe, Brenden M. Lake, Todd M. Gureckis |
| 2014 | CogSci | Adaptive teaching: Improving the efficiency of learning through hypothesis-dependent selection of training data. | Patricia Angie Chan, Douglas Markant, Brenden M. Lake, Todd M. Gureckis |
| 2014 | CogSci | One-shot learning of generative speech concepts. | Brenden M. Lake, Chia-ying Lee, James R. Glass, Joshua B. Tenenbaum |
| 2014 | CogSci | Computational Creativity: Generating new objects with a hierarchical Bayesian model. | Brenden M. Lake, Josh Tenenbaum |
| 2012 | CogSci | Concept learning as motor program induction: A large-scale empirical study. | Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum |
| 2011 | CogSci | Estimating the strength of unlabeled information during semi-supervised learning. | Brenden M. Lake, James L. McClelland |
| 2011 | CogSci | One shot learning of simple visual concepts. | Brenden M. Lake, Ruslan Salakhutdinov, Jason Gross, Joshua B. Tenenbaum |