Publication
] What if Eye..? Computationally Recreating Vision Evolution. arXiv (2025). at <https://arxiv.org/abs/2501.15001>
2501.15001v1.pdf (5.2 MB)
2501.15001v1.pdf (5.2 MB) What have we learned about artificial intelligence from studying the brain?. Biological Cybernetics 118, 1 - 5 (2024).
What Babies KnowAbstractCore KnowledgeAbstract. 190 - C5.T1 (Oxford University PressNew York, 2022). doi:10.1093/oso/9780190618247.001.000110.1093/oso/9780190618247.003.0005
What Could Go Wrong: Adults and Children Calibrate Predictions and Explanations of Others' Actions Based on Relative Reward and Danger. Cognitive Science 46, (2022).
When and how convolutional neural networks generalize to out-of-distribution category–viewpoint combinations. Nature Machine Intelligence 4, 146 - 153 (2022).
What Matters In Branch Specialization? Using a Toy Task to Make Predictions. Shared Visual Representations in Human and Machine Intelligence (SVRHM) Workshop at NeurIPS (2021). at <https://openreview.net/forum?id=0kPS1i6wict>
When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. International Conference on Computer Vision (ICCV) (2021). doi:10.1109/iccv48922.2021.00032 Bomatter_When_Pigs_Fly_Contextual_Reasoning_in_Synthetic_and_Natural_Scenes_ICCV_2021_paper.pdf (3.24 MB)
Bomatter_When_Pigs_Fly_Contextual_Reasoning_in_Synthetic_and_Natural_Scenes_ICCV_2021_paper.pdf (3.24 MB) What can human minimal videos tell us about dynamic recognition models?. International Conference on Learning Representations (ICLR 2020) (2020). at <https://baicsworkshop.github.io/pdf/BAICS_1.pdf> Authors' final version (516.09 KB)
Authors' final version (516.09 KB) Why Are Face and Object Processing Segregated in the Human Brain? Testing Computational Hypotheses with Deep Convolutional Neural Networks . Conference on Cognitive Computational Neuroscience (2020).
Psychology of Learning and Motivation 70, (2019).
Write, Execute, Assess: Program Synthesis with a REPL. Neural Information Processing Systems (NeurIPS 2019) (2019). 9116-write-execute-assess-program-synthesis-with-a-repl.pdf (3.9 MB)
9116-write-execute-assess-program-synthesis-with-a-repl.pdf (3.9 MB) What am I searching for?. (2018). CBMM-Memo-096.pdf (1.74 MB)
CBMM-Memo-096.pdf (1.74 MB) What is changing when: decoding visual information in movies from human intracranial recordings. NeuroImage 180, Part A, 147-159 (2018). Human neurophysiological responses during movies (2.78 MB)
Human neurophysiological responses during movies (2.78 MB) What is changing when: Decoding visual information in movies from human intracranial recordings. Neuroimage (2017). doi:https://doi.org/10.1016/j.neuroimage.2017.08.027
When and Why Are Deep Networks Better Than Shallow Ones?. AAAI-17: Thirty-First AAAI Conference on Artificial Intelligence (2017).
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review. International Journal of Automation and Computing 1-17 (2017). doi:10.1007/s11633-017-1054-2 art%3A10.1007%2Fs11633-017-1054-2.pdf (1.68 MB)
art%3A10.1007%2Fs11633-017-1054-2.pdf (1.68 MB) Why does deep and cheap learning work so well?. Journal of Statistical Physics 168, 1223–1247 (2017). 1608.08225.pdf (2.14 MB)
1608.08225.pdf (2.14 MB) Welfare-tradeoff ratios in children. Human Behavior and Evolution Society (2016).
When Does Model-Based Control Pay Off?. PLoS Comput Biol 12, e1005090 (2016). KoolEtAl_PLOS_CB.PDF (5.85 MB)
KoolEtAl_PLOS_CB.PDF (5.85 MB) Where do hypotheses come from?. (2016). CBMM-Memo-056-v2.pdf (733.35 KB)
CBMM-Memo-056-v2.pdf (733.35 KB) What if.. (2015). What if.pdf (2.09 MB)
What if.pdf (2.09 MB) Whole-agent selectivity within the macaque face-processing system. Proceedings of the National Academy of Sciences (PNAS) 112, (2015). Authors' last version of article. (3.1 MB)
Authors' last version of article. (3.1 MB) Mechanisms of Sensory Working Memory: Attention and Performance XXV. (Elsevier Inc. , 2015). at <https://www.sciencedirect.com/book/9780128013717/mechanisms-of-sensory-working-memory>