All Publications
2020
“Beyond the feedforward sweep: feedback computations in the visual cortex”, Ann. N.Y. Acad. Sci. | Special Issue: The Year in Cognitive Neuroscience, vol. 1464, no. 1, pp. 222-241, 2020. gk7812.pdf (1.93 MB) ,
CBMM Funded
“Beyond the feedforward sweep: feedback computations in the visual cortex”, Annals of the New York Academy of Sciences, vol. 1464, no. 1, pp. 222 - 241, 2020. ,
CBMM Funded
“Hierarchical neural network models that more closely match primary visual cortex tend to better explain higher level visual cortical responses ”, in COSYNE, Denver, Colorado, USA, 2020. ,
CBMM Funded
“Complexity Control by Gradient Descent in Deep Networks”, Nature Communications, vol. 11, 2020. s41467-020-14663-9.pdf (431.68 KB) ,
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“Temporal information for action recognition only needs to be integrated at a choice level in neural networks and primates ”, in COSYNE, Denver, CO, USA, 2020. ,
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“Scale and translation-invariance for novel objects in human vision”, Scientific Reports, vol. 10, no. 1411, 2020. s41598-019-57261-6.pdf (1.46 MB) ,
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“Segregation from Noise as Outlier Detection ”, in Association for Research in Otolaryngology, San Jose, CA, USA, 2020. ,
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“Can Deep Learning Recognize Subtle Human Activities?”, CVPR 2020, 2020. ,
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“The ability to predict actions of others from distributed cues is still developing in children”, PsyArXiv Preprints, 2020. Action_prediction_in_children.pdf (427.84 KB) ,
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“An analysis of training and generalization errors in shallow and deep networks”, Neural Networks, vol. 121, pp. 229 - 241, 2020. ,
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“Infants represent 'like-kin' affiliation ”, in Budapest Conference on Cognitive Development, Budapest, Hungary, 2020. ,
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“Putting visual object recognition in context”, CVPR 2020, 2020. gk7876.pdf (3.12 MB) ,
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CBMM Memo No.
125
“Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas”. 2020. CBMM-Memo-125.pdf (2.12 MB) ,
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CBMM Memo No.
124
“Deep compositional robotic planners that follow natural language commands”. 2020. CBMM-Memo-124.pdf (1.03 MB) ,
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“Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas”, in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA, 2020. ,
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CBMM Funded
“The fine structure of surprise in intuitive physics: when, why, and how much?”, in Proceedings of the 42th Annual Meeting of the Cognitive Science Society - Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020, virtual, July 29 - August 1, 2020, 2020. ,
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2019
“How Adults’ Actions, Outcomes, and Testimony Affect Preschoolers’ Persistence”, Child Development, 2019. ,
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“Invariant representations of mass in the human brain”, eLife, vol. 8, 2019. ,
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“Representational similarity precedes category selectivity in the developing ventral visual pathway”, NeuroImage, vol. 197, pp. 565 - 574, 2019. ,
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“Eye movements and retinotopic tuning in developmental prosopagnosia”, Journal of Vision, vol. 19, no. 9, p. 7, 2019. ,
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“Large-scale hyperparameter search for predicting human brain responses in the Algonauts challenge”, in The Algonauts Project: Explaining the Human Visual Brain Workshop 2019 , MIT, Cambridge MA, 2019. ,
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CBMM Memo No.
102
“Double descent in the condition number”. 2019. Fixing typos, clarifying error in y, best approach is crossvalidation (837.18 KB) Incorporated footnote in text plus other edits (854.05 KB) Deleted previous discussion on kernel regression and deep nets: it will appear, extended, in a separate paper (795.28 KB) correcting a bad typo (261.24 KB) Deleted plot of condition number of kernel matrix: we cannot get a double descent curve (769.32 KB) ,
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“Deep Compositional Robotic Planners that Follow Natural Language Commands.”, Workshop on Visually Grounded Interaction and Language (ViGIL) at the Thirty-third Annual Conference on Neural Information Processing Systems (NeurIPS). Vancouver Convention Centre, Vancouver, Canada, 2019. ,
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“Ecological origins of perceptual grouping principles in the auditory system”, Proceedings of the National Academy of Sciences, vol. 116, no. 50, pp. 25355 - 25364, 2019. ,
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