Publication
On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering. arXiv (2022). doi:10.48550/arXiv.2201.03965
On_the_Efficacy_of_Co-Attention_Transformer_Layers.pdf (35.54 MB)
Short temporal asynchrony disrupts visual object recognition. (2014). at <http://klab.tch.harvard.edu/resources/singer_asynchrony.html>
Sensitivity to Timing and Order in Human Visual Cortex. (2014).
CBMM-Memo-005.pdf (1.12 MB)
Sensitivity to timing and order in human visual cortex. Journal of Neurophysiology 113, 1656 - 1669 (2015).
Short temporal asynchrony disrupts visual object recognition. (2014). at <http://klab.tch.harvard.edu/resources/singer_asynchrony.html>
Learning to Learn: How to Continuously Teach Humans and Machines . International Conference on Computer Vision (ICCV), 2023 (2023). at <https://openaccess.thecvf.com/content/ICCV2023/html/Singh_Learning_to_Learn_How_to_Continuously_Teach_Humans_and_Machines_ICCV_2023_paper.html>
Comparing human and monkey neural circuits for processing social scenes. Social & Affective Neuroscience Society (SANS) (2018). at <http://www.socialaffectiveneuro.org/conferences.html>
Comparing human and monkey neural circuits for processing social scenes. Cognitive Neuroscience Society Annual Meeting (CNS), Boston, MA (2018).
From agents to actions to interactions: Uncovering multiple social networks in the primate brain. Society for Social and Affective Neuroscience (2017).
A Dedicated Network for Social Interaction Processing in the Primate Brain. Science Vol. 356, pp. 745-749 (2017).
A Network for Social interaction understanding in the primate brain. Organization for Human Brain Mapping - OHBM 2017 (2017).
Comparing human and monkey neural circuits for processing social scenes. Société Francophone de Primatologie (SFDP) Annual Meeting, Paris, France (2018).
From agents to actions to interactions: Uncovering multiple social networks in the primate brain. Society for Neuroscience (2016).
SFN2016.pdf (555.77 KB)
Comparing human and monkey neural circuits for processing social scenes. Society for Neuroscience's Annual Meeting - SfN 2017 (2017).
Comparing human and monkey neural circuits for processing social scenes. Organization for Computational Neurosciences - CNS 2018 (2018). at <http://www.cnsorg.org/cns-2018>
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) (2019). at <http: //physadept.csail.mit.edu/>
ADEPT_NeurIPS.pdf (11.07 MB)
The fine structure of surprise in intuitive physics: when, why, and how much?. 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). at <https://cogsci.mindmodeling.org/2020/papers/0761/index.html>
Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017). doi:10.1109/CVPR.2017.269
Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks.pdf (2.86 MB)
Moral dynamics: Grounding moral judgment in intuitive physics and intuitive psychology. Cognition 217, 104890 (2021).
Scientists Making a Difference: One Hundred Eminent Behavioral and Brain Scientists Talk about Their Most Important Contributions (Cambridge University Press, 2016).
What Babies KnowAbstractCore KnowledgeAbstract. 190 - C5.T1 (Oxford University PressNew York, 2022). doi:10.1093/oso/9780190618247.001.000110.1093/oso/9780190618247.003.0005
Core Knowledge and Conceptual Change (Oxford University Press, 2016).
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