Yaoda Xu
Affiliations: | Harvard University, Cambridge, MA, United States |
Google:
"Yaoda Xu"Mean distance: 13.04 (cluster 23) | S | N | B | C | P |
Parents
Sign in to add mentor| Mary C. Potter | grad student | MIT | |
| Marvin M. Chun | post-doc | Yale | |
| Ken Nakayama | post-doc | Harvard |
Children
Sign in to add trainee| Su Keun Jeong | grad student | 2009-2014 | Harvard |
| Sonia Poltoratski | research scientist | 2009-2011 | Harvard |
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Publications
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| Xu Y. (2024) The human posterior parietal cortices orthogonalize the representation of different streams of information concurrently coded in visual working memory. Plos Biology. 22: e3002915 |
| Xu Y. (2023) Parietal-driven visual working memory representation in occipito-temporal cortex. Current Biology : Cb |
| Mocz V, Jeong SK, Chun M, et al. (2023) Multiple visual objects are represented differently in the human brain and convolutional neural networks. Scientific Reports. 13: 9088 |
| Mocz V, Jeong SK, Chun M, et al. (2023) Representing Multiple Visual Objects in the Human Brain and Convolutional Neural Networks. Biorxiv : the Preprint Server For Biology |
| Taylor J, Xu Y. (2023) Comparing the Dominance of Color and Form Information across the Human Ventral Visual Pathway and Convolutional Neural Networks. Journal of Cognitive Neuroscience. 35: 816-840 |
| Mocz V, Xu Y. (2023) Decision-making from temporally accumulated conflicting evidence: The more the merrier. Journal of Vision. 23: 3 |
| Xu Y. (2022) Global object shape representations in the primate brain. Trends in Cognitive Sciences |
| Mocz V, Vaziri-Pashkam M, Chun M, et al. (2022) Predicting Identity-Preserving Object Transformations in Human Posterior Parietal Cortex and Convolutional Neural Networks. Journal of Cognitive Neuroscience. 1-30 |
| Xu Y, Vaziri-Pashkam M. (2022) Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks. Neuroimage. 263: 119635 |
| Tang K, Chin M, Chun M, et al. (2022) The contribution of object identity and configuration to scene representation in convolutional neural networks. Plos One. 17: e0270667 |