Publication
Invariant Recognition Shapes Neural Representations of Visual Input. Annual Review of Vision Science 4, 403 - 422 (2018).
annurev-vision-091517-034103.pdf (1.55 MB)
Invariant recognition drives neural representations of action sequences. PLoS Comp. Bio (2017).
Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets. (2017).
CBMM-Memo-062.pdf (9.37 MB)
Invariant recognition drives neural representations of action sequences. PLOS Computational Biology 13, e1005859 (2017).
journal.pcbi_.1005859.pdf (9.24 MB)
Representation Learning from Orbit Sets for One-shot Classification. AAAI Spring Symposium Series, Science of Intelligence (2017). at <https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15357>
Trading robust representations for sample complexity through self-supervised visual experience. Advances in Neural Information Processing Systems 31 () 9640–9650 (Curran Associates, Inc., 2018). at <http://papers.nips.cc/paper/8170-trading-robust-representations-for-sample-complexity-through-self-supervised-visual-experience.pdf>
trading-robust-representations-for-sample-complexity-through-self-supervised-visual-experience.pdf (3.32 MB)
NeurIPS2018_Poster.pdf (6.12 MB)
Invariant representations for action recognition in the visual system. Vision Sciences Society 15, (2015).
Using Multimodal DNNs to Study Vision-Language Integration in the Brain. ICLR 2023 (2023). at <https://openreview.net/pdf?id=OQQ1p0pFP4>
On the Forgetting of College Academics: at "Ebbinghaus Speed"?. (2017).
CBMM Memo 068-On Forgetting - June 18th 2017 v2.pdf (713.7 KB)
Dynamics of random neural networks with bistable units. Phys Rev E Stat Nonlin Soft Matter Phys 90, (2014).
Untangling in Invariant Speech Recognition. Neural Information Processing Systems (NeurIPS 2019) (2019).
9583-untangling-in-invariant-speech-recognition.pdf (2.09 MB)
Marbles in inaction: Counterfactual simulation and causation by omission. Proceedings of the 39th Annual Conference of the Cognitive Science Society (2017).
Marbles in Inaction Counterfactual Simulation and Causation by Omission, Stephan, Willemsen, Gerstenberg, 2017.pdf (1.46 MB)
Evidence for an attentional priority map in inferotemporal cortex. Proceedings of the National Academy of Sciences 116, 23797 - 23805 (2019).
Minimal images in deep neural networks: Fragile Object Recognition in Natural Images. International Conference on Learning Representations (ICLR) (2019). at <https://arxiv.org/pdf/1902.03227.pdf>
Forward learning with top-down feedback: empirical and analytical characterization. arXiv (2023). at <https://arxiv.org/abs/2302.05440>
Infants’ Reasoning about Affiliation and Caregiving. Cognitive Development Society (CDS) | More on Development workshop (2015).
Welfare-tradeoff ratios in children. Human Behavior and Evolution Society (2016).
The cradle of social knowledge: Infants' reasoning about caregiving and affiliation. Cognition 159, 102-116 (2017).
How Infants Reason About Affective States and Social Interactions. International Conference on Infant Studies (ICIS) (2016).
Like Adults, children make consistent welfare tradeoff allocations. Budapest CEU Conference on Cognitive Development (2017).
The Functions of Infants’ Social Categorization: Early Reasoning about Affiliation and Social Networks. International Conference on Infant Studies (ICIS) (2016).
Infants’ Reasoning about Affiliation and Caregiving. Cognitive Development Society (CDS) Biennial Meeting (2015).
Four-year-old children favor kin when the stakes are higher. Cognitive Development Society (CDS) (2017). at <https://cogdevsoc.org/wp-content/uploads/2017/10/CDS2017AbstractBook.pdf>
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