Publication

Found 912 results
Author [ Title(Asc)] Type Year
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E
Yildirim, I., Kulkarni, T., Freiwald, W. A. & Tenenbaum, J. B. Efficient and robust analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations. Annual Conference of the Cognitive Science Society (2015).PDF icon yildirimetal_cogsci15.pdf (3.22 MB)
Sikarwar, A. & Kreiman, G. On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering. arXiv (2022). doi:10.48550/arXiv.2201.03965PDF icon On_the_Efficacy_of_Co-Attention_Transformer_Layers.pdf (35.54 MB)
Kunhardt, O., Deza, A. & Poggio, T. The Effects of Image Distribution and Task on Adversarial Robustness. (2021).PDF icon CBMM_Memo_116.pdf (5.44 MB)
Dobs, K. et al. Effects of Face Familiarity in Humans and Deep Neural Networks . European Conference on Visual Perception (2019).
N. Murty, A. Ratan & Arun, S. P. Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex. Journal of Neurophysiology 11823, 353 - 362 (2017).
Azami, H. et al. EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer’s Disease. Journal of Alzheimer's Disease 91, 1557 - 1572 (2023).
Młynarski, W. & McDermott, J. H. Ecological origins of perceptual grouping principles in the auditory system. Proceedings of the National Academy of Sciences 116, 25355 - 25364 (2019).
Zhang, J., Han, Y., Poggio, T. & Roig, G. Eccentricity Dependent Neural Network with Recurrent Attention for Scale, Translation and Clutter Invariance . Vision Science Society (2019).
Chen, F., Roig, G., Isik, L., Boix, X. & Poggio, T. Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision. AAAI Spring Symposium Series, Science of Intelligence (2017). at <https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15360>PDF icon paper.pdf (963.87 KB)
Roig, G., Chen, F., Boix, X. & Poggio, T. Eccentricity Dependent Deep Neural Networks for Modeling Human Vision. Vision Sciences Society (2017).
Spokes, A. C. & Spelke, E. S. Early Reasoning about Affiliation and Social Networks. International Conference on Infant Studies (ICIS) (2016).
Spokes, A. C. & Spelke, E. S. Early reasoning about affiliation and kinship. (2015).
Spokes, A. C. & Spelke, E. S. Early Reasoning about Affiliation and Caregiving. Cognitive Development Society (CDS) (2015).
Thomas, A. J., Woo, B., Nettle, D., Spelke, E. S. & Saxe, R. Early concepts of intimacy: Young humans use saliva sharing to infer close relationships. Science 375, 311 - 315 (2022).
D
Stern, M., Sompolinsky, H. & Abbott, L. F. Dynamics of random neural networks with bistable units. Phys Rev E Stat Nonlin Soft Matter Phys 90, (2014).
Isik, L., Meyers, E., Leibo, J. Z. & Poggio, T. The dynamics of invariant object recognition in the human visual system. J Neurophysiol 111, 91-102 (2014).
Isik, L., Meyers, E., Leibo, J. Z. & Poggio, T. The dynamics of invariant object recognition in the human visual system. (2014). doi:http://dx.doi.org/10.7910/DVN/KRUPXZ
N. Murty, A. Ratan & Arun, S. P. Dynamics of 3D view invariance in monkey inferotemporal cortex. Journal of Neurophysiology 11319212373232821, 2180 - 2194 (2015).
Xu, M., Rangamani, A., Liao, Q., Galanti, T. & Poggio, T. Dynamics in Deep Classifiers trained with the Square Loss: normalization, low rank, neural collapse and generalization bounds. Research (2023). doi:10.34133/research.0024PDF icon research.0024.pdf (4.05 MB)
Banburski, A. et al. Dynamics & Generalization in Deep Networks -Minimizing the Norm. NAS Sackler Colloquium on Science of Deep Learning (2019).
Xu, M. et al. Dynamics and Neural Collapse in Deep Classifiers trained with the Square Loss. (2021).PDF icon v1.0 (4.61 MB)PDF icon v1.4corrections to generalization section (5.85 MB)PDF icon v1.7Small edits (22.65 MB)
Meyers, E. Dynamic population coding and its relationship to working memory. Journal of Neurophysiology 120, 2260 - 2268 (2018).
Dehghani, N. Dynamic balance of excitation and inhibition in human and monkey neocortex. Nature Scientific Reports (2016). doi:10.1038/srep23176PDF icon BalanceExcitationInhibition.pdf (2.1 MB)
Banburski, A. et al. Dreaming with ARC. Learning Meets Combinatorial Algorithms workshop at NeurIPS 2020 (2020).PDF icon CBMM Memo 113.pdf (1019.64 KB)
Ullman, T. D. et al. Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects. Cognitive Science Society (2019). at <https://mindmodeling.org/cogsci2019/papers/0506/index.html>PDF icon Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects.pdf (2.62 MB)

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