Publication

Found 22 results
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2023
Rando, M., Molinari, C., Villa, S. & Rosasco, L. An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization. 37th Conference on Neural Information Processing Systems (NeurIPS 2023) (2023). at <https://proceedings.neurips.cc/paper_files/paper/2023/file/7429f4c1b267cf619f28c4d4f1532f99-Paper-Conference.pdf>
Xiao, W., Sharma, S., Kreiman, G. & Livingstone, M. S. Out of sight, out of mind: Responses in primate ventral visual cortex track individual fixations during natural vision. bioRxiv (2023). doi:10.1101/2023.02.08.527666
2022
Casper, S., Nadeau, M. & Kreiman, G. One thing to fool them all: generating interpretable, universal, and physically-realizable adversarial features. arXiv (2022). doi:10.48550/arXiv.2110.03605PDF icon 2110.03605.pdf (6.7 MB)
2020
Sheskin, M. et al. Online Developmental Science to Foster Innovation, Access, and Impact. Trends in Cognitive Sciences 24, 675 - 678 (2020).
Gershman, S. J. Origin of perseveration in the trade-off between reward and complexity. Cognition 204, 104394 (2020).
Poggio, T. & Banburski, A. An Overview of Some Issues in the Theory of Deep Networks. IEEJ Transactions on Electrical and Electronic Engineering 15, 1560 - 1571 (2020).
2019
Barbu, A. et al. ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models. Neural Information Processing Systems (NeurIPS 2019) (2019).PDF icon 9142-objectnet-a-large-scale-bias-controlled-dataset-for-pushing-the-limits-of-object-recognition-models.pdf (16.31 MB)
Brewer, K., Mittman, B., Kominsky, J. & Henes, J. Open Source Subject Database Project (OSSDP). (2019).
Liu, S., Brooks, N. B. & Spelke, E. S. Origins of the concepts cause, cost, and goal in prereaching infants. Cognitive Development Society (2019).PDF icon liu_etal_lumi_cds2019_final.pdf (22.95 MB)
Liu, S., Brooks, N. B. & Spelke, E. S. Origins of the concepts cause, cost, and goal in prereaching infants. PNAS (2019). doi:https://doi.org/10.1073/pnas.1904410116PDF icon Author's last draft (2.58 MB)
2017
Liao, Q. & Poggio, T. Object-Oriented Deep Learning. (2017).PDF icon CBMM-Memo-070.pdf (963.54 KB)
Wu, Y., Muentener, P. & Schulz, L. One- to Four-year-olds’ Ability to Connect Diverse Positive Emotional Expressions to Their Probable Causes . Society for Research in Child Development (2017).
Online learning of symbolic concepts. (2017).
Deen, B. et al. Organization of high-level visual cortex in human infants. Nature Communications (2017). doi:10.1038/ncomms13995
Penagos, H., Varela, C. & Wilson, M. A. Oscillations, neural computations and learning during wake and sleep. Current Opinion in Neurobiology 44C, (2017).
2016
Lewis, O. & Poggio, T. From Neuron to Cognition via Computational Neuroscience (The MIT Press, 2016). at <https://mitpress.mit.edu/neuron-cognition>
Kamps, F. S., Julian, J. B., Kubilius, J., Kanwisher, N. & Dilks, D. D. The occipital place area represents the local elements of scenes. NeuroImage 132, 417 - 424 (2016).
2015
Wong, A. & Yuille, A. One Shot Learning by Composition of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).PDF icon AlexWongOneShotCVPR2015.pdf (1.83 MB)
Wong, A. & Yuille, A. One Shot Learning via Compositions of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).PDF icon AlexWongOneShotCVPR2015.pdf (1.83 MB)
Newman, J. P. et al. Optogenetic feedback control of neural activity. Elife 4, e07192 (2015).PDF icon elife-07192-v1-download.pdf (5.92 MB)
Rockmore, D. Our Mother the Machine, by Dan Rockmore [Huffpost] . (2015). at <http://www.huffingtonpost.com/dan-rockmore/our-mother-the-machine_b_7273504.html>PDF icon Our Mother the Machine.pdf (199.73 KB)
2013
Rosasco, L. Object recognition data sets (iCub/IIT). (2013).