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Found 910 results
Author [ Title(Asc)] Type Year
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I
Pagliana, N. & Rosasco, L. Implicit Regularization of Accelerated Methods in Hilbert Spaces. Neural Information Processing Systems (NeurIPS 2019) (2019).PDF icon 9591-implicit-regularization-of-accelerated-methods-in-hilbert-spaces.pdf (451.14 KB)
Poggio, T., Liao, Q. & Xu, M. Implicit dynamic regularization in deep networks. (2020).PDF icon v1.2 (2.29 MB)PDF icon v.59 Update on rank (2.43 MB)
Galanti, T. & Galanti, L. On the Implicit Bias Towards Minimal Depth of Deep Neural Networks. arXiv (2022). at <https://arxiv.org/abs/2202.09028>PDF icon 2202.09028.pdf (2 MB)
Kosakowski, H. L., Powell, L. J. & Spelke, E. S. Imitation Preferences of Preverbal Infants. CBMM Summer Research Program (2014).PDF icon Imitation Preferences of Preverbal Infants. (11.32 MB)
Saxe, R. Imaging the infant brain. Japanese Society for Neuroscience Kobe Japan, (2018).
Magid, R. Imagination and the generation of new ideas. Cognitive Development 34, 99–110 (2015).PDF icon Imagination and the generation of new ideas (266.63 KB)
Ullman, S. et al. Image interpretation by iterative bottom-up top- down processing. (2021).PDF icon CBMM-Memo-120.pdf (2.83 MB)
Ben-Yosef, G. & Ullman, S. Image interpretation above and below the object level. Interface Focus 8, 20180020 (2018).
Ben-Yosef, G. & Ullman, S. Image interpretation above and below the object level. Proceedings of the Royal Society: Interface Focus (2018).PDF icon 2018-BenYosef_Ullman-Image_interpretation_above_and_below the object_level.pdf (3.26 MB)
Ben-Yosef, G. & Ullman, S. Image interpretation above and below the object level. (2018).PDF icon CBMM-Memo-089.pdf (2.06 MB)
McWalter, R. & McDermott, J. H. Illusory sound texture reveals multi-second statistical completion in auditory scene analysis. Nature Communications 10, (2019).
Harrod, J., Purdon, P. L., Brown, E. N. & Flores, F. J. Identification of vigilance states in freely behaving animals using thalamocortical activity and Deep Belief networks. Society for Neuroscience (2019).
H
Tsividis, P., Tenenbaum, J. B. & Schulz, L. Hypothesis-Space Constraints in Causal Learning. Annual Meeting of the Cognitive Science Society (CogSci) (2015). at <https://mindmodeling.org/cogsci2015/papers/0418/index.html>PDF icon hypothesis_space_constraints (1).pdf (1.54 MB)
Zhang, M., Badkundri, R., Talbot, M. B., Zawar, R. & Kreiman, G. Hypothesis-driven Online Video Stream Learning with Augmented Memory. arXiv (2021). doi:10.48550/arXiv.2104.02206PDF icon 2104.02206.pdf (2.25 MB)
Mottaghi, R., Fidler, S., Yuille, A., Urtasun, R. & Parikh, D. Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding. (2014).PDF icon CBMM-Memo-020.pdf (1.89 MB)
Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B. Human-level concept learning through probabilistic program induction. Science 350, 1332-1338 (2015).
Han, Y., Roig, G., Geiger, G. & Poggio, T. Is the Human Visual System Invariant to Translation and Scale?. AAAI Spring Symposium Series, Science of Intelligence (2017).
Han, Y., Roig, G., Geiger, G. & Poggio, T. On the Human Visual System Invariance to Translation and Scale. Vision Sciences Society (2017).
Yang, S., Bill, J., Drugowitsch, J. & Gershman, S. J. Human visual motion perception shows hallmarks of Bayesian structural inference. Scientific Reports 11, (2021).
Traer, J. & McDermott, J. H. Human recognition of environmental sounds is not always robust to reverberation. Annual Meeting of the Acoustical Society 143, (2018).
Lifshitz, I., Fetaya, E. & Ullman, S. Human Pose Estimation Using Deep Consensus Voting. ECCV 2016 (2016).PDF icon 1603.08212.pdf (6.05 MB)
Tsividis, P., Pouncy, T., Xu, J. L., Tenenbaum, J. B. & Gershman, S. J. Human Learning in Atari. AAAI Spring Symposium Series (2017).PDF icon Tsividis et al - Human Learning in Atari.pdf (844.47 KB)
Traer, J. & McDermott, J. H. Human inference of force from impact sounds: Perceptual evidence for inverse physics. Annual Meeting of the Acoustical Society 143, (2018).
Sani, I. et al. The human endogenous attentional control network includes a ventro-temporal cortical node. Nature Communications 12, (2021).
Gerstenberg, T., Goodman, N. D., Lagnado, D. A. & Tenenbaum, J. B. How, whether, why: Causal judgments as counterfactual contrasts. Annual Meeting of the Cognitive Science Society (CogSci) 782-787 (2015). at <https://mindmodeling.org/cogsci2015/papers/0142/index.html>PDF icon GerstenbergEtAl2015-Cogsci.pdf (2.16 MB)

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