Publication

Found 910 results
Author Title [ Type(Desc)] Year
Conference Paper
Galanti, T., Xu, M., Galanti, L. & Poggio, T. Norm-based Generalization Bounds for Sparse Neural Networks. NeurIPS 2023 (2023). at <https://proceedings.neurips.cc/paper_files/paper/2023/file/8493e190ff1bbe3837eca821190b61ff-Paper-Conference.pdf>PDF icon NeurIPS-2023-norm-based-generalization-bounds-for-sparse-neural-networks-Paper-Conference.pdf (577.69 KB)
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)
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>
Myanganbayar, B. et al. Partially Occluded Hands: A challenging new dataset for single-image hand pose estimation. The 14th Asian Conference on Computer Vision (ACCV 2018) (2018). at <http://accv2018.net/>PDF icon partially-occluded-hands-6.pdf (8.29 MB)
Liu, S., McCoy, J. P. & Ullman, T. D. People's perceptions of others’ risk preferences. Cognitive Science Society (2019).PDF icon risk_cogsci_2019_final.pdf (899.8 KB)
Yildirim, I., Siegel, M. & Tenenbaum, J. B. Perceiving Fully Occluded Objects with Physical Simulation. Cognitive Science Conference (CogSci) (2015).
Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception. AAAI-21 (2021).
Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Eventsfor Machine Social Perception. Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020 (2020). at <https://openreview.net/forum?id=_bokm801zhx>PDF icon phase_physically_grounded_abstract_social_events_for_machine_social_perception.pdf (2.49 MB)
Zhang, C., Voinea, S., Evangelopoulos, G., Rosasco, L. & Poggio, T. Phone Classification by a Hierarchy of Invariant Representation Layers. INTERSPEECH 2014 - 15th Annual Conf. of the International Speech Communication Association (International Speech Communication Association (ISCA), 2014). at <http://www.isca-speech.org/archive/interspeech_2014/i14_2346.html>
Kulkarni, T., Kohli, P., Tenenbaum, J. B. & Mansinghka, V. Picture: An Imperative Probabilistic Programming Language for Scene Perception. Computer Vision and Pattern Recognition (2015).
Berzak, Y., Nakamura, C., Flynn, S. & Katz, B. Predicting Native Language from Gaze. Annual Meeting of the Association for Computational Linguistics (ACL 2017) (2017).
Yan, P., Magid, R. & Schulz, L. Preschoolers expect others to learn rationally from evidence. Annual Conference of the Cognitive Science Society (2014).PDF icon Yan, Magid, & Schulz_CogSci14_REVISED.pdf (302.4 KB)
Bagus, A. Marliawaty, Marques, T., Sanghavi, S., DiCarlo, J. J. & Schrimpf, M. Primate Inferotemporal Cortex Neurons Generalize Better to Novel Image Distributions Than Analogous Deep Neural Networks Units. NeurIPS (2022). at <https://openreview.net/forum?id=iPF7mhoWkOl>
Han, Y., Roig, G., Geiger, G. & Poggio, T. Properties of invariant object recognition in human one-shot learning suggests a hierarchical architecture different from deep convolutional neural networks. Vision Science Society (2019).
Han, Y., Roig, G., Geiger, G. & Poggio, T. Properties of invariant object recognition in human oneshot learning suggests a hierarchical architecture different from deep convolutional neural networks . Vision Science Society (2019). doi:10.1167/19.10.28d
Coronel, S. Otero, Phillips-Jones, T., Sani, I. & Freiwald, W. A. Pupillary responses track changes in arousal and attention while exploring a virtual reality environment. The Rockefeller University 2019 Summer Undergraduate Research Fellowship (SURF) Program (2019).
Chu, J., Gauthier, J., Levy, R., Tenenbaum, J. B. & Schulz, L. Query-guided visual search . 41st Annual conference of the Cognitive Science Society (2019).
Dillon, M. R. & Spelke, E. S. Reorientation ability predicts early spatial symbol reading. 2015 Society for Research in Child Development Biennial Meeting (2015).
Tacchetti, A., Voinea, S., Evangelopoulos, G. & Poggio, T. 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>
Cusimano, M., Traer, J. & McDermott, J. H. Scrape, rub, and roll: causal inference in the perception of sustained contact sounds . Cognitive Science (2019).
Siddharth, N., Barbu, A. & Siskind, J. Mark. Seeing What You’re Told: Sentence-Guided Activity Recognition In Video. CVPR (IEEE, 2014).PDF icon Publication (453.54 KB)
Hicks, J. M. & McDermott, J. H. Segregation from Noise as Outlier Detection . Association for Research in Otolaryngology (2020).
Janner, M., Wu, J., Kulkarni, T., Yildirim, I. & Tenenbaum, J. B. Self-supervised intrinsic image decomposition. Annual Conference on Neural Information Processing Systems (NIPS) (2017). at <https://papers.nips.cc/paper/7175-self-supervised-intrinsic-image-decomposition>PDF icon intrinsicImg_nips_2017.pdf (5.87 MB)
Wang, J. & Yuille, A. Semantic Part Segmentation using Compositional Model combing Shape and Appearance. CVPR (2015).PDF icon JianyuWangSemanticCVPR2015 (1).pdf (6.15 MB)

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