Publication

Found 23 results
Author Title Type [ Year(Desc)]
Filters: First Letter Of Last Name is O  [Clear All Filters]
2014
Amir, N. et al. Abstracts of the 2014 Brains, Minds, and Machines Summer Course. (2014).PDF icon CBMM-Memo-024.pdf (2.86 MB)
Amir, N. et al. Abstracts of the 2014 Brains, Minds, and Machines Summer Course. (2014).PDF icon CBMM-Memo-024.pdf (2.86 MB)
2015
Hartshorne, J. K. The causes and consequences explicit in verbs. Language, Cognition and Neuroscience 30, 716-734 (2015).
Buice, M. & de Vries, S. Population Coding, Correlations, and Functional Connectivity in the mouse visual system with the Cortical Activity Map (CAM). Society for Neuroscience 2015 (2015).PDF icon 2015 SFN Population_Coding.pdf (2.94 MB)
Buice, M. & de Vries, S. Population Coding, Correlations, and Functional Connectivity in the mouse visual system with the Cortical Activity Map (CAM). Society for Neuroscience 2015 (2015).PDF icon 2015 SFN Population_Coding.pdf (2.94 MB)
2016
Owens, A., Isola, P., McDermott, J. H., Freeman, W. T. & Torralba, A. Lecture Notes in Computer ScienceComputer Vision – ECCV 2016Ambient Sound Provides Supervision for Visual Learning. 14th European Conference on Computer Vision 801 - 816 (2016). doi:10.1007/978-3-319-46448-010.1007/978-3-319-46448-0_48
Owens, A. et al. Visually indicated sounds. Conference on Computer Vision and Pattern Recognition (2016).PDF icon Owens_etal_2016_visually_indicated_sounds_CVPR.pdf (7.57 MB)
2018
O'Brien, N., Latessa, S., Evangelopoulos, G. & Boix, X. The Language of Fake News: Opening the Black-Box of Deep Learning Based Detectors. workshop on "AI for Social Good", NIPS 2018 (2018). at <http://hdl.handle.net/1721.1/120056>PDF icon fake-news-paper-NIPS.pdf (147.36 KB)PDF icon fake-news-paper-NIPS_2018_v2.pdf (147.36 KB)
Owaki, T. et al. Searching for visual features that explain response variance of face neurons in inferior temporal cortex. PLOS ONE 13, e0201192 (2018).
2019
Dobs, K. et al. Effects of Face Familiarity in Humans and Deep Neural Networks . European Conference on Visual Perception (2019).
Obiajulu, D., Vazquez, Y., Ianni, G. A., Yazdani, F. & Freiwald, W. A. Facial Expression Scoring and Assessment of Facial Movement Kinematics in Non-Human Primates. The Rockefeller University 2019 Summer Science Research Program (SSRP) (2019).
Fazeli, N. et al. See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion. Science Robotics 4, eaav3123 (2019).
Jacoby, N. et al. Universal and Non-universal Features of Musical Pitch Perception Revealed by Singing. Current Biology (2019). doi:10.1016/j.cub.2019.08.020
2021
Cohen, M. A., Ostrand, C., Frontero, N. & Pham, P. - N. Characterizing a snapshot of perceptual experience. Journal of Experimental Psychology: General (2021). doi:10.1037/xge0000864
Houlihan, S. Dae, Tenenbaum, J. B. & Saxe, R. The Neural Basis of Mentalizing: Linking Models of Theory of Mind and Measures of Human Brain Activity. 209 - 235 (Springer International Publishing, 2021). doi:10.1007/978-3-030-51890-510.1007/978-3-030-51890-5_11
Liu, Y. et al. Temporally delayed linear modelling (TDLM) measures replay in both animals and humans. eLife 10, (2021).
2022
Houlihan, S. Dae, Ong, D., Cusimano, M. & Saxe, R. Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind. Proceedings of the Annual Conference of the Cognitive Science Society 44, 854-861 (2022).PDF icon Houlihan 2022 Proceedings of the 44th Annual Conference of the Cognitive Science Society.pdf (687.98 KB)
Ellis, K., Albright, A., Solar-Lezama, A., Tenenbaum, J. B. & O’Donnell, T. J. Synthesizing theories of human language with Bayesian program inductionAbstract. Nature Communications 13, (2022).PDF icon s41467-022-32012-w.pdf (2.19 MB)
2023
O'Connell, T. P. et al. Approaching human 3D shape perception with neurally mappable models. arXiv (2023). at <https://arxiv.org/abs/2308.11300>
Zador, A. et al. Catalyzing next-generation Artificial Intelligence through NeuroAIAbstract. Nature Communications 14, (2023).
Zador, A. et al. Catalyzing next-generation Artificial Intelligence through NeuroAIAbstract. Nature Communications 14, (2023).
Bricken, T., Schaeffer, R., Olshausen, B. & Kreiman, G. Emergence of Sparse Representations from Noise. ICML 2023 (2023). at <https://openreview.net/pdf?id=cxYaBAXVKg>
2024
Alfano, P. Didier, Pastore, V. Paolo, Rosasco, L. & Odone, F. Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods. Image and Vision Computing 142, 104894 (2024).