Zobrazeno 1 - 10
of 230
pro vyhledávání: '"Tsao, Doris"'
Autor:
Peters, Benjamin, DiCarlo, James J., Gureckis, Todd, Haefner, Ralf, Isik, Leyla, Tenenbaum, Joshua, Konkle, Talia, Naselaris, Thomas, Stachenfeld, Kimberly, Tavares, Zenna, Tsao, Doris, Yildirim, Ilker, Kriegeskorte, Nikolaus
Vision is widely understood as an inference problem. However, two contrasting conceptions of the inference process have each been influential in research on biological vision as well as the engineering of machine vision. The first emphasizes bottom-u
Externí odkaz:
http://arxiv.org/abs/2401.06005
Autor:
Zador, Anthony, Escola, Sean, Richards, Blake, Ölveczky, Bence, Bengio, Yoshua, Boahen, Kwabena, Botvinick, Matthew, Chklovskii, Dmitri, Churchland, Anne, Clopath, Claudia, DiCarlo, James, Ganguli, Surya, Hawkins, Jeff, Koerding, Konrad, Koulakov, Alexei, LeCun, Yann, Lillicrap, Timothy, Marblestone, Adam, Olshausen, Bruno, Pouget, Alexandre, Savin, Cristina, Sejnowski, Terrence, Simoncelli, Eero, Solla, Sara, Sussillo, David, Tolias, Andreas S., Tsao, Doris
Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which c
Externí odkaz:
http://arxiv.org/abs/2210.08340
Ten years into the revival of deep networks and artificial intelligence, we propose a theoretical framework that sheds light on understanding deep networks within a bigger picture of Intelligence in general. We introduce two fundamental principles, P
Externí odkaz:
http://arxiv.org/abs/2207.04630
Autor:
Tsao, Thomas, Tsao, Doris Y.
The world is composed of objects, the ground, and the sky. Visual perception of objects requires solving two fundamental challenges: segmenting visual input into discrete units, and tracking identities of these units despite appearance changes due to
Externí odkaz:
http://arxiv.org/abs/2107.02036
Autor:
Huang, Yujia, Gornet, James, Dai, Sihui, Yu, Zhiding, Nguyen, Tan, Tsao, Doris Y., Anandkumar, Anima
Neural networks are vulnerable to input perturbations such as additive noise and adversarial attacks. In contrast, human perception is much more robust to such perturbations. The Bayesian brain hypothesis states that human brains use an internal gene
Externí odkaz:
http://arxiv.org/abs/2007.09200
Autor:
Higgins, Irina, Chang, Le, Langston, Victoria, Hassabis, Demis, Summerfield, Christopher, Tsao, Doris, Botvinick, Matthew
Deep supervised neural networks trained to classify objects have emerged as popular models of computation in the primate ventral stream. These models represent information with a high-dimensional distributed population code, implying that inferotempo
Externí odkaz:
http://arxiv.org/abs/2006.14304
Autor:
Guo, Hongsun, Salahshoor, Hossein, Wu, Di, Yoo, Sangjin, Sato, Tomokazu, Tsao, Doris Y., Shapiro, Mikhail G.
Publikováno v:
In iScience 15 December 2023 26(12)
Akademický článek
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Autor:
Klink, P. Christiaan, Aubry, Jean-François, Ferrera, Vincent P., Fox, Andrew S., Froudist-Walsh, Sean, Jarraya, Béchir, Konofagou, Elisa E., Krauzlis, Richard J., Messinger, Adam, Mitchell, Anna S., Ortiz-Rios, Michael, Oya, Hiroyuki, Roberts, Angela C., Roe, Anna Wang, Rushworth, Matthew F.S., Sallet, Jérôme, Schmid, Michael Christoph, Schroeder, Charles E., Tasserie, Jordy, Tsao, Doris Y., Uhrig, Lynn, Vanduffel, Wim, Wilke, Melanie, Kagan, Igor, Petkov, Christopher I.
Publikováno v:
In NeuroImage 15 July 2021 235
Autor:
Tsao, Doris Y.
Publikováno v:
Scientific American, 2019 Feb 01. 320(2), 22-29.
Externí odkaz:
https://www.jstor.org/stable/27265064