Zobrazeno 1 - 10
of 249
pro vyhledávání: '"DiCarlo, James J"'
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:
Kuoch, Michael, Chou, Chi-Ning, Parthasarathy, Nikhil, Dapello, Joel, DiCarlo, James J., Sompolinsky, Haim, Chung, SueYeon
Recently, growth in our understanding of the computations performed in both biological and artificial neural networks has largely been driven by either low-level mechanistic studies or global normative approaches. However, concrete methodologies for
Externí odkaz:
http://arxiv.org/abs/2312.14285
Autor:
Kar, Kohitij, DiCarlo, James J
Visual object recognition -- the behavioral ability to rapidly and accurately categorize many visually encountered objects -- is core to primate cognition. This behavioral capability is algorithmically impressive because of the myriad identity-preser
Externí odkaz:
http://arxiv.org/abs/2312.05956
The visual object category reports of artificial neural networks (ANNs) are notoriously sensitive to tiny, adversarial image perturbations. Because human category reports (aka human percepts) are thought to be insensitive to those same small-norm per
Externí odkaz:
http://arxiv.org/abs/2308.06887
Autor:
Guo, Chong, Lee, Michael J., Leclerc, Guillaume, Dapello, Joel, Rao, Yug, Madry, Aleksander, DiCarlo, James J.
Visual systems of primates are the gold standard of robust perception. There is thus a general belief that mimicking the neural representations that underlie those systems will yield artificial visual systems that are adversarially robust. In this wo
Externí odkaz:
http://arxiv.org/abs/2206.11228
Autor:
Dapello, Joel, Feather, Jenelle, Le, Hang, Marques, Tiago, Cox, David D., McDermott, Josh H., DiCarlo, James J., Chung, SueYeon
Adversarial examples are often cited by neuroscientists and machine learning researchers as an example of how computational models diverge from biological sensory systems. Recent work has proposed adding biologically-inspired components to visual neu
Externí odkaz:
http://arxiv.org/abs/2111.06979
Publikováno v:
Workshop on Shared Visual Representations in Human and Machine Intelligence 2021
While some convolutional neural networks (CNNs) have surpassed human visual abilities in object classification, they often struggle to recognize objects in images corrupted with different types of common noise patterns, highlighting a major limitatio
Externí odkaz:
http://arxiv.org/abs/2110.10645
Autor:
Margalit, Eshed, Lee, Hyodong, Finzi, Dawn, DiCarlo, James J., Grill-Spector, Kalanit, Yamins, Daniel L.K.
Publikováno v:
In Neuron 17 July 2024 112(14):2435-2451
Autor:
Gan, Chuang, Zhou, Siyuan, Schwartz, Jeremy, Alter, Seth, Bhandwaldar, Abhishek, Gutfreund, Dan, Yamins, Daniel L. K., DiCarlo, James J, McDermott, Josh, Torralba, Antonio, Tenenbaum, Joshua B.
We introduce a visually-guided and physics-driven task-and-motion planning benchmark, which we call the ThreeDWorld Transport Challenge. In this challenge, an embodied agent equipped with two 9-DOF articulated arms is spawned randomly in a simulated
Externí odkaz:
http://arxiv.org/abs/2103.14025
Autor:
Gan, Chuang, Schwartz, Jeremy, Alter, Seth, Mrowca, Damian, Schrimpf, Martin, Traer, James, De Freitas, Julian, Kubilius, Jonas, Bhandwaldar, Abhishek, Haber, Nick, Sano, Megumi, Kim, Kuno, Wang, Elias, Lingelbach, Michael, Curtis, Aidan, Feigelis, Kevin, Bear, Daniel M., Gutfreund, Dan, Cox, David, Torralba, Antonio, DiCarlo, James J., Tenenbaum, Joshua B., McDermott, Josh H., Yamins, Daniel L. K.
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties in
Externí odkaz:
http://arxiv.org/abs/2007.04954