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Adversarially trained neural representations are already as robust as biological neural representations.

C. Guo, M. Lee, G. Leclerc, J. Dapello, Y. Rao, A. Madry, and J. DiCarlo. ICML, volume 162 of Proceedings of Machine Learning Research, page 8072-8081. PMLR, (2022)

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Artur Joel

Walter Joel

Feiga Joelsohn

Hans Joël

Moritz Joel

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Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception.J. Dapello, J. Feather, H. Le, T. Marques, D. Cox, J. McDermott, J. DiCarlo, and S. Chung. NeurIPS, page 15595-15607. (2021)On the Information Bottleneck Theory of Deep Learning.A. Saxe, Y. Bansal, J. Dapello, M. Advani, A. Kolchinsky, B. Tracey, and D. Cox. ICLR (Poster), OpenReview.net, (2018)Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness.J. Dapello, K. Kar, M. Schrimpf, R. Geary, M. Ferguson, D. Cox, and J. DiCarlo. ICLR, OpenReview.net, (2023)On the information bottleneck theory of deep learningA. Saxe, Y. Bansal, J. Dapello, M. Advani, A. Kolchinsky, B. Tracey, and D. Cox. Journal of Statistical Mechanics: Theory and Experiment, 2019 (12): 124020 (December 2019)Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations.J. Dapello, T. Marques, M. Schrimpf, F. Geiger, D. Cox, and J. DiCarlo. NeurIPS, (2020)Adversarially trained neural representations are already as robust as biological neural representations.C. Guo, M. Lee, G. Leclerc, J. Dapello, Y. Rao, A. Madry, and J. DiCarlo. ICML, volume 162 of Proceedings of Machine Learning Research, page 8072-8081. PMLR, (2022)ProtoGraph: A Non-Expert Toolkit for Creating Animated Graphs.M. Rodrigues, J. Dapello, P. Vaithilingam, C. Nobre, and J. Beyer. IEEE VIS (Short Papers), page 176-180. IEEE, (2023)On the information bottleneck theory of deep learningA. Saxe, Y. Bansal, J. Dapello, and M. Advani. (2018)Adversarially trained neural representations may already be as robust as corresponding biological neural representations.C. Guo, M. Lee, G. Leclerc, J. Dapello, Y. Rao, A. Madry, and J. DiCarlo. CoRR, (2022)Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds.M. Kuoch, C. Chou, N. Parthasarathy, J. Dapello, J. DiCarlo, H. Sompolinsky, and S. Chung. CoRR, (2023)

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Disambiguation of "Dapello, Joel"

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Adversarially trained neural representations are already as robust as biological neural representations.

Please choose a person to relate this publication to

Artur Joel

Walter Joel

Feiga Joelsohn

Hans Joël

Moritz Joel

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Dapello, Joel"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Adversarially trained neural representations are already as robust as biological neural representations.

Please choose a person to relate this publication to

Artur Joel

Walter Joel

Feiga Joelsohn

Hans Joël

Moritz Joel

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Chicago
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Adversarially trained neural representations are already as robust as biological neural representations.