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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)

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Artur Joel

Walter Joel

Feiga Joelsohn

Moritz Joel

Georg Joël

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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)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)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)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)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)Combining Different V1 Brain Model Variants to Improve Robustness to Image Corruptions in CNNs.A. Baidya, J. Dapello, J. DiCarlo, and T. Marques. CoRR, (2021)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)

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Disambiguation of "Dapello, Joel"

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On the Information Bottleneck Theory of Deep Learning.

Please choose a person to relate this publication to

Artur Joel

Walter Joel

Feiga Joelsohn

Moritz Joel

Georg Joël

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 On the Information Bottleneck Theory of Deep Learning.

Please choose a person to relate this publication to

Artur Joel

Walter Joel

Feiga Joelsohn

Moritz Joel

Georg Joël

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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On the Information Bottleneck Theory of Deep Learning.