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The Representational Status of Deep Learning Models

21 March 2023

Papers citing "The Representational Status of Deep Learning Models"

25 / 25 papers shown

Title
Apriori Knowledge in an Era of Computational Opacity: The Role of AI in Mathematical Discovery Eamon Duede Kevin Davey 22 1 0 15 Mar 2024
Talking About Large Language Models Murray Shanahan AI4CE 115 273 0 07 Dec 2022
In-context Learning and Induction Heads Catherine Olsson Nelson Elhage Neel Nanda Nicholas Joseph Nova Dassarma ... Tom B. Brown Jack Clark Jared Kaplan Sam McCandlish C. Olah 344 527 0 24 Sep 2022
Deep Learning Opacity in Scientific Discovery Eamon Duede 47 24 0 01 Jun 2022
Why AI is Harder Than We Think Melanie Mitchell 115 97 0 26 Apr 2021
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 171 688 0 06 Nov 2020
Towards falsifiable interpretability research Matthew L. Leavitt Ari S. Morcos AAML AI4CE 84 68 0 22 Oct 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 229 2,069 0 16 Apr 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 179 123 0 26 Mar 2020
Overinterpretation reveals image classification model pathologies Brandon Carter Siddhartha Jain Jonas W. Mueller David K Gifford FAtt 142 52 0 19 Mar 2020
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 93 449 0 26 Sep 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 260 2,249 0 05 Jul 2019
Understanding artificial intelligence ethics and safety David Leslie FaML AI4TS 74 363 0 11 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 104 1,846 0 06 May 2019
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 197 1,973 0 08 Oct 2018
Humans can decipher adversarial images Zhenglong Zhou C. Firestone AAML 68 122 0 11 Sep 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 116 1,786 0 30 May 2018
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations Weili Nie Yang Zhang Ankit B. Patel FAtt 179 151 0 18 May 2018
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 153 872 0 29 Oct 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,732 0 10 Jun 2016
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 186 3,276 0 05 Dec 2014
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition C. Cadieu Ha Hong Daniel L. K. Yamins Nicolas Pinto Diego Ardila E. Solomon N. Majaj J. DiCarlo 104 787 0 12 Jun 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 306 14,985 1 21 Dec 2013
Rich feature hierarchies for accurate object detection and semantic segmentation Ross B. Girshick Jeff Donahue Trevor Darrell Jitendra Malik ObjD 331 26,271 0 11 Nov 2013
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 316 12,486 0 24 Jun 2012