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Controversial stimuli: pitting neural networks against each other as models of human recognition

21 November 2019

Papers citing "Controversial stimuli: pitting neural networks against each other as models of human recognition"

36 / 36 papers shown

Title
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 85 546 0 06 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 520 42,559 0 03 Dec 2019
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions Yao Qin Nicholas Frosst S. Sabour Colin Raffel G. Cottrell Geoffrey E. Hinton GAN AAML 53 72 0 05 Jul 2019
MNIST-C: A Robustness Benchmark for Computer Vision Norman Mu Justin Gilmer 57 212 0 05 Jun 2019
Understanding the Limitations of Conditional Generative Models Ethan Fetaya J. Jacobsen Will Grathwohl R. Zemel 74 53 0 04 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 91 1,843 0 06 May 2019
Capturing human categorization of natural images at scale by combining deep networks and cognitive models Ruairidh M. Battleday Joshua C. Peterson Thomas Griffiths 42 13 0 26 Apr 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 188 3,445 0 28 Mar 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 68 46 0 25 Mar 2019
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix Wichmann Wieland Brendel 105 2,672 0 29 Nov 2018
DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules Nicholas Frosst S. Sabour Geoffrey E. Hinton GAN 30 47 0 16 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 68 166 0 01 Nov 2018
Do Deep Generative Models Know What They Don't Know? Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan OOD 66 759 0 22 Oct 2018
Humans can decipher adversarial images Zhenglong Zhou C. Firestone AAML 34 122 0 11 Sep 2018
Generalisation in humans and deep neural networks Robert Geirhos Carlos R. Medina Temme Jonas Rauber Heiko H. Schutt Matthias Bethge Felix Wichmann OOD 107 609 0 27 Aug 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 104 1,783 0 30 May 2018
Towards the first adversarially robust neural network model on MNIST Lukas Schott Jonas Rauber Matthias Bethge Wieland Brendel AAML OOD 68 370 0 23 May 2018
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans Gamaleldin F. Elsayed Shreya Shankar Brian Cheung Nicolas Papernot Alexey Kurakin Ian Goodfellow Jascha Narain Sohl-Dickstein AAML 77 262 0 22 Feb 2018
Deep Predictive Coding Network for Object Recognition Haiguang Wen Kuan Han Junxing Shi Yizhen Zhang Eugenio Culurciello Zhongming Liu 40 83 0 13 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 230 3,194 0 01 Feb 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Y. Zhang Phillip Isola Alexei A. Efros Eli Shechtman Oliver Wang EGVM 377 11,877 0 11 Jan 2018
Measuring the tendency of CNNs to Learn Surface Statistical Regularities Jason Jo Yoshua Bengio AAML 71 250 0 30 Nov 2017
Dynamic Routing Between Capsules S. Sabour Nicholas Frosst Geoffrey E. Hinton 177 4,602 0 26 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 310 12,117 0 19 Jun 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,855 0 14 Jun 2017
A Study and Comparison of Human and Deep Learning Recognition Performance Under Visual Distortions Samuel F. Dodge Lina Karam 3DH 64 423 0 06 May 2017
EMNIST: an extension of MNIST to handwritten letters Gregory Cohen Saeed Afshar J. Tapson André van Schaik 63 720 0 17 Feb 2017
Delving into Transferable Adversarial Examples and Black-box Attacks Yanpei Liu Xinyun Chen Chang-rui Liu Basel Alomair AAML 140 1,741 0 08 Nov 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 349 7,995 0 23 May 2016
Illuminating search spaces by mapping elites Jean-Baptiste Mouret Jeff Clune 76 735 0 20 Apr 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,260 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,107 0 20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 169 3,275 0 05 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,479 0 04 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 277 14,927 1 21 Dec 2013
Bayesian Active Learning for Classification and Preference Learning N. Houlsby Ferenc Huszár Zoubin Ghahramani M. Lengyel 122 915 0 24 Dec 2011