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Nicholas Frosst

Google Brain Toronto

Neural Additive Models: Interpretable Machine Learning with Neural Nets

Apr 29, 2020
Rishabh Agarwal, Nicholas Frosst, Xuezhou Zhang, Rich Caruana, Geoffrey E. Hinton

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Deflecting Adversarial Attacks

Feb 18, 2020
Yao Qin, Nicholas Frosst, Colin Raffel, Garrison Cottrell, Geoffrey Hinton

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Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions

Jul 05, 2019
Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison Cottrell, Geoffrey Hinton

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Analyzing and Improving Representations with the Soft Nearest Neighbor Loss

Feb 05, 2019
Nicholas Frosst, Nicolas Papernot, Geoffrey Hinton

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SMILER: Saliency Model Implementation Library for Experimental Research

Dec 20, 2018
Calden Wloka, Toni Kunić, Iuliia Kotseruba, Ramin Fahimi, Nicholas Frosst, Neil D. B. Bruce, John K. Tsotsos

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DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules

Nov 16, 2018
Nicholas Frosst, Sara Sabour, Geoffrey Hinton

* To be presented at NIPS 2018 Workshop on Security in Machine Learning 

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Distilling a Neural Network Into a Soft Decision Tree

Nov 27, 2017
Nicholas Frosst, Geoffrey Hinton

* presented at the CEX workshop at AI*IA 2017 conference 

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Dynamic Routing Between Capsules

Nov 07, 2017
Sara Sabour, Nicholas Frosst, Geoffrey E Hinton

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