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Nicholas Frosst
Nicholas Frosst
Unknown affiliation
Verified email at secant.ai
Title
Cited by
Cited by
Year
Dynamic routing between capsules
S Sabour, N Frosst, GE Hinton
Advances in neural information processing systems 30, 2017
39022017
Matrix capsules with EM routing
GE Hinton, S Sabour, N Frosst
International conference on learning representations, 2018
8732018
Distilling a neural network into a soft decision tree
N Frosst, G Hinton
arXiv preprint arXiv:1711.09784, 2017
4342017
Neural additive models: Interpretable machine learning with neural nets
R Agarwal, L Melnick, N Frosst, X Zhang, B Lengerich, R Caruana, ...
Advances in Neural Information Processing Systems 34, 4699-4711, 2021
1172021
On computational modeling of visual saliency: Examining what’s right, and what’s left
NDB Bruce, C Wloka, N Frosst, S Rahman, JK Tsotsos
Vision research 116, 95-112, 2015
922015
Analyzing and improving representations with the soft nearest neighbor loss
N Frosst, N Papernot, G Hinton
International conference on machine learning, 2012-2020, 2019
712019
Detecting and diagnosing adversarial images with class-conditional capsule reconstructions
Y Qin, N Frosst, S Sabour, C Raffel, G Cottrell, G Hinton
arXiv preprint arXiv:1907.02957, 2019
512019
Darccc: Detecting adversaries by reconstruction from class conditional capsules
N Frosst, S Sabour, G Hinton
arXiv preprint arXiv:1811.06969, 2018
462018
Deflecting adversarial attacks
Y Qin, N Frosst, C Raffel, G Cottrell, G Hinton
arXiv preprint arXiv:2002.07405, 2020
162020
Smiler: Saliency model implementation library for experimental research
C Wloka, T Kunić, I Kotseruba, R Fahimi, N Frosst, NDB Bruce, JK Tsotsos
arXiv preprint arXiv:1812.08848, 2018
102018
Matrix capsules with em routing
HE Geoffrey, S Sara, F Nicholas
International conference on learning representations, 2018
72018
Predicting twitter engagement with deep language models
M Volkovs, Z Cheng, M Ravaut, H Yang, K Shen, JP Zhou, A Wong, ...
Proceedings of the Recommender Systems Challenge 2020, 38-43, 2020
42020
Mitigating harm in language models with conditional-likelihood filtration
H Ngo, C Raterink, JGM Ara˙jo, I Zhang, C Chen, A Morisot, N Frosst
arXiv preprint arXiv:2108.07790, 2021
32021
Text conditional lyric video generation
N Frosst, J Kereliuk, G Kid
chap. Machine Learning for Creativity and Design Workshop, 2019
22019
The effects of image padding in saliency algorithms
NMW Frosst, C Wloka, J Tsotsos
Perception ECVP abstract 43, 106-106, 2014
22014
Interlocking Backpropagation: Improving depthwise model-parallelism
AN Gomez, O Key, S Gou, N Frosst, J Dean, Y Gal
arXiv preprint arXiv:2010.04116, 2020
12020
Neural network training using the soft nearest neighbor loss
GE Hinton, NMW Frosst, NGR Papernot
US Patent App. 17/423,612, 2022
2022
No News is Good News: A Critique of the One Billion Word Benchmark
H Ngo, JGM Ara˙jo, J Hui, N Frosst
arXiv preprint arXiv:2110.12609, 2021
2021
Neural Additive Models: Interpretable Machine Learning with Neural Networks
R Agarwal, L Melnick, N Frosst, B Lengerich, X Zhang, R Caruana, ...
2021
Capsule neural networks
GE Hinton, NMW Frosst, SSR Aghdam
US Patent App. 16/652,536, 2020
2020
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