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Nicholas Frosst
Nicholas Frosst
cofounder of cohere.ai
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Title
Cited by
Cited by
Year
Dynamic routing between capsules
S Sabour, N Frosst, GE Hinton
Advances in neural information processing systems 30, 2017
56862017
Matrix capsules with EM routing
GE Hinton, S Sabour, N Frosst
International conference on learning representations, 2018
12322018
Distilling a neural network into a soft decision tree
N Frosst, G Hinton
arXiv preprint arXiv:1711.09784, 2017
7042017
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
3702021
Analyzing and improving representations with the soft nearest neighbor loss
N Frosst, N Papernot, G Hinton
International conference on machine learning, 2012-2020, 2019
1432019
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
972015
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
892019
Darccc: Detecting adversaries by reconstruction from class conditional capsules
N Frosst, S Sabour, G Hinton
arXiv preprint arXiv:1811.06969, 2018
562018
Dynamic routing between capsules. arXiv 2017
S Sabour, N Frosst, GE Hinton
arXiv preprint arXiv:1710.09829, 0
55
Mitigating harm in language models with conditional-likelihood filtration
H Ngo, C Raterink, JGM Araújo, I Zhang, C Chen, A Morisot, N Frosst
arXiv preprint arXiv:2108.07790, 2021
262021
Deflecting adversarial attacks
Y Qin, N Frosst, C Raffel, G Cottrell, G Hinton
arXiv preprint arXiv:2002.07405, 2020
202020
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
162018
Interlocking backpropagation: Improving depthwise model-parallelism
AN Gomez, O Key, K Perlin, S Gou, N Frosst, J Dean, Y Gal
Journal of Machine Learning Research 23 (171), 1-28, 2022
142022
Matrix capsules with em routing
EH Geoffrey, S Sara, F Nicholas
International conference on learning representations, 2018
92018
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
62020
No news is good news: A critique of the one billion word benchmark
H Ngo, JGM Araújo, J Hui, N Frosst
arXiv preprint arXiv:2110.12609, 2021
32021
Text conditional lyric video generation
N Frosst, J Kereliuk, G Kid
chap. Machine Learning for Creativity and Design Workshop, 2019
32019
The effects of image padding in saliency algorithms
NMW Frosst, C Wloka, J Tsotsos
Perception 43 (1), 106-107, 2014
22014
Capsule neural networks
GE Hinton, NMW Frosst, SSR Aghdam
US Patent 11,694,060, 2023
2023
System and Method for Training Language Models Using Already Trained Language Models
NMW Frosst, R Ghanavi, CA Cremer
US Patent App. 18/060,341, 2023
2023
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