Nicholas Frosst

According to our database, Nicholas Frosst authored at least 16 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Aya 23: Open Weight Releases to Further Multilingual Progress.

Viraat Aryabumi, John Dang, Dwarak Talupuru, Saurabh Dash, David Cairuz, Hangyu Lin, Bharat Venkitesh, Madeline Smith, Jon Ander Campos, Yi Chern Tan, Kelly Marchisio, Max Bartolo, Sebastian Ruder, Acyr Locatelli, Julia Kreutzer, Nick Frosst, Aidan N. Gomez, Phil Blunsom, Marzieh Fadaee, Ahmet Üstün, Sara Hooker

CoRR, 2024

2022

Interlocking Backpropagation: Improving depthwise model-parallelism.

Aidan N. Gomez, Oscar Key, Kuba Perlin, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal

J. Mach. Learn. Res., 2022

2021

No News is Good News: A Critique of the One Billion Word Benchmark.

Helen Ngo, João G. M. Araújo, Jeffrey Hui, Nicholas Frosst

CoRR, 2021

Mitigating harm in language models with conditional-likelihood filtration.

Helen Ngo, Cooper Raterink, João G. M. Araújo, Ivan Zhang, Carol Chen, Adrien Morisot, Nicholas Frosst

CoRR, 2021

Neural Additive Models: Interpretable Machine Learning with Neural Nets.

Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin J. Lengerich, Rich Caruana, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Interlocking Backpropagation: Improving depthwise model-parallelism.

Aidan N. Gomez, Oscar Key, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal

CoRR, 2020

Neural Additive Models: Interpretable Machine Learning with Neural Nets.

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

CoRR, 2020

Deflecting Adversarial Attacks.

Yao Qin, Nicholas Frosst, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton

CoRR, 2020

Predicting Twitter Engagement With Deep Language Models.

Maksims Volkovs, Zhaoyue Cheng, Mathieu Ravaut, Hojin Yang, Kevin Shen, Jin Peng Zhou, Anson Wong, Saba Zuberi, Ivan Zhang, Nick Frosst, Helen Ngo, Carol Chen, Bharat Venkitesh, Stephen Gou, Aidan N. Gomez

Proceedings of the RecSys Challenge '20: Proceedings of the Recommender Systems Challenge 2020, 2020

Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions.

Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Analyzing and Improving Representations with the Soft Nearest Neighbor Loss.

Nicholas Frosst, Nicolas Papernot, Geoffrey E. Hinton

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

SMILER: Saliency Model Implementation Library for Experimental Research.

Calden Wloka, Toni Kunic, Iuliia Kotseruba, Ramin Fahimi, Nicholas Frosst, Neil D. B. Bruce, John K. Tsotsos

CoRR, 2018

DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules.

Nicholas Frosst, Sara Sabour, Geoffrey E. Hinton

CoRR, 2018

Matrix capsules with EM routing.

Geoffrey E. Hinton, Sara Sabour, Nicholas Frosst

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Dynamic Routing Between Capsules.

Sara Sabour, Nicholas Frosst, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Distilling a Neural Network Into a Soft Decision Tree.

Nicholas Frosst, Geoffrey E. Hinton

Proceedings of the First International Workshop on Comprehensibility and Explanation in AI and ML 2017 co-located with 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017