Aidan N. Gomez

According to our database, Aidan N. Gomez authored at least 21 papers between 2017 and 2022.

Collaborative distances:

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

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

Exploring Low Rank Training of Deep Neural Networks.

Siddhartha Rao Kamalakara, Acyr Locatelli, Bharat Venkitesh, Jimmy Ba, Yarin Gal, Aidan N. Gomez

CoRR, 2022

Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval.

Pascal Notin, Mafalda Dias, Jonathan Frazer, Javier Marchena-Hurtado, Aidan N. Gomez, Debora S. Marks, Yarin Gal

Proceedings of the International Conference on Machine Learning, 2022

Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt.

Sören Mindermann, Jan Markus Brauner, Muhammed Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N. Gomez, Adrien Morisot, Sebastian Farquhar, Yarin Gal

Proceedings of the International Conference on Machine Learning, 2022

2021

Prioritized training on points that are learnable, worth learning, and not yet learned.

Sören Mindermann, Muhammed Razzak, Winnie Xu, Andreas Kirsch, Mrinank Sharma, Adrien Morisot, Aidan N. Gomez, Sebastian Farquhar, Jan Markus Brauner, Yarin Gal

CoRR, 2021

Robustness to Pruning Predicts Generalization in Deep Neural Networks.

Lorenz Kuhn, Clare Lyle, Aidan N. Gomez, Jonas Rothfuss, Yarin Gal

CoRR, 2021

Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning.

Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Thomas Rainforth, Yarin Gal

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

SliceOut: Training Transformers and CNNs faster while using less memory.

Pascal Notin, Aidan N. Gomez, Joanna Yoo, Yarin Gal

CoRR, 2020

Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers.

Tim Z. Xiao, Aidan N. Gomez, Yarin Gal

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

2019

RL: Generic reinforcement learning codebase in TensorFlow.

Bryan M. Li, Alexander I. Cowen-Rivers, Piotr Kozakowski, David Tao, Siddhartha Kamalakara, Nitarshan Rajkumar, Hariharan Sezhiyan, Sicong Huang, Aidan N. Gomez

J. Open Source Softw., 2019

A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks.

Angelos Filos, Sebastian Farquhar, Aidan N. Gomez, Tim G. J. Rudner, Zachary Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal

CoRR, 2019

The Difficulty of Training Sparse Neural Networks.

Utku Evci, Fabian Pedregosa, Aidan N. Gomez, Erich Elsen

CoRR, 2019

Learning Sparse Networks Using Targeted Dropout.

Aidan N. Gomez, Ivan Zhang, Kevin Swersky, Yarin Gal, Geoffrey E. Hinton

CoRR, 2019

2018

Depthwise Separable Convolutions for Neural Machine Translation.

Lukasz Kaiser, Aidan N. Gomez, François Chollet

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

Unsupervised Cipher Cracking Using Discrete GANs.

Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser

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

Tensor2Tensor for Neural Machine Translation.

Ashish Vaswani, Samy Bengio, Eugene Brevdo, François Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, Lukasz Kaiser, Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, Jakob Uszkoreit

Proceedings of the 13th Conference of the Association for Machine Translation in the Americas, 2018

2017

One Model To Learn Them All.

Lukasz Kaiser, Aidan N. Gomez, Noam Shazeer, Ashish Vaswani, Niki Parmar, Llion Jones, Jakob Uszkoreit

CoRR, 2017

Attention is All you Need.

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin

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

The Reversible Residual Network: Backpropagation Without Storing Activations.

Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse

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