Aidan N. Gomez

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 30

Top Topics

Machine Translation

Diabetic Retinopathy

Top Venues

Publications

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
Aya 23: Open Weight Releases to Further Multilingual Progress. CoRR (2024)
Pascal Notin, Mafalda Dias, Jonathan Frazer, Javier Marchena-Hurtado, Aidan N. Gomez, Debora S. Marks, Yarin Gal
Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval. ICML (2022)
Sören Mindermann, Jan Markus Brauner, Muhammed Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N. Gomez, Adrien Morisot, Sebastian Farquhar, Yarin Gal
Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt. ICML (2022)
Aidan N. Gomez, Oscar Key, Kuba Perlin, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal
Interlocking Backpropagation: Improving depthwise model-parallelism. J. Mach. Learn. Res. 23 (2022)
Siddhartha Rao Kamalakara, Acyr Locatelli, Bharat Venkitesh, Jimmy Ba, Yarin Gal, Aidan N. Gomez
Exploring Low Rank Training of Deep Neural Networks. CoRR (2022)
Sören Mindermann, Jan Markus Brauner, Muhammed Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N. Gomez, Adrien Morisot, Sebastian Farquhar, Yarin Gal
Prioritized Training on Points that are Learnable, Worth Learning, and Not Yet Learnt. CoRR (2022)
Pascal Notin, Mafalda Dias, Jonathan Frazer, Javier Marchena-Hurtado, Aidan N. Gomez, Debora S. Marks, Yarin Gal
Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval. CoRR (2022)
Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Tom Rainforth, Yarin Gal
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning. CoRR (2021)
Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Thomas Rainforth, Yarin Gal
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning. NeurIPS (2021)
Sören Mindermann, Muhammed Razzak, Winnie Xu, Andreas Kirsch, Mrinank Sharma, Adrien Morisot, Aidan N. Gomez, Sebastian Farquhar, Jan Markus Brauner, Yarin Gal
Prioritized training on points that are learnable, worth learning, and not yet learned. CoRR (2021)
Lorenz Kuhn, Clare Lyle, Aidan N. Gomez, Jonas Rothfuss, Yarin Gal
Robustness to Pruning Predicts Generalization in Deep Neural Networks. CoRR (2021)
Aidan N. Gomez, Oscar Key, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal
Interlocking Backpropagation: Improving depthwise model-parallelism. CoRR (2020)
Pascal Notin, Aidan N. Gomez, Joanna Yoo, Yarin Gal
SliceOut: Training Transformers and CNNs faster while using less memory. CoRR (2020)
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
Predicting Twitter Engagement With Deep Language Models. RecSys Challenge (2020)
Tim Z. Xiao, Aidan N. Gomez, Yarin Gal
Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers. CoRR (2020)
Bryan M. Li, Alexander Imani Cowen-Rivers, Piotr Kozakowski, David Tao, Siddhartha Kamalakara, Nitarshan Rajkumar, Hariharan Sezhiyan, Sicong Huang, Aidan N. Gomez
RL: Generic reinforcement learning codebase in TensorFlow. J. Open Source Softw. 4 (42) (2019)
Aidan N. Gomez, Ivan Zhang, Kevin Swersky, Yarin Gal, Geoffrey E. Hinton
Learning Sparse Networks Using Targeted Dropout. CoRR (2019)
Utku Evci, Fabian Pedregosa, Aidan N. Gomez, Erich Elsen
The Difficulty of Training Sparse Neural Networks. CoRR (2019)
Angelos Filos, Sebastian Farquhar, Aidan N. Gomez, Tim G. J. Rudner, Zachary Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal
A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks. CoRR (2019)
Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser
Unsupervised Cipher Cracking Using Discrete GANs. CoRR (2018)
Lukasz Kaiser, Aidan N. Gomez, François Chollet
Depthwise Separable Convolutions for Neural Machine Translation. ICLR (Poster) (2018)
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
Tensor2Tensor for Neural Machine Translation. CoRR (2018)
Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser
Unsupervised Cipher Cracking Using Discrete GANs. ICLR (Poster) (2018)
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
Tensor2Tensor for Neural Machine Translation. AMTA (1) (2018)
Lukasz Kaiser, Aidan N. Gomez, François Chollet
Depthwise Separable Convolutions for Neural Machine Translation. CoRR (2017)
Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse
The Reversible Residual Network: Backpropagation Without Storing Activations. NIPS (2017)
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin
Attention is All you Need. NIPS (2017)
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin
Attention Is All You Need. CoRR (2017)
Lukasz Kaiser, Aidan N. Gomez, Noam Shazeer, Ashish Vaswani, Niki Parmar, Llion Jones, Jakob Uszkoreit
One Model To Learn Them All. CoRR (2017)
Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse
The Reversible Residual Network: Backpropagation Without Storing Activations. CoRR (2017)