Ethan Dyer

According to our database, Ethan Dyer authored at least 19 papers between 2018 and 2024.

Collaborative distances:

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

2024

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy P. Lillicrap, Jean-Baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, Ioannis Antonoglou, Rohan Anil, Sebastian Borgeaud, Andrew M. Dai, Katie Millican, Ethan Dyer, Mia Glaese, Thibault Sottiaux, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, James Molloy, Jilin Chen, Michael Isard, Paul Barham, Tom Hennigan, Ross McIlroy, Melvin Johnson, Johan Schalkwyk, Eli Collins, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, Clemens Meyer, Gregory Thornton, Zhen Yang, Henryk Michalewski, Zaheer Abbas, Nathan Schucher, Ankesh Anand, Richard Ives, James Keeling, Karel Lenc, Salem Haykal, Siamak Shakeri, Pranav Shyam, Aakanksha Chowdhery, Roman Ring, Stephen Spencer, Eren Sezener, et al.

CoRR, 2024

2023

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models.

Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel

CoRR, 2023

PaLM 2 Technical Report.

Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernández Ábrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan A. Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, et al.

CoRR, 2023

2022

WhichTF is functionally important in your open chromatin data?

Yosuke Tanigawa, Ethan Dyer, Gill Bejerano

PLoS Comput. Biol., 2022

Solving Quantitative Reasoning Problems with Language Models.

Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay V. Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, Vedant Misra

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Block-Recurrent Transformers.

DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exploring Length Generalization in Large Language Models.

Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay V. Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Effect of scale on catastrophic forgetting in neural networks.

Vinay Venkatesh Ramasesh, Aitor Lewkowycz, Ethan Dyer

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Explaining Neural Scaling Laws.

Yasaman Bahri, Ethan Dyer, Jared Kaplan, Jaehoon Lee, Utkarsh Sharma

CoRR, 2021

Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization.

Neha S. Wadia, Daniel Duckworth, Samuel S. Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein

Proceedings of the 38th International Conference on Machine Learning, 2021

When Do Curricula Work?

Xiaoxia Wu, Ethan Dyer, Behnam Neyshabur

Proceedings of the 9th International Conference on Learning Representations, 2021

Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics.

Vinay Venkatesh Ramasesh, Ethan Dyer, Maithra Raghu

Proceedings of the 9th International Conference on Learning Representations, 2021

Tradeoffs in Data Augmentation: An Empirical Study.

Raphael Gontijo Lopes, Sylvia J. Smullin, Ekin Dogus Cubuk, Ethan Dyer

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Asymptotics of Wide Convolutional Neural Networks.

Anders Andreassen, Ethan Dyer

CoRR, 2020

Whitening and second order optimization both destroy information about the dataset, and can make generalization impossible.

Neha S. Wadia, Daniel Duckworth, Samuel S. Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein

CoRR, 2020

The large learning rate phase of deep learning: the catapult mechanism.

Aitor Lewkowycz, Yasaman Bahri, Ethan Dyer, Jascha Sohl-Dickstein, Guy Gur-Ari

CoRR, 2020

Affinity and Diversity: Quantifying Mechanisms of Data Augmentation.

Raphael Gontijo Lopes, Sylvia J. Smullin, Ekin D. Cubuk, Ethan Dyer

CoRR, 2020

Asymptotics of Wide Networks from Feynman Diagrams.

Ethan Dyer, Guy Gur-Ari

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

2018

Gradient Descent Happens in a Tiny Subspace.

Guy Gur-Ari, Daniel A. Roberts, Ethan Dyer

CoRR, 2018