Oscar Key

According to our database, Oscar Key authored at least 11 papers between 2020 and 2024.

Collaborative distances:

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

2024

Approximate Top-<i>k</i> for Increased Parallelism.

Oscar Key, Luka Ribar, Alberto Cattaneo, Luke Hudlass-Galley, Douglas Orr

CoRR, 2024

Scalable Data Assimilation with Message Passing.

Oscar Key, So Takao, Daniel Giles, Marc Peter Deisenroth

CoRR, 2024

2023

No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models.

Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference.

Ayush Bharti, Masha Naslidnyk, Oscar Key, Samuel Kaski, François-Xavier Briol

Proceedings of the International Conference on Machine Learning, 2023

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

Towards Healing the Blindness of Score Matching.

Mingtian Zhang, Oscar Key, Peter Hayes, David Barber, Brooks Paige, François-Xavier Briol

CoRR, 2022

2021

Composite Goodness-of-fit Tests with Kernels.

Oscar Key, Tamara Fernandez, Arthur Gretton, François-Xavier Briol

CoRR, 2021

Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression.

Joost van Amersfoort, Lewis Smith, Andrew Jesson, Oscar Key, Yarin Gal

CoRR, 2021

On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes.

Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth

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

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties.

Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Interlocking Backpropagation: Improving depthwise model-parallelism.

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

CoRR, 2020