Oscar Key | DeepAI

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Featured Co-authors

Samuel Kaski
126 publications
Yarin Gal
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Arthur Gretton
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Tom Rainforth
49 publications
Pasquale Minervini
41 publications
David Barber
40 publications
Brooks Paige
31 publications
Francois-Xavier Briol
29 publications
Matt J. Kusner
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Jeff Dean
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Aidan N. Gomez
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∙ 07/12/2023

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

The computation necessary for training Transformer-based language models...

0 Jean Kaddour, et al. ∙

∙ 01/27/2023

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

Likelihood-free inference methods typically make use of a distance betwe...

0 Ayush Bharti, et al. ∙

∙ 09/15/2022

Towards Healing the Blindness of Score Matching

Score-based divergences have been widely used in machine learning and st...

5 Mingtian Zhang, et al. ∙

∙ 11/19/2021

Composite Goodness-of-fit Tests with Kernels

Model misspecification can create significant challenges for the impleme...

0 Oscar Key, et al. ∙

∙ 03/16/2021

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

Counterfactual explanations (CEs) are a practical tool for demonstrating...

10 Lisa Schut, et al. ∙

∙ 02/22/2021

Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression

We propose a new model that estimates uncertainty in a single forward pa...

0 Joost van Amersfoort, et al. ∙

∙ 11/01/2020

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

We show that the gradient estimates used in training Deep Gaussian Proce...

0 Tim G. J. Rudner, et al. ∙

∙ 10/08/2020

Interlocking Backpropagation: Improving depthwise model-parallelism

The number of parameters in state of the art neural networks has drastic...

11 Aidan N. Gomez, et al. ∙

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