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Publications

We do research in both theoretical machine learning, as well as applications of machine learning in various domains, including medical, astronomy, autonomous driving, and more.

Recent publications:
07/2019: "Benchmarking Bayesian Deep Learning with Diabetic Retinopathy Diagnosis" (Angelos Filos, Sebastian Farquhar, Aidan Gomez, Tim G. J. Rudner, Zac Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal).
05/2019: "BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning" (Andreas Kirsch, Joost van Amersfoort, Yarin Gal).
05/2019: "Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning" (Mike Walmsley, Lewis Smith, Chris Lintott, Yarin Gal, Steven Bamford, Hugh Dickinson, Lucy Fortson, Sandor Kruk, Karen Masters, Claudia Scarlata, Brooke Simmons, Rebecca Smethurst, Darryl Wright).

Reproducibility and Code

One of our lab's missions is to contribute to the reproducibility effort. Here we provide code for our own research, as well as reproductions of works by others (e.g. ones we implemented as baselines as part of our own research).

Recent code release:
07/2019: Putting TensorFlow back in PyTorch, back in TensorFlow (differentiable TensorFlow PyTorch adapters) (Andreas Kirsch).
06/2019: Code for BatchBALD blog post and paper (active learning) (Andreas Kirsch, Joost van Amersfoort, Yarin Gal).
06/2019: Reproducing the results from "Do Deep Generative Models Know What They Don't Know?" (Joost van Amersfoort).

Group Members

We are researchers coming from varied backgrounds, including Computer Science, Maths & Stats, Engineering, and Physics.

We come from academia (Oxford, Cambridge, MILA, McGill, U of Amsterdam, U of Toronto, Yale, and others) and industry (Google, DeepMind, Twitter, Qualcomm, and startups).

We include 3 Rhodes Scholars, 2 Clarendon Scholars, one DeepMind Scholar, with our students funded by many additional sources (AIMS CDT, Cyber CDT, and more).

Contact

We are located at
Department of Computer Science, University of Oxford
Wolfson Building
Parks Road
OXFORD
OX1 3QD
UK
Twitter: @OATML_Oxford
Github: OATML
Email: oatml@cs.ox.ac.uk


Are you looking to do a PhD in machine learning? Did you do a PhD in another field and want to do a postdoc in machine learning? Would you like to visit the group?

How to apply