News

More news

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:
12/2023: "High-Cadence Thermospheric Density Estimation enabled by Machine Learning on Solar Imagery" (Shreshth Malik, James Walsh, Giacomo Acciarini, Thomas E. Berger, Atılım Güneş Baydin).
10/2023: "Bridging the Human-AI Knowledge Gap - Concept Discovery and Transfer in AlphaZero" (Lisa Schut, Nenad Tomasev, Tom McGrath, Demis Hassabis, Ulrich Paquet, Been Kim).
10/2023: "Managing AI Risks in an Era of Rapid Progress" (Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atılım Güneş Baydin, Sheila McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca Dragan, Philip Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann).

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:
05/2022: Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval (Pascal Notin).
12/2021: Improving black-box optimization in VAE latent space using decoder uncertainty (Pascal Notin).
11/2021: Disease variant prediction with deep generative models of evolutionary data (Pascal Notin).
07/2020: OATomobile: A research framework for autonomous driving (Angelos Filos, Panagiotis Tigas).
07/2020: Slurm for Machine Learning (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, Manchester, U of Amsterdam, U of Toronto, U of Cape Town, Yale, and others) and industry (Google, DeepMind, Twitter, Qualcomm, and startups).

We include 5 Rhodes Scholars, 3 Clarendon Scholars, 3 DeepMind Scholars, one cancer research UK Scholar, with our students funded by many additional sources (AIMS CDT, Cyber CDT, industry, and more). If you'd like to join us take a look here.

Current group members: Yarin Gal (Associate Professor) ● Freddie Kalaitzis (Senior Research Fellow, 2020) ● Tiarnan Doherty (Postdoc, 2022) ● Hazel Kim (PhD, 2023) ● Luckeciano Carvalho Melo (PhD, 2023) ● Matthew Kearney (PhD, 2023) ● Yonatan Gideoni (PhD, 2023) ● Katrina Dickson (Associate Member (Program Manager), 2023) ● Kunal Handa (MSc by Research, 2023) ● Ilia Shumailov (Associate Member (Senior Research Fellow), 2022) ● Gunshi Gupta (PhD, 2021) ● Kelsey Doerksen (PhD, 2021) ● Ruben Weitzman (PhD, 2021) ● Shreshth Malik (PhD, 2021) ● Jannik Kossen (PhD, 2020) ● Lisa Schut (PhD, 2020) ● Muhammed Razzak (PhD, 2020) ● Tuan Nguyen (Associate Member (PhD), 2020) ● Gabriel Jones (Associate Member (PhD), 2020) ● Freddie Bickford Smith (Associate Member (PhD), 2020) ● Angus Nicolson (Associate Member (PhD), 2020) ● Atılım Güneş Baydin (Associate Member (Faculty), 2020) ● Andrew Jesson (PhD, 2019) ● Jan Brauner (PhD, 2019) ● Jishnu Mukhoti (Associate Member (PhD), 2019) ● Pascal Notin (Associate Member (Senior Research Fellow), 2019) ● Tom Rainforth (Associate Member (Faculty), 2019) ● Tim G. J. Rudner (PhD, 2017) ● Sebastian Farquhar (Associate Member (Senior Research Fellow), 2017)


Group Invited Talks

Recent invited talks:
02 Nov 2021, 15:00, Zoom Owain Evans (Oxford).
18 Oct 2021, 15:00, Oxford Stanislav Fort (Oxford).
06 Jul 2021, 15:00, Zoom Pavel Izmailov (NYU).
16 Jun 2021, 15:00, Zoom Tamara Broderick (MIT).

Group Collaborators and Affiliates

Our group collaborators include:



And our group affiliates include:

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


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