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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:
07/2023: "Question Decomposition Improves the Faithfulness of Model-Generated Reasoning" (A Radhakrishnan, K Nguyen,, A Chen, C Chen, C Denison, D Hernandez, E Durmus, E Hubinger, J Kernion, K Lukosiute, N Cheng, N Joseph, N Schiefer, O Rausch, S McCandlish, S El Showk, T Lanham, T Maxwell, V Chandrasekaran, Z Hatfield-Dodds, J Kaplan, Jan Brauner, SR Bowman, E Perez).
07/2023: "Measuring Faithfulness in Chain-of-Thought Reasoning" (Tamera Lanham, Anna Chen, Ansh Radhakrishnan, Benoit Steiner, Carson Denison, Danny Hernandez, Dustin Li, Esin Durmus, Evan Hubinger, Jackson Kernion, Kamile Lukosiute, Karina Nguyen, Newton Cheng, Nicholas Joseph, Nicholas Schiefer, Oliver Rausch, Robin Larson, Sam McCandlish, Sandipan Kundu, Saurav Kadavath, Shannon Yang, Thomas Henighan, Timothy Maxwell, Timothy Telleen-Lawton, Tristan Hume, Zac Hatfield-Dodds, Jared Kaplan, Jan Brauner, Samuel R. Bowman, Ethan Perez).
06/2023: "BatchGFN: Generative Flow Networks for Batch Active Learning" (Shreshth Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal).

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) ● Katrina Dickson (Associate Member (Program Manager), 2023) ● Gunshi Gupta (PhD, 2021) ● Kelsey Doerksen (PhD, 2021) ● Lorenz Kuhn (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) ● Pascal Notin (PhD, 2019) ● Sören Mindermann (PhD, 2019) ● Jishnu Mukhoti (Associate Member (PhD), 2019) ● Tom Rainforth (Associate Member (Faculty), 2019) ● Panagiotis Tigas (PhD, 2018) ● 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


We are located at
Department of Computer Science, University of Oxford
Wolfson Building
Parks Road
Twitter: @OATML_Oxford
Github: OATML