Department of Computer Science (OATML)

Oxford Applied and Theoretical Machine Learning group.

Epistemic Overview

About the Institute

The Oxford Applied and Theoretical Machine Learning Group (OATML) is at the heart of machine learning research at the University of Oxford, focusing on advancing the theory and application of ML.

Key Facts

Founded

1957

Director / President

Prof Yarin Gal (group lead)

Category

University Department / Research Group

Research Domains

machine learning
theory
deep learning

Timeline

1957

Parent entity, the 'Oxford University Computing Laboratory' (now Dept. of Computer Science), is founded.

c. 2015

The OATML research group begins to form around the work of Prof. Yarin Gal.

2016

Publication of 'Dropout as a Bayesian Approximation', a foundational paper for the group and for the field of Bayesian Deep Learning.

2017

Group lead Yarin Gal named to Forbes 30 Under 30 Europe.

2019

Publication of 'Bayesian-Optimized-Dropout' paper, furthering the group's work on uncertainty.

2023

Group lead Yarin Gal is appointed as a Full Professor of Machine Learning at the department.

2024

Group actively publishes research on topics like uncertainty in diffusion models and scalable Bayesian deep learning.

Events

  • The main Department of Computer Science hosts a 'Distinguished Speaker Series', but no OATML-specific events were found.

Influential Papers / Notable Research

  • Pioneering research in Bayesian Deep Learning and uncertainty quantification.

  • Seminal work on 'Dropout as a Bayesian Approximation', a widely used technique in deep learning.

  • Development of models for reliable and robust AI, particularly in machine vision and autonomous systems.