News

Lewis Smith publishes paper in Nature Scientific Reports
31 Mar 2021
OATML graduate student Lewis Smith’s work as part of FDL 2019 was published as a full length paper in Scientific Reports. This work was a collaboration between the four members of his team, and academics from several universities.

Pascal Notin to speak at the Cornell ML in Medicine seminar series
19 Mar 2021
OATML graduate student Pascal Notin will give an invited talk on Uncertainty in deep generative models with applications to genomics and drug design at the Cornell Machine Learning in Medicine seminar series.

Tim G. J. Rudner releases paper series on AI safety
17 Mar 2021
OATML graduate student Tim G. J. Rudner wrote a paper series on AI safety for non-experts (An Overview, Robustness, Interpretability).

Pascal Notin to speak at the EMBL workshop on ML in Drug Discovery
11 Mar 2021
OATML graduate student Pascal Notin will give an invited talk on “Large-scale clinical interpretation of genetic variants using evolutionary data and deep generative models” at the EMBL-EBI workshop on Machine Learning in Drug Discovery. The work is a collaboration between OATML and the Marks Lab at Harvard.

Seb Farquhar to speak at UCL AI Centre Seminar Series
10 Feb 2021
OATML graduate student Seb Farquhar will speak on approximate Bayes in large neural networks drawing on Liberty or Depth (NeurIPS 2020) and Radial BNNs (AI Stats 2020) at the UCL Centre for Artificial Intelligence Seminar Series.

Five papers with OATML members accepted to ICLR 2021
15 Jan 2021
Five papers with OATML members accepted to ICLR 2021:
- Invariant Representations for Reinforcement Learning without Reconstruction
- Improving Transformation Invariance in Contrastive Representation Learning
- On Statistical Bias In Active Learning: How and When to Fix It
- Improving VAEs’ Robustness to Adversarial Attack
- Capturing Label Characteristics in VAEs

Tim G. J. Rudner to speak at Max Planck Institute & UCLA
17 Dec 2020
OATML graduate student Tim G. J. Rudner will give an invited talk on Outcome-Driven Reinforcement Learning via Variational Inference at the MPI+UCLA Mathematical Machine Learning Seminar.

Tim G. J. Rudner to give guest lecture at UCL
16 Dec 2020
OATML graduate student Tim G. J. Rudner will give an invited guest lecture on Bayesian Deep Learning at University College London.

Tim G. J. Rudner to speak at Center for Security & Emerging Technology
16 Dec 2020
OATML graduate student Tim G. J. Rudner will give an invited talk on “A Non-technical Guide to Modern Machine Learning” at the Georgetown University’s Center for Security & Emerging Technology.

OATML researchers publish paper in Science
15 Dec 2020
The paper called “Inferring the effectiveness of government interventions against COVID-19” was published in Science today. The work is a collaboration with researchers from 9 universities, led by OATML graduate students Sören Mindermann and Jan Brauner, together with Mrinank Sharma from the Department of Statistics.

Oxford-Google Workshop on Reliable Machine Learning
24 Nov 2020
OATML hosted a joint workshop with Google Research on reliable machine learning with a series of talks and breakout sessions. The event was organized by OATML graduate student Tim G. J. Rudner and Mario Lučić at Google.

Freddie Kalaitzis to give a spotlight talk at the AI for Earth Sciences workshop at NeurIPS 2020
05 Nov 2020
OATML Senior Research Fellow Freddie Kalaitzis will be giving a Spotlight Talk on Dynamic Hydrology Maps from Satellite-LiDAR Fusion at the AI for Earth Sciences workshop at NeurIPS 2020.

Tim G. J. Rudner receives Outstanding Reviewer Award
01 Nov 2020
OATML graduate student Tim G. J. Rudner received a best reviewer award (top 10%) at NeurIPS 2020.

Sören Mindermann and Jan Brauner speak at the German Centre for Infection Research
26 Oct 2020
OATML graduate students Sören Mindermann and Jan Brauner, together with Mrinank Sharma from the Department of Statistics, were invited to give a talk on their work on ‘inferring the effects of non-pharmaceutical interventions against COVID-19’, at the German Centre for Infection Research/University of Cologne.

Tim G. J. Rudner to speak at University of Cambridge
16 Oct 2020
OATML graduate student Tim G. J. Rudner will give an invited talk on Inter-domain Deep Gaussian Processes at the University of Cambridge’s ML@CS Seminar.

Angelos Filos co-organising NeurIPS 2020 Workshop on Talking to Strangers: Zero-Shot Emergent Communication
13 Oct 2020
OATML DPhil student Angelos Filos is co-organising the NeurIPS 2020 Workshop on Talking to Strangers: Zero-Shot Emergent Communication.

Lisa Schut presents at Accenture Turing Innovation Symposium
02 Oct 2020
OATML graduate student Lisa Schut presented alongside Rory McGrath, from Accenture Labs, on “Counterfactual Explanations: Making AI decision-making more useful and trustworthy.” The research presented was joint work with Oscar Key, in collaboration with Accenture Labs.

Tim G. J. Rudner invited to join OECD AI Working Groups
01 Oct 2020
OATML graduate student Tim G. J. Rudner has joined the OECD’s Working Groups on Trustworthy AI and AI Classification as an invited expert.

Clare Lyle to speak at Simons Institute
29 Sep 2020
OATML graduate student Clare Lyle will be giving a talk on causal inference and generalization in deep reinforcement learning at the Simons Institute Workshop on Deep Reinforcement Learning on Thursday October 1.

Yarin Gal to give Keynote at MICCAI UNSURE workshop
26 Sep 2020
Prof Yarin Gal will give a keynote talk at the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE) workshop at the Medical Image Computing and Computer Assisted Intervention (MICCAI) conference. He will discuss work done at OATML on AI in medical imaging. The talk will cover work on topics ranging from data efficient AI to safe and interpretable AI.

Six papers with OATML members accepted to NeurIPS 2020
25 Sep 2020
Six papers with OATML members accepted to NeurIPS 2020:
- Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
- Identifying Causal Effect Inference Failure with Uncertainty-Aware Models
- On the robustness of effectiveness estimation of nonpharmaceutical interventions against COVID-19 transmission
- Calibrating Deep Neural Networks using Focal Loss
- A Bayesian Perspective on Training Speed and Model Selection
- Neural Architecture Generator Optimization


Tim G. J. Rudner to speak at UCL Centre for AI
13 Aug 2020
OATML graduate student Tim G. J. Rudner will give an invited talk on Inter-domain Deep Gaussian Processes at the UCL Centre for AI’s Statistical Machine Learning Seminar.

Clare Lyle awarded OpenPhil AI Fellowship
09 Jun 2020
OATML graduate student Clare Lyle has been selected for the 2020 Open Philanthropy AI Fellowship. The fellowship will support her research for five years.

Five papers with OATML members accepted to ICML 2020
08 Jun 2020
Five papers with OATML members accepted to ICML 2020:
- Invariant Causal Prediction for Block MDPs
- Uncertainty Estimation Using a Single Deep Deterministic Neural Network
- Inter-domain Deep Gaussian Processes
- Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support
- Can autonomous vehicles identify, recover from, and adapt to distribution shifts?

OATML graduate students to speak at Africa CDC on COVID-19
06 Jun 2020
OATML graduate students Jan Brauner and Sören Mindermann will give an invited talk at Africa CDC, Africa’s intercontinental public health agency, on June 12. They will present their work on nonpharmacetical interventions against COVID-19 to the COVID-19 modelling group.

Joost van Amersfoort to speak at Waymo and Rutherford Appleton Laboratory
06 Jun 2020
OATML graduate student Joost van Amersfoort was invited to talk on deterministic uncertainty quantification (DUQ) at Waymo (March 27th) and Rutherford Appleton Laboratory (June 18th).

Uncertainty in Brain Tumor Segmentation Challenge
05 Jun 2020
We’re organising the second “Quantification of Uncertainty in Segmentation” task as part of the Multimodal Brain Tumor Segmentation Challenge at MICCAI 2020, together with Angelos Filos, Raghav Mehta and Tal Arbel.

Bayesian deep learning for all humankind
14 Jan 2020
Our work with NASA and ESA over the past few years, together with Lewis Smith and Tim G. J. Rudner, is summarised in a recent article written by James Parr. Read more in Inspired: Bayesian deep learning for all humankind

MIT Technology Review names Yarin Gal on their Innovators Under 35 Europe 2019 list
19 Dec 2019
Since 1999, MIT Technology Review has recognised young innovators and talented entrepreneurs from different countries who are developing new technologies to help solve the problems that affect our society. Yarin has been included in the ‘pioneers’ category. Read more: AI still makes mistakes, but his tools can alert us when a system is about to go wrong

25 papers by OATML authors at NeurIPS 2019
08 Dec 2019
We are glad to share 25 papers by OATML authors and collaborators presented at NeurIPS 2019 conference and workshops. Read more: blog post

Yarin Gal announced as Turing AI Fellow
24 Oct 2019
Yarin Gal is one of five new Turing AI Fellows announced by The Alan Turing Institute. The Office for Artificial Intelligence, The Alan Turing Institute and UK Research and Innovation (UKRI) have worked together to successfully attract the Turing AI Fellows, some of the best research talent from around the world. Yarin will work on democratising safe and robust AI. Read more: Turing AI Fellows

Six group members honoured as NeurIPS top reviewers
07 Sep 2019
Six group members honoured as top reviewers at NeurIPS 2019: 2 members among the top 400 highest scoring reviewers and awarded free registration (Tim G. J. Rudner and Sebastian Farquhar), and 4 among the top 50% reviewers (Zac Kenton, Andreas Kirsch, Angelos Filos and Joost van Amersfoort).

Five papers with OATML members accepted to NeurIPS 2019
07 Sep 2019
Five papers with OATML members accepted to NeurIPS 2019:
- BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
- A Geometric Perspective on Optimal Representations for Reinforcement Learning
- VIREL: A Variational Inference Framework for Reinforcement Learning
- Variational Bayesian Optimal Experimental Design
- On the Benefits of Disentangled Representations

Angelos Filos co-organising NeurIPS 2019 Workshop on Emergent Communication: Towards Natural Language
01 Sep 2019
OATML DPhil student Angelos Filos is co-organising the NeurIPS 2019 Workshop on Emergent Communication: Towards Natural Language.

Aidan Gomez to speak at Deep Learning Indaba
20 Aug 2019
OATML graduate student Aidan Gomez will be presenting the Recurrent Neural Networks session with Kris Sankaran at Deep Learning Indaba on Tuesday 27 August. Schedule is available here and slides are available here.

Uncertainty in Brain Tumor Segmentation Challenge
15 Aug 2019
We’re organising a “Quantification of Uncertainty in Segmentation” task as part of the Multimodal Brain Tumor Segmentation Challenge at MICCAI 2019, together with Angelos Filos, Raghav Mehta and Tal Arbel.

Fourth Bayesian Deep Learning Workshop
01 Aug 2019
We’re organising the Fourth Bayesian Deep Learning Workshop at NeurIPS 2019.

Two OATML students received ICML 2019 Outstanding Reviewer Awards
02 Jun 2019
OATML DPhil students Lewis Smith and Tim G. J. Rudner received ICML 2019 Outstanding Reviewer Awards (top 5% of reviewers).

Yarin Gal to speak at the European Space Agency
01 Jun 2019
Prof Yarin Gal will be speaking at the European Space Agency’s Phi-week, discussing work done at OATML on AI in space. The talk will cover work on topics ranging from exoplanet atmospheric retrieval to asteroid shape modelling from radar data.

Angelos Filos' paper accepted for oral presentation at ICML 2019 Workshop
15 May 2019
OATML graduate student Angelos Filos will present his paper ‘Inverse Reinforcement Learning for Limit Order Book Dynamics’ at the the ICML 2019 Workshop on Applications and Infrastructure for Multi-Agent Learning, with the paper selected for an oral presentation.

Yarin Gal to speak at the Royal Society's Summer Science Exhibition on AI and Art
02 May 2019
Prof Yarin Gal will be speaking at the Royal Society’s Summer Science Exhibition on 6 July, discussing work on AI and art. The talk will cover techniques in machine learning that give us the chance to venture beyond the frame of some famous paintings.

Aidan Gomez awarded OpenPhil AI Fellowship
01 May 2019
OATML graduate student Aidan Gomez has been selected for the 2019 Open Philanthropy AI Fellowship. The fellowship will support his research for five years.

Aidan Gomez co-organising ICML 2019 Workshop on Invertible Neural Nets and Normalizing Flows
15 Apr 2019
OATML DPhil student Aidan Gomez is co-organising the ICML 2019 Workshop on Invertible Neural Nets and Normalizing Flows together with Aaron Courville and Danilo Rezende.

Yarin Gal to speak at the UN summit on "AI for Good"
02 Apr 2019
Prof Yarin Gal will give a talk at the UN summit on “AI for Good” on the development of AI which we can trust: How can we develop trust-worthy machine learning tools to be deployed in the wild? He will further participate in a panel discussion on the topic IT’S A MATTER OF TRUST.

NeurIPS and UAI papers
17 Oct 2018
The Publications page has been updated with NeurIPS and UAI papers.

Third Bayesian Deep Learning Workshop
17 Oct 2018
We’re organising the Third Bayesian Deep Learning Workshop at NeurIPS 2018.