van der Schaar Lab

van der Schaar Lab at ICLR 2022: 5 papers accepted

The van der Schaar Lab’s researchers have had a total of 5 papers accepted to ICLR 2022 (April 25 – 29, 2022), matching last year’s strong performance.

ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science.

Collectively, these papers touch on some of the most important areas within the lab’s extensive research agenda, including machine learning interpretability, understanding and improving human learning and decision-making, uncertainty estimation, time series analysis, and genomics.

Titles, authors and abstracts for all 5 papers are provided below.

D-CODE: Discovering Closed-form ODEs from Observed Trajectories

Zhaozhi Qian, Krzysztof Kacprzyk, Mihaela van der Schaar

Abstract and URL

Self-Supervision Enhanced Feature Selection with Correlated Gates

Changhee Lee*, Fergus Imrie*, Mihaela van der Schaar

Abstract and URL

Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies

Alex Chan, Alicia Curth, Mihaela van der Schaar

Abstract and URL

Neural graphical modelling in continuous-time:
consistency guarantees and algorithms

Alexis Bellot, Kim Branson, Mihaela van der Schaar

Abstract

POETREE: Interpretable Policy Learning with Adaptive Decision Trees

Alizée Pace, Alex Chan, Mihaela van der Schaar

Abstract and URL

About ICLR

For a full list of the van der Schaar Lab’s publications at the top AI and ML conferences, click here.

Nick Maxfield

From 2020 to 2022, Nick oversaw the van der Schaar Lab’s communications, including media relations, content creation, and maintenance of the lab’s online presence.