Understanding and Preventing Capacity Loss in Reinforcement Learning

A new state of the art for unsupervised computer vision

Machine learning for medical imaging: methodological failures and recommendations for the future

Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients

Active Learning Helps Pretrained Models Learn the Intended Task

Learning to Induce Causal Structure

An optimized solution for face recognition

A practical guide to multi-objective reinforcement learning and planning

Multi-animal pose estimation, identification and tracking with DeepLabCut

The medical algorithmic audit