Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Auxiliary Tasks in Multi-task Learning

Reference implementation of "Faster Training of Mask R-CNN by Focusing on Instance Boundaries"

SXL: Spatially explicit learning of geographic processes with auxiliary tasks

Attend Before you Act: Leveraging human visual attention for continual learning

NeurIPS 2021: Learning State Representations from Random Deep Action-conditional Predictions

Investigating alternative auxiliary tasks in image classification.

Implementations for RL agents that seek to learn about their environment by predicting multiple signals from a single stream of experience.

Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning

An Empirical Study of Multitask Learning to Improve Open Domain Dialogue Systems, NoDaLiDa 2023