DFG proposal accepted

We are excited to announce that the funding proposal Long-term and Few-shot Action Anticipation using Causal Representation Learning has been approved by the German Research Foundation (DFG)! The project will also include a collaboration with Mercator Fellow Prof. Kun Zhang from CMU.

The goal of this project is to develop computational methods for causal representation learning for long-term and few-shot action anticipation. Action anticipation and proactive adaptation are key for efficient human-AI collaboration. We will specifically study settings in which an AI system parses video recordings of humans to learn structural causal models of their behaviour.

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