Our recent preprint develops an architecture and a training method to give latent states physical meaning in the context of trajectory prediction:
- Zhenjiang Mao, Ivan Ruchkin.
Towards Physically Interpretable World Models: Meaningful Weakly Supervised Representations for Visual Trajectory Prediction [Arxiv] [Poster].
Preprint, 2024.