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Paul Mattes

2 accepted papers

2026

SIR: Structured Image Representations for Explainable Robot Learning

CVPR 2026

Existing robot policies based on learned visual embeddings lack explicit structure and are sensitive to visual distractions.Thus, the representations that drive their behaviour are often opaque, making their decision-making process difficult to interpret.To address this, we introduce Structured Imag

Cited by 0SourceScholar
2024

Hieros: Hierarchical Imagination on Structured State Space Sequence World Models

ICML 2024poster

One of the biggest challenges to modern deep reinforcement learning (DRL) algorithms is sample efficiency. Many approaches learn a world model in order to train an agent entirely in imagination, eliminating the need for direct environment interaction during training. However, these methods often suf…