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Thomas Lang

2 accepted papers

2026

Understanding and Improving Hyperbolic Deep Reinforcement Learning

ICLR 2026poster

The performance of reinforcement learning (RL) agents depends critically on the quality of the underlying feature representations. Hyperbolic feature spaces are well-suited for this purpose, as they naturally capture hierarchical and relational structure often present in complex RL environments. How…

Cited by 0SourcecodeScholar
2025

Breaking the Reclustering Barrier in Centroid-based Deep Clustering

ICLR 2025poster

This work investigates an important phenomenon in centroid-based deep clustering (DC) algorithms: Performance quickly saturates after a period of rapid early gains. Practitioners commonly address early saturation with periodic reclustering, which we demonstrate to be insufficient to address performa…