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cs.LG2024
Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics
Charlotte Beylier, Simon M. Hofmann, Nico Scherf
The learning process of a reinforcement learning (RL) agent remains poorly understood beyond the mathematical formulation of its learning algorithm. To address this gap, we introdu…
cs.LG2024
EEG-Features for Generalized Deepfake Detection
Arian Beckmann, Tilman Stephani, Felix Klotzsche +8
Since the advent of Deepfakes in digital media, the development of robust and reliable detection mechanism is urgently called for. In this study, we explore a novel approach to Dee…