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cs.LG2024
Using Part-based Representations for Explainable Deep Reinforcement Learning
Manos Kirtas, Konstantinos Tsampazis, Loukia Avramelou +2
Utilizing deep learning models to learn part-based representations holds significant potential for interpretable-by-design approaches, as these models incorporate latent causes obt…
cs.LG2023★ 11 cited
Multiplicative update rules for accelerating deep learning training and increasing robustness
Manos Kirtas, Nikolaos Passalis, Anastasios Tefas
Even nowadays, where Deep Learning (DL) has achieved state-of-the-art performance in a wide range of research domains, accelerating training and building robust DL models remains a…