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20172023
most citedLearning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning

16 citations · 47 across the 11 of their papers we have counts for

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cs.LG2023★ 11 cited

The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold

Jialin Mao, Itay Griniasty, Han Kheng Teoh +5

We develop information-geometric techniques to analyze the trajectories of the predictions of deep networks during training. By examining the underlying high-dimensional probabilis…