119 citations · 168 across the 14 of their papers we have counts for
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cs.LG2023★ 4 cited
Learning Environment Models with Continuous Stochastic Dynamics
Martin Tappler, Edi Muškardin, Bernhard K. Aichernig +1
Solving control tasks in complex environments automatically through learning offers great potential. While contemporary techniques from deep reinforcement learning (DRL) provide ef…
cs.LG2023
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth
Edi Muškardin, Martin Tappler, Ingo Pill +2
We examine the assumption that the hidden-state vectors of recurrent neural networks (RNNs) tend to form clusters of semantically similar vectors, which we dub the clustering hypot…