70 citations · 170 across the 13 of their papers we have counts for
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cs.LG2023
Bag of Policies for Distributional Deep Exploration
Asen Nachkov, Luchen Li, Giulia Luise +2
Efficient exploration in complex environments remains a major challenge for reinforcement learning (RL). Compared to previous Thompson sampling-inspired mechanisms that enable temp…
cs.LG2023★ 31 cited
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero +3
Message Passing Neural Networks (MPNNs) are instances of Graph Neural Networks that leverage the graph to send messages over the edges. This inductive bias leads to a phenomenon kn…