3 citations · 5 across the 5 of their papers we have counts for
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cs.LG2023
Training Neural Networks with Internal State, Unconstrained Connectivity, and Discrete Activations
Alexander Grushin
Today's most powerful machine learning approaches are typically designed to train stateless architectures with predefined layers and differentiable activation functions. While thes…
cs.LG2023★ 3 cited
Safety Margins for Reinforcement Learning
Alexander Grushin, Walt Woods, Alvaro Velasquez +1
Any autonomous controller will be unsafe in some situations. The ability to quantitatively identify when these unsafe situations are about to occur is crucial for drawing timely hu…