179 citations · 294 across the 16 of their papers we have counts for
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hep-lat2022★ 5 cited
Aspects of scaling and scalability for flow-based sampling of lattice QCD
Ryan Abbott, Michael S. Albergo, Aleksandar Botev +10
Recent applications of machine-learned normalizing flows to sampling in lattice field theory suggest that such methods may be able to mitigate critical slowing down and topological…
cs.LG2022★ 1 cited
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers
Guodong Zhang, Aleksandar Botev, James Martens
Training very deep neural networks is still an extremely challenging task. The common solution is to use shortcut connections and normalization layers, which are both crucial ingre…