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cs.LG2023
Learning to simulate partially known spatio-temporal dynamics with trainable difference operators
Xiang Huang, Zhuoyuan Li, Hongsheng Liu +4
Recently, using neural networks to simulate spatio-temporal dynamics has received a lot of attention. However, most existing methods adopt pure data-driven black-box models, which…
cs.LG2021
Layer-Parallel Training of Residual Networks with Auxiliary-Variable Networks
Qi Sun, Hexin Dong, Zewei Chen +3
Gradient-based methods for the distributed training of residual networks (ResNets) typically require a forward pass of the input data, followed by back-propagating the error gradie…