Summary of Learning Generalized Hamiltonians Using Fully Symplectic Mappings, by Harsh Choudhary et al.
Learning Generalized Hamiltonians using fully Symplectic Mappingsby Harsh Choudhary, Chandan Gupta, Vyacheslav kungrutsev, Melvin Leok,…
Learning Generalized Hamiltonians using fully Symplectic Mappingsby Harsh Choudhary, Chandan Gupta, Vyacheslav kungrutsev, Melvin Leok,…
Revising the Structure of Recurrent Neural Networks to Eliminate Numerical Derivatives in Forming Physics Informed…
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Learning Joint Models of Prediction and Optimizationby James Kotary, Vincenzo Di Vito, Jacob Cristopher, Pascal…
Unsupervised Adaptive Normalizationby Bilal Faye, Hanane Azzag, Mustapha Lebbah, Fangchen FangFirst submitted to arxiv on:…
Rethinking Deep Learning: Propagating Information in Neural Networks without Backpropagation and Statistical Optimizationby Kei ItohFirst…