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cs.LG2023★ 2 cited
Symplectic Autoencoders for Model Reduction of Hamiltonian Systems
Benedikt Brantner, Michael Kraus
Many applications, such as optimization, uncertainty quantification and inverse problems, require repeatedly performing simulations of large-dimensional physical systems for differ…
cs.LG2023
Generalizing Adam to Manifolds for Efficiently Training Transformers
Benedikt Brantner
One of the primary reasons behind the success of neural networks has been the emergence of an array of new, highly-successful optimizers, perhaps most importantly the Adam optimize…