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A Physics-Inspired Optimizer: Velocity Regularized Adam

Pranav Vaidhyanathan, Lucas Schorling, Natalia Ares, Maike Osborne
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arXiv:2505.13196v3 Announce Type: replace-cross Abstract: We introduce Velocity-Regularized Adam (VRAdam), a physics-inspired optimizer for training deep neural networks that draws on ideas from quartic terms for kinetic energy with its stabilizing effects on various system dynamics. Previous algorithms, including the ubiquitous Adam, operate at...

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