A Physics-Inspired Optimizer: Velocity Regularized Adam
Researchers introduce Velocity-Regularized Adam (VRAdam), a physics-inspired optimizer that improves deep neural network training by adding velocity-based regularization to prevent oscillations and instability. VRAdam demonstrates superior performance compared to standard optimizers like AdamW across multiple benchmarks including image classification, language modeling, and generative modeling tasks.