optim
Exploration and implementation of state-of-the-art deep learning optimization algorithms in PyTorch.
A research project for implementing, benchmarking, and analyzing modern deep learning optimizers. Built in PyTorch with potential extensions to JAX.
The repository serves as an active playground for experimenting with novel optimization techniques relevant to fractional-order gradient methods, adaptive learning rate schedules, and training paradigms for scientific computing applications.