Postdoc, , Johannes Kepler Universität Linz
2 papers at NeurIPS 2025
We propose GyroSwin, a 5D Swin Transformer to learn a 5D PDE commonly encountered in Gyrokinetics to simulate turbulence in a nuclear fusion reactor.
We propose EVA, a parameter-efficient fine-tuning method that initalizes LoRA weights in a variance-optimal manner and performs adaptive rank allocation to provably maximize the expected gradient signal at the beginning of fine-tuning.
