PhD student, University of California, Irvine
2 papers at NeurIPS 2025
We propose OmniCast, a scalable and skillful probabilistic model that unifies weather forecasting across timescales.
We propose a method that unifies deterministic feed‑forward rendering with autoregressive diffusion to synthesize photorealistic novel views from sparse inputs in a single transformer framework.
