Associate Professor, University of California, Irvine
3 papers at NeurIPS 2025
We propose a unified transformer framework to model mixed-type event sequences
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.
This paper introduces a collection of time-series anomaly detection datasets.
