Current Research

Data & Evaluation. Create new data engines. Create benchmarks that are formally verifed. Unify scientific inverse problems into common frameworks.

Models & Architecture. Create new effective representations, such as for time series.

Inference & Search. Develop principled Bayesian inference methods using diffusion priors. Develop self-training for LLM-based tree search.