Graph Neural Networks
Oct 26, 2023
Latent Causal Discovery in Reinforcement Learning and Large Language Models
Exploring identifiable latent causal structures to improve decision-making in reinforcement learning and interpretability in large language models.
Apr 30, 2022
AI for Science
Leveraging artificial intelligence and machine learning to address complex scientific challenges across diverse domains, including civil engineering, chemistry, fluid dynamics, plant biology, and materials science.
Apr 30, 2022
Advances in Differentiable DAG Learning: Analytic Constraints and Truncated Power Iteration
This project integrates two recent advances in differentiable DAG learning: (1) analytic DAG constraints for improved computational stability and (2) Truncated Matrix Power Iteration (TMPI) for escaping gradient vanishing. The methods are applied to causal discovery and structure learning in high-dimensional settings.
Oct 1, 2021