Biwei Huang

Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks

Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

Causal Representation Meets Stochastic Modeling under Generic Geometry

I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making

A Fast Kernel-based Conditional Independence Test with Application to Causal Discovery

Transformer Is Inherently a Causal Learner

Towards Identifiable Latent Additive Noise Models

Backdoor Attribution: Elucidating and Controlling Backdoor in Language Models

Auto-scaling Continuous Memory for GUI Agent

Learning Modal-mixed Chain-of-thought Reasoning with Latent Embedding

Sparse World Models: Visual World Modeling with Sparse Representations

Learning Task-Sufficient World Models via Intervention-Curriculum Co-Design

Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems

Towards General Continuous Memory for Vision-Language Models

Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models

Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations

Analytic DAG Constraints for Differentiable DAG Learning

Practical Kernel Selection for Kernel-based Conditional Independence Test

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

Differentiable Causal Discovery for Latent Hierarchical Causal Models

A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery

MissScore: High-Order Score Estimation in the Presence of Missing Data

Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning

Revisiting Differentiable Structure Learning: Inconsistency of $\ell_1$ Penalty and Beyond

Identification of Nonparametric Dynamic Causal Model and Latent Process for Climate Analysis

Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning

Turning Challenges into Opportunities: How Distribution Shifts Enhance Identifiability in Causal Representation Learning

Practical Kernel Learning for Kernel-based Conditional Independent Test

MissScore: High-Order Score Estimation in the Presence of Missing Data

TrendDiff: Decoupling Intrinsic and Measurement Trends for Enhanced Time Series Causal Discovery

Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders

Unified Framework for Causal Discovery and Long-term Forecasting in Non-stationary Environments