6 papers
Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling
Fan Feng, Yujia Zheng, Minghao Fu +5
Learning and planning in imagination using world models provides an effective paradigm for training agents for decision-making. However, existing approaches often rely on high-dime…
Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
Minghao Fu, Biwei Huang, Zijian Li +5
Understanding climate dynamics requires going beyond correlations in observational data to uncover the underlying causal process. Latent drivers such as atmospheric processes play…
Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making
Fan Feng, Selena Ge, Minghao Fu +6
Recent work has framed decision-making as a sequence modeling problem using generative models such as diffusion models. Although promising, these approaches often overlook latent f…
Differentiable Causal Discovery For Latent Hierarchical Causal Models
Parjanya Prashant, Ignavier Ng, Kun Zhang +1
Discovering causal structures with latent variables from observational data is a fundamental challenge in causal discovery. Existing methods often rely on constraint-based, iterati…
Natural Counterfactuals With Necessary Backtracking
Guang-Yuan Hao, Jiji Zhang, Biwei Huang +2
Counterfactual reasoning is pivotal in human cognition and especially important for providing explanations and making decisions. While Judea Pearl's influential approach is theoret…
Revisiting Differentiable Structure Learning: Inconsistency of Penalty and Beyond
Kaifeng Jin, Ignavier Ng, Kun Zhang +1
Recent advances in differentiable structure learning have framed the combinatorial problem of learning directed acyclic graphs as a continuous optimization problem. Various aspects…