5 papers
Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts
Yuanyuan Wang, Wenjie Wang, Haoxuan Li +2
Causal representation learning for time series has developed strong identifiability results in discrete-time latent causal models, but identifiability in continuous-time latent sto…
Causal Ensemble Agent: Hierarchical Causal Discovery with LLM-guided Expert Reweighting
Xinyu Li, Yuanyuan Wang, Haoxuan Li +7
Causal discovery aims to uncover causal structures from observational data, which is crucial for real-world decision-making. However, different causal discovery algorithms can prod…
AnisoLift: Anisotropic Latent Representations for Coarse Particle Liquid Enhancement
Zhengqing Gao, Huaxi Huang, Runqi Lin +6
Particle-based liquid simulation is widely used in graphics and physical modeling, but high-resolution rollouts remain computationally expensive. Consequently, many methods aim to…
Physics from Video: Identifiability of Time-Invariant Second-Order ODEs under Minimal Trajectory Conditions
Yuanyuan Wang, Wenjie Wang, Kun Zhang +1
Bridging the gap between visual realism and physical understanding is a core challenge for video-based world models. We study the structural identifiability of continuous-time phys…
Identifiability Analysis of Linear ODE Systems with Hidden Confounders
Yuanyuan Wang, Biwei Huang, Wei Huang +2
The identifiability analysis of linear Ordinary Differential Equation (ODE) systems is a necessary prerequisite for making reliable causal inferences about these systems. While ide…