Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts
cs.LG, stat.ML
Submitted: 2026-06-26
Updated: 2026-10-01
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Disentangling Dynamical Systems: Causal Representation Learning Meets Local Sparse Attention
- TRACE: Trajectory Recovery for Continuous Mechanism Evolution in Causal Representation Learning
- Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots
- Causal Representation Meets Stochastic Modeling under Generic Geometry
- Towards Identifiability of Interventional Stochastic Differential Equations
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