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stat.ML2026
End-to-End Identifiable and Consistent Recurrent Switching Dynamical Systems
Carles Balsells-Rodas, Zhengrui Xiang, Xavier Sumba +1
Learning identifiable representations in deep generative models remains a fundamental challenge, particularly for sequential data with regime-switching dynamics. Existing approache…
stat.ML2024
Identifying Nonstationary Causal Structures with High-Order Markov Switching Models
Carles Balsells-Rodas, Yixin Wang, Pedro A. M. Mediano +1
Causal discovery in time series is a rapidly evolving field with a wide variety of applications in other areas such as climate science and neuroscience. Traditional approaches assu…
stat.ML2023
On the Identifiability of Switching Dynamical Systems
Carles Balsells-Rodas, Yixin Wang, Yingzhen Li
The identifiability of latent variable models has received increasing attention due to its relevance in interpretability and out-of-distribution generalisation. In this work, we st…