arXiv Machine Learning July 9, 2026 By Roxana Barrios, Ioannis Sgouralis

Tensorized algorithms and scalable filtering methods for hidden Markov and factorial hidden Markov models

Read the original on arXiv Machine Learning →

arXiv:2607. 07008v1 Announce Type: cross Abstract: A common method for the representation and analysis of time-series data is the hidden Markov model (HMM), where each observation is associated with a hidden state that evolves over time.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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Your Probabilistic JEPA Is Secretly a Hidden Markov Model: A State-Space Interpretation of Joint-Embedding Predictive Learning

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