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stat.ML2023
Context-specific kernel-based hidden Markov model for time series analysis
Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga +1
Traditional hidden Markov models have been a useful tool to understand and model stochastic dynamic data; in the case of non-Gaussian data, models such as mixture of Gaussian hidde…
stat.ML2020★ 3 cited
Sparse Cholesky covariance parametrization for recovering latent structure in ordered data
Irene Córdoba, Concha Bielza, Pedro Larrañaga +1
The sparse Cholesky parametrization of the inverse covariance matrix can be interpreted as a Gaussian Bayesian network; however its counterpart, the covariance Cholesky factor, has…