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Found 4 papers, 0 papers with code
Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models
In machine learning, a nonparametric forecasting algorithm for time series data has been proposed, called the kernel spectral hidden Markov model (KSHMM).
Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models
Our contribution in this paper is to introduce a novel approach, termed the {\em model-based kernel sum rule} (Mb-KSR), to combine a probabilistic model and kernel Bayesian inference.
Characteristic Kernels and Infinitely Divisible Distributions
If $P, Q$, and kernel $k$ are Gaussians, then computation (i) and (ii) results in Gaussian pdfs that is tractable.
Filtering with State-Observation Examples via Kernel Monte Carlo Filter
In particular, the sampling and resampling procedures are novel in being expressed using kernel mean embeddings, so we theoretically analyze their behaviors.
