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Component isolation for multi-component signal analysis using a non-parametric Gaussian latent feature model
A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly
time-varying signals especially when they are overlapped in time and frequency plane. In …
time-varying signals especially when they are overlapped in time and frequency plane. In …
Random function priors for correlation modeling
The likelihood model of high dimensional data $ X_n $ can often be expressed as $ p (X_n|
Z_n,\theta) $, where $\theta\mathrel {\mathop:}=(\theta_k) _ {k\in [K]} $ is a collection of …
Z_n,\theta) $, where $\theta\mathrel {\mathop:}=(\theta_k) _ {k\in [K]} $ is a collection of …
[КНИГА][B] Composing Deep Learning and Bayesian Nonparametric Methods
A Zhang - 2019 - search.proquest.com
Recent progress in Bayesian methods largely focus on non-conjugate models featured with
extensive use of black-box functions: continuous functions implemented with neural …
extensive use of black-box functions: continuous functions implemented with neural …