13 skills found
spatstat / SpatstatUmbrella package of the 'spatstat' family................
blei-lab / HdpHierarchical Dirichlet processes. Topic models where the data determine the number of topics. This implements Gibbs sampling.
arnim / HDPGibbs sampler 4 the Hierarchical Dirichlet Process
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Bureaucratic overreach and environmental catastrophe are precisely the kinds of slow-moving existential challenges that democracies deal with very badly.... Finally, there is the threat du jour: corporations and the technologies they promote." (pp. 56–57.)
shaharpit809 / Machine Learning For Signal ProcessingThis repository consists of work done in Machine Learning and Signal Processing. Machine Learning Stage consists of: * K-means * Expectation Maximization * Principal Component Analysis (PCA) * Mixture Models * Hidden Markov Models (HMM) * Graphical Models * Gibbs Sampling * Manifold Learning * Hashing Signal Processing Stage consists of : * Source Separation * Stereo Matching * Audio Processing * Fourier Transform * Brain Waves * Keyword Detection * Sentiment Analysis * Music Signal Processing * Image Segmentation
ZiyangS / IGMMinfinite Gaussian Mixture Model(Dirichlet Process Gaussian Mixture Model) by gibbs sampling. Multivaraite Gaussian with full covariance and diagonal covariance.
laurimi / Ddcrp GibbsGibbs sampler for the Distance Dependent Chinese Restaurant Process
intoraw / Dpmmdirichlet process mixture model, using gibbs sampling
kleinschmidt / Hdp Bayes VowelsHierarchical Dirichlet Process vowel-acquisition device Gibbs sampler (e.g. Feldman et al., 2009)
aaadriano / 672 Statistical LearningKernel Principal Component Analysis, Spectral Clustering, Gaussian Processes, RKHS of vector-valued functions, RKHS embedding of the realization of random variables, Tests of independence and conditional independence, Bayesian networks, k-means, mixture models, the expectation maximization algorithm, Markov random fields, Gibbs distributions, belief propagation algorithms, variational inference, Markov chain Monte Carlo.
zhoufeng6288 / DFN HawkesThe repository implements three inference methods (Gibbs sampler, EM algorithm and mean-field approximation) for the sigmoid nonlinear multivariate Hawkes processes (SNMHP) and its dynamic version (dynamic-SNMHP) in the paper "Efficient Inference for Dynamic Flexible Interactions of Neural Populations".
spatstat / Spatstat.modelSub-package of spatstat containing functionality for parametric modelling and inference
JullesMitoura / Tes ThermoThis is the TeS library, a tool designed for simulating reaction processes using isothermal and adiabatic reactors using Gibbs minimization and entropy maximization, respectively.
