Global ETD Search
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Showing 1 to 7 of 7 for “"Hierarchical Dirichlet processes"”.
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Permutation-based Significance Tests for Multi-modal Hierarchical Dirichlet Processes with Application to Audio-visual Data
… in a meaningful way. We explore the multi-modal hierarchical Dirichlet process (mmHDP) mixture model as a Bayesian non-parametric approach to data fusion. In particular, we elaborate on its censored-data perspective, which aligns groups of observations at a group level to accommodate for missing …
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Advances in Hierarchical Probabilistic Multimodal Data Fusion
… we develop a multimodal extension to hierarchical Dirichlet processes (mmHDPs) where, in contrast to the setting for LDF, we lack observation-level correspondences across modalities and the data arise from an implicit latent variable model. Finally, we develop a novel representation …
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Computational discovery of gene modules, regulatory networks and expression programs
… I present GeneProgram, a framework based on Hierarchical Dirichlet Processes, which uses large compendia of mammalian expression data to simultaneously organize genes into overlapping programs and tissues into groups to produce maps of expression programs. I demonstrate that GeneProgram …
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Efficient Bayesian Nonparametric Methods for Model-Free Reinforcement Learning in Centralized and Decentralized Sequential Environments
… we study Q learning with Gaussian processes to solve Markov decision processes, and we also employ hierarchical Dirichlet processes as the prior for the control policy parameters to solve partially observable Markov decision processes. For decentralized partially observable Markov …
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Nonparametric Methods for Analysis and Modeling of Complex Multivariate Distributions
… compared. We introduce a Bayesian nonparametric hierarchical modeling approach for accomplishing both calibration and cell classification jointly in a unified probabilistic manner. Three important features of our method make it particularly effective for analyzing multi-sample flow cytometry …
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Probabilistic modelling of somatic alterations in bulk tissue and single cells using repeat DNA
Chromosomal instability characterises several cancer types, in which large-scale structural alterations of the genome accumulate at an increased rate. An important class of structural alterations are somatic copy number alterations (SCNAs). SCNAs have been shown to be major drivers of oncogenesis …