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Stochastic variational inference for clustering short text data with finite mixtures of Dirichlet-Multinomial distributions

• Authors : Bilancia, Massimo; Nigri, Andrea; Magro, Samuele ...

• Source: Statistical Papers ; volume 66, issue 4 ; ISSN 0932-5026 1613-9798

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Stochastic variational inference for scalable non-stationary Gaussian process regression

• Authors : Paun, Ionut; Husmeier, Dirk; Torney, Colin J. ...

• Source: Statistics and Computing ; volume 33, issue 2 ; ISSN 0960-3174 1573-1375

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State estimation of a physical system with unknown governing equations

• Authors : Course, Kevin; Nair, Prasanth B.

• Source: Nature ; volume 622, issue 7982, page 261-267 ; ISSN 0028-0836 1476-4687

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A scalable variational inference approach for increased mixed-model association power

• Authors : Loya, Hrushikesh; Kalantzis, Georgios; Cooper, Fergus

• Source: Nature Genetics ; volume 57, issue 2, page 461-468 ; ISSN 1061-4036 1546-1718

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Deep latent force models: ODE-based process convolutions for Bayesian deep learning

• Authors : Baldwin-McDonald, Thomas; Shi, Xinxing; Shen, Mingxin ...

• Source: Machine Learning ; volume 114, issue 8 ; ISSN 0885-6125 1573-0565

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Manifold learning by a deep Gaussian process autoencoder

• Authors : Francesco Camastra; Angelo Casolaro; Gennaro Iannuzzo

Subjects: Manifold learning, Deep Guassian processes, Variational autoencoders, Clustering indices

• Source: Neural Computing and Applications. 35:15573-15582

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Unifying supervised learning and VAEs: coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions

• Authors : Glüsenkamp, Thorsten

• Source: The European Physical Journal C ; volume 84, issue 2 ; ISSN 1434-6052

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Stochastic variational variable selection for high-dimensional microbiome data

• Authors : Dang, Tung; Kumaishi, Kie; Usui, Erika ...

• Source: Microbiome ; volume 10, issue 1 ; ISSN 2049-2618

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Scaling up stochastic gradient descent for non-convex optimisation

• Authors : Mohamad, Saad; Alamri, Hamad; Bouchachia, Abdelhamid ...

• Source: Machine Learning ; volume 111, issue 11, page 4039-4079 ; ISSN 0885-6125 1573-0565

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Cohort Revenue & Retention Analysis: A Bayesian Approach

• Authors : Orduz, Juan Camilo

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