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Deep Gaussian mixture models

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2 Published in 2019 at "Statistics and Computing"

DOI: 10.1007/s11222-017-9793-z

Abstract: Deep learning is a hierarchical inference method formed by subsequent multiple layers of learning able to more efficiently describe complex relationships. In this work, deep Gaussian mixture models (DGMM) are introduced and discussed. A DGMM… read more here.

Keywords: mixture; deep gaussian; mixture models; gaussian mixture ... See more keywords

Deep Gaussian Process-Based Bayesian Inference for Contaminant Source Localization

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0 Published in 2018 at "IEEE Access"

DOI: 10.1109/access.2018.2867687

Abstract: This paper proposes a Bayesian framework for localization of multiple sources in the event of accidental hazardous contaminant release. The framework assimilates sensor measurements of the contaminant concentration with the integrated multizone computational fluid dynamics… read more here.

Keywords: process based; model; deep gaussian; gaussian process ... See more keywords

Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification

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2 Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3237990

Abstract: Machine learning (ML) methods often require large volumes of labeled data to achieve meaningful performance. The expertise necessary for labeling data in medical applications like pathology presents a significant challenge in developing clinical-grade tools. Crowdsourcing… read more here.

Keywords: classification; deep gaussian; tex math; inline formula ... See more keywords

Indoor Radio Map Construction and Localization With Deep Gaussian Processes

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0 Published in 2020 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2020.2996564

Abstract: With the increasing demand for location-based service, WiFi-based localization has become one of the most popular methods due to the wide deployment of WiFi and its low cost. To improve this technology, we propose DeepMap,… read more here.

Keywords: indoor radio; radio map; map construction; location ... See more keywords

Empirical Assessment of Deep Gaussian Process Surrogate Models for Engineering Problems

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0 Published in 2020 at "Journal of Aircraft"

DOI: 10.2514/1.c036026

Abstract: In recent years, multilayered hierarchical compositions of the well-known and widely used Gaussian process models called deep Gaussian processes are finding use in the approximation of black-box fu... read more here.

Keywords: assessment deep; empirical assessment; process surrogate; deep gaussian ... See more keywords