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Published in 2019 at "Molecular Physics"
DOI: 10.1080/00268976.2019.1615646
Abstract: ABSTRACT In this article, the possible use of sets of basis functions alternative with respect to the usual atom-centred orbitals sets is considered. The orbitals describing the inner part of the wavefunction (i.e. the region…
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Keywords:
gaussian orbitals;
calculations application;
molecular calculations;
distributed gaussian ... See more keywords
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Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3501409
Abstract: Gaussian Process regression is a powerful non-parametric approach that facilitates probabilistic uncertainty quantification in machine learning. Distributed Gaussian Process (DGP) methods offer scalable solutions by dividing data among multiple GP models (or “experts”). DGPs have…
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Keywords:
processes uncertain;
distributed gaussian;
gaussian process;
uncertain inputs ... See more keywords
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2
Published in 2023 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2022.3208969
Abstract: In this letter, we propose a coded load balancing method for distributed Gaussian process regression over heterogeneous wireless networks, where users with diverse computational and communications capabilities may offload excessive training data onto a computationally…
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Keywords:
coded distributed;
distributed gaussian;
process regression;
gaussian process ... See more keywords
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Published in 2020 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2020.2971449
Abstract: In this article, we consider the distributed direct target tracking using the received radio signal by exploiting time delay and Doppler for heterogeneous wireless sensor networks. We develop herein a distributed Gaussian particle filtering (D-GPF)…
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Keywords:
gaussian particle;
distributed gaussian;
heterogeneous networks;
particle ... See more keywords