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Gaussian Processes and Bayesian Inference

TopicLeading institutions, researchers & key papers

Gaussian Processes and Bayesian Inference is a topic indexed in ScholarIQ from OpenAlex.

What is known about Gaussian Processes and Bayesian Inference?

ScholarIQrecord summary

This cluster of papers focuses on the application of Gaussian Processes in machine learning, covering topics such as variational inference, sparse regression, Bayesian inference, deep learning, and probabilistic models. It also explores the use of Gaussian Processes for nonparametric methods, time series modelling, and handling big data.

How many works does Gaussian Processes and Bayesian Inference have?

ScholarIQindexed works

Gaussian Processes and Bayesian Inference has 12 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.

What is the OpenAlex record for Gaussian Processes and Bayesian Inference?

ScholarIQopenalex

The OpenAlex for Gaussian Processes and Bayesian Inference is on the source record.

What are the most-cited papers on Gaussian Processes and Bayesian Inference?

ScholarIQmost cited works
Solution of physics-based Bayesian inverse problems with deep generative priors
Dhruv Patel, Deep Ray, Assad A. Oberai
Computer Methods in Applied Mechanics and Engineering. 202258 CitationsOPEN ACCESS
On the adaptation of recurrent neural networks for system identification
Marco Forgione, Aneri Muni, Dario Piga, Marco Gallieri
Automatica. 202332 CitationsOPEN ACCESS
A dimension-reduced variational approach for solving physics-based inverse problems using generative adversarial network priors and normalizing flows
Agnimitra Dasgupta, Dhruv Patel, Deep Ray, E. A. Johnson, Assad A. Oberai
Computer Methods in Applied Mechanics and Engineering. 202324 Citations

Where is Gaussian Processes and Bayesian Inference research published, and who funds it?

ScholarIQvenues & funding sources

TOP FUNDERS

National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock

How much of the research on Gaussian Processes and Bayesian Inference is open access?

ScholarIQopen access share
67%OPEN ACCESS
Gold
0%
Green
33%
Hybrid
33%
Bronze
0%
Closed
33%

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