Astroinformatics

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SEEK ID: https://publications.h-its.org/projects/5

Public web page: Not specified

Organisms: No Organisms specified

HITS Publication SEEK PALs: No PALs for this Research Group

Research Group created: 7th Nov 2017

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Showing 5 out of a possible 9 People Advanced People list for this Research Group with search and filtering

Antonio D'Isanto

Research Groups: Astroinformatics

Institutions: Heidelberg Institute for Theoretical Studies

Nikos Gianniotis

Research Groups: Astroinformatics

Institutions: Heidelberg Institute for Theoretical Studies

https://orcid.org/0000-0002-2187-5522

Expertise: Machine learning

Tools: Neural networks, Gaussian processes, Probabilistic Models, Bayesian inference

Erica Hopkins

Research Groups: Astroinformatics

Institutions: Heidelberg Institute for Theoretical Studies

Xiaoming Hu

Research Groups: Scientific Databases and Visualisation, Computational Molecular Evolution, Physics of Stellar Objects, Molecular and Cellular Modeling, Molecular Biomechanics, Astroinformatics, Groups and Geometry, Playground, Computational Carbon Chemistry, Data Mining and Uncertainty Quantification, Computational Statistics, SIMPLAIX

Institutions: Heidelberg Institute for Theoretical Studies, Heidelberg University

Fenja Kollasch

Research Groups: Astroinformatics

Institutions: Heidelberg Institute for Theoretical Studies

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Heidelberg Institute for Theoretical Studies

Country: Germany

City: Heidelberg

Web page: https://www.h-its.org

Showing 5 out of a possible 80 Publications Advanced Publications list for this Research Group with search and filtering

Positive and Scale Invariant Gaussian Process Latent Variable Model for Astronomical Spectra

Astroinformatics

Abstract

Not specified

Authors: Nikos Gianniotis, Kai L. Polsterer, Iliana Isabel Cortés Pérez

Date Published: 2024

Publication Type: InProceedings

DOI: 10.14428/esann/2024.ES2024-72

Citation: ESANN 2024 proceesdings,pp.315-320,Ciaco - i6doc.com

Created: 7th Oct 2024 at 07:02

A Gaussian process cross-correlation approach to time-delay estimation in active galactic nuclei

Astroinformatics

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Abstract

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Authors: F. Pozo Nunez, N. Gianniotis, K.L. Polsterer

Date Published: 18th Apr 2023

Publication Type: Journal

DOI: 10.1051/0004-6361/202345932

Citation: A&A

Created: 2nd May 2023 at 12:18, Last updated: 5th Mar 2024 at 21:25

Applications of AI in Astronomy

Astroinformatics

Abstract (Expand)

We provide a brief, and inevitably incomplete overview of the use of Machine Learning (ML) and other AI methods in astronomy, astrophysics, and cosmology. Astronomy entered the big data era with the …

Authors: S. G. Djorgovski, Ashish Mahabal, M. J. Graham, Kai L. Polsterer, Alberto Krone-Martins

Date Published: 1st Apr 2023

Publication Type: InCollection

DOI: 10.1142/13123

Citation:

Created: 17th Feb 2023 at 15:45, Last updated: 5th Mar 2024 at 21:25

Modeling photometric reverberation mapping data for the next generation of big data surveys. Quasar accretion disks sizes with the LSST

Astroinformatics

Abstract (Expand)

Abstract Photometric reverberation mapping can detect the radial extent of the accretion disc (AD) in Active Galactic Nuclei by measuring the time delays between light curves observed in different …

Authors: F Pozo Nuñez, C Bruckmann, S Desamutara, B Czerny, S Panda, A P Lobban, G Pietrzyński, K L Polsterer

Date Published: 6th Feb 2023

Publication Type: Journal

DOI: 10.1093/mnras/stad286

Citation: Monthly Notices of the Royal Astronomical Society,stad286

Created: 21st Feb 2023 at 07:25, Last updated: 5th Mar 2024 at 21:25

Probabilistic Modelling of Time Series for explorative Big Data Analysis in Astronomy

Astroinformatics

Abstract

Not specified

Author: Fenja Schweder

Date Published: 1st Feb 2023