ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1706.01629
  4. Cited By
Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy

Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy

6 June 2017
Sanjib Sharma
ArXiv (abs)PDFHTMLGithub (59★)

Papers citing "Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy"

14 / 14 papers shown
Title
The Clear Sky Corridor: Insights Towards Aerosol Formation in Exoplanets
  Using An AI-based Survey of Exoplanet Atmospheres
The Clear Sky Corridor: Insights Towards Aerosol Formation in Exoplanets Using An AI-based Survey of Exoplanet Atmospheres
Reza Ashtari
Kevin B. Stevenson
David Sing
Mercedes Lopez-Morales
Munazza K. Alam
Nikolay K. Nikolov
Thomas M. Evans-Soma
56
1
0
09 Oct 2024
A comparison of Bayesian sampling algorithms for high-dimensional
  particle physics and cosmology applications
A comparison of Bayesian sampling algorithms for high-dimensional particle physics and cosmology applications
Joshua Albert
Csaba Balazs
A. Fowlie
Will Handley
Nicholas Hunt-Smith
Roberto Ruiz de Austri
Martin White
119
3
0
27 Sep 2024
Automatic Parallel Tempering Markov Chain Monte Carlo with Nii-C
Automatic Parallel Tempering Markov Chain Monte Carlo with Nii-C
Sheng Jin
Wenxin Jiang
Dong-Hong Wu
144
2
0
13 Jul 2024
Liouville Flow Importance Sampler
Liouville Flow Importance Sampler
Yifeng Tian
Nishant Panda
Yen Ting Lin
123
13
0
03 May 2024
Estimating the Local Learning Coefficient at Scale
Estimating the Local Learning Coefficient at Scale
Zach Furman
Edmund Lau
67
3
0
06 Feb 2024
Isolated pulsar population synthesis with simulation-based inference
Isolated pulsar population synthesis with simulation-based inference
V. Graber
M. Ronchi
C. Pardo-Araujo
N. Rea
62
5
0
22 Dec 2023
Eryn : A multi-purpose sampler for Bayesian inference
Eryn : A multi-purpose sampler for Bayesian inference
N. Karnesis
Michael L. Katz
N. Korsakova
J. Gair
N. Stergioulas
57
31
0
03 Mar 2023
Deep representation learning: Fundamentals, Perspectives, Applications,
  and Open Challenges
Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challenges
K. T. Baghaei
Amirreza Payandeh
Pooya Fayyazsanavi
Shahram Rahimi
Zhiqian Chen
Somayeh Bakhtiari Ramezani
FaMLAI4TS
69
6
0
27 Nov 2022
The No-U-Turn Sampler as a Proposal Distribution in a Sequential Monte
  Carlo Sampler with a Near-Optimal L-Kernel
The No-U-Turn Sampler as a Proposal Distribution in a Sequential Monte Carlo Sampler with a Near-Optimal L-Kernel
L. Devlin
P. Horridge
P. L. Green
Simon Maskell
33
2
0
05 Aug 2021
Bayesian spectral density approach for identification and uncertainty
  quantification of bridge section's flutter derivatives operated in turbulent
  flow
Bayesian spectral density approach for identification and uncertainty quantification of bridge section's flutter derivatives operated in turbulent flow
Xiaolei Chu
W. Cui
Peng Liu
Lin Zhao
Y. Ge
11
10
0
03 Aug 2021
Informative Bayesian model selection for RR Lyrae star classifiers
Informative Bayesian model selection for RR Lyrae star classifiers
Francisco Pérez-Galarce
K. Pichara
P. Huijse
M. Catelán
Domingo Mery
37
1
0
24 May 2021
dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian
  Posteriors and Evidences
dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences
J. Speagle
88
1,223
0
03 Apr 2019
A Simple Algorithm for Scalable Monte Carlo Inference
A Simple Algorithm for Scalable Monte Carlo Inference
A. Borisenko
M. Byshkin
Alessandro Lomi
46
10
0
02 Jan 2019
Data analysis recipes: Using Markov Chain Monte Carlo
Data analysis recipes: Using Markov Chain Monte Carlo
D. Hogg
D. Foreman-Mackey
68
213
0
17 Oct 2017
1