A Bayesian Framework for Dynamical System Model Selection from Time-Series Data

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-01
DOI
https://doi.org/10.5281/zenodo.14213390
Primary Topic
Gaussian Processes and Bayesian Inference
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Bayesian Framework for Dynamical System Model Selection from Time-Series Data

Zenodo (CERN European Organization for Nuclear Research)
Gaussian Processes and Bayesian Inference
article

A Bayesian Framework for Dynamical System Model Selection from Time-Series Data

article en

Abstract

No abstract available for this paper.
Zenodo (CERN European Organization for Nuclear Research)
University of Canberra (AU), Institut Pprime (FR), CentraleSupélec (FR)
Openalex Percentile: Top 61%
Gaussian Processes and Bayesian Inference
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Bayesian Framework for Dynamical System Model Selection from Time-Series Data · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS