PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 22, 20260 citationsOpen Access

Data Assimilation: From Mathematical and Statistical Foundations to Applications

View Full Paper
(U(:unkn) unknown

Key Points

  • The workshop aimed to explore the foundations and applications of data assimilation in various fields.
  • Gathering experts in dynamical systems, statistics, machine learning, and related areas.
  • Discussions on the sequential updating of predictions based on new observations.
  • Exploring the integration of uncertainty quantification and mathematical modeling.
  • Highlights the growing relevance of data assimilation in science and technology.
  • Demonstrates diverse applications and techniques in dynamical systems and uncertainty quantification.

Abstract

Data assimilation, where predictions from a dynamical system are updated sequentially based on new and incomplete observations, is increasingly finding applications in many areas of science and technology. This workshop brought together a collection of scientists from dynamical systems, statistics, machine learning, applied probability, uncertainty quantification, and mathematical modelling, as well as practitioners in the field.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

(:unkn) unknown (2025) studied this question.

synapsesocial.com/papers/69bf393dc7b3c90b18b43b92https://doi.org/10.34657/32211
Ask AI
Helpful
Bookmark
Share
View Full Paper