arXiv (All)
open access
Inverse Problems Conditioned on Observation Ensembles: Applications and Methods
We introduce a new multivariate statistical problem that we refer to as the Ensemble-conditioned Inverse Problem (EIP). The aim of EIP is to invert for an ensemble that is distributed according to the pushforward of a prior under a forward process. In high energy physics (HEP), this is related to a
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems#144295
- Ensemble Kalman Inversion as an Inertial Interacting Particle System#1084236
- Target-Guided Selective Reweighting for Physics-Informed Neural Network Inverse Problems: A Transfer Learning Approach#926110
- Hölder-Logarithmic Stability and Convergence Rates for an Inverse Random Source Problem#973077
- When Noise Estimation Hides Basis Misspecification in Repeated Bayesian Inverse Problems#1142072
Record · ID 1063838
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive