arXiv (OAI Expanded)
open access
Beyond Prediction: Conformal Inference for Latent Distributional Parameters
Many prediction problems seek to infer an unobserved, instance-specific parameter that governs the distribution of an observable response, even though the latent parameter is unavailable for both historical and future instances. We develop LatentCP, a prior-free conformal framework that constructs u
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
- Beyond Prediction: Conformal Inference for Latent Distributional Parameters#925216
- Beyond Marginal Validity: Finite-Sample Guarantees for Localized Conformal Prediction#432532
- Conformal prediction after data-dependent model selection#149175
- Rolling Conformal Prediction in Sequential Model Training#1063162
- Orthogonal JEPA: Factorized Predictive States for Latent World Models#471241
Record · ID 920981
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