arXiv (All)
open access
Beyond Average Error through Oracle-Informed Stress Tests for Time-Series Forecasting
Average squared error cannot reveal whether forecasting performance degrades because the future becomes less predictable or because forecasts move farther from the conditional mean. We introduce paired, mechanism-controlled stress tests that decompose changes in expected squared error at each lead t
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
- Dynamical Parameters: An Interpretability Framework for Time-Series Foundation Models#1119389
- Validating Explainer Methods: A Functionally Grounded Approach for Numerical Forecasting#451792
- Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models#146916
- FETS Benchmark: Foundation Models Enable Scalable and Generalizable Energy Time Series Forecasting#684431
- FETS Benchmark: Foundation Models Enable Scalable and Generalizable Energy Time Series Forecasting#682656
Record · ID 1037503
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