arXiv (All)
open access
A Generalisation Signal Need Not Be a Model-Selection Signal
Model selection in computational biology often relies on validation data drawn from the training regime, even when deployment lies outside it. When validation no longer preserves which model is best, a natural alternative is to rank candidates using properties of the trained network itself. We test
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
- Model selection with proper scoring rules on data sets of time series#303196
- Evaluating Long-term Direct and Correlated Selection Response in White Plymouth Rock Chickens Selected for High or Low 8-week Body Weight#970086
- Transfer Learning of Supervised Sequence to Function Models Enables Cell Type Specific Regulatory Sequence Prediction in Kidney#616081
- Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation#1013626
- Where Decoder Cosine Similarity Fails for SAE Feature Flow Discovery#1070080
Record · ID 1144066
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