Conceptio › Archive › arXiv (All)
arXiv (All) open access

Optimization Encoders: Rethinking Second-Order Meta-Learning for Neural Fields

van Herten, Rudolf L. M. et al.
arXiv (All) · Papers
Open Source ↗Direct PDF ↓
computer-vision-and-pattern-recognitionmachine-learning
Conditional neural fields represent signals continuously, but their effectiveness depends on how the conditional latent representations are inferred from observed data. In meta-learning, this encoding occurs through gradient updates induced by the decoder, tying representation learning directly to d
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

Record · ID 1217810
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