arXiv (OAI Expanded)
open access
Neural network design for J function approximation in dynamic programming
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
- Bond strength prediction model of corroded reinforcement in concrete using neural network#397983
- Back propagation artificial neural network modeling of flexural and compressive strength of concrete reinforced with polypropylene fibers#394199
- The Forgotten History of Wave Function Variance Optimization and its Relevance for Neural-Network VMC#985806
- Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation#246727
- Deep neural network approximation theory for high-dimensional functions#180488
Record · ID 639108
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