arXiv (All)
open access
RECOB: Reliable Benchmarking of Experimental Optimization in Chemistry and Materials Science
Optimization methods for experimental science are often evaluated on synthetic functions that are reproducible but omit important characteristics of real experiments. We introduce RECOB (REliable Chem Optimization Benchmark, Github repository: \hyperlink{https://github.com/XieZikai/RECOB}{https://gi
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
- DisCoMBO: Steering Expert-in-the-Loop Black Box Optimization via Distributional Conformance#1131314
- Unifying Physical Backpropagation#1062983
- Integrating Computational Optimization with Antimicrobial Susceptibility Testing: A Particle Swarm Optimization Framework for Enhancing Fluoride Toothpaste Formulations#135503
- Integrating Computational Optimization with Antimicrobial Susceptibility Testing: A Particle Swarm Optimization Framework for Enhancing Fluoride Toothpaste Formulations#133232
- Computational Nonsmooth Optimization#429979
Record · ID 1034865
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