arXiv (All)
open access
RuNNer 2.0: A Software Suite for High-Dimensional Neural Network Potentials
We present RuNNer 2.0, the "Ruhr University Neural Network energy representation", a highly optimized software suite for training and evaluating high-dimensional neural network potentials (HDNNPs) of the second, third, and fourth generation. Long-range electrostatics and charge equilibration (QEq) f
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
- Enhancing EBSD throughput of battery electrode materials using super-resolution generative adversarial networks#467116
- AutoPot: Automated and massively parallelized construction of Machine-Learning Potentials#821418
- A budget-dependent crossover between coverage- and response-based training-set selection for machine-learned interatomic potentials#973497
- Optimal gradient estimates for the insulated conductivity problem with dimensions more than two#155444
- ECENet: An Edge Cluster Expansion Line-Graph Neural Network#1048880
Record · ID 1129336
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