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Entities25 of 207,987
- large language modeltechnology1,043 mentions
- robotic manipulationmarket824 mentions
- artificial intelligencetechnology739 mentions
- reinforcement learningtechnology491 mentions
- density-functional theorytechnology386 mentions
- Transformertechnology371 mentions
- agentic AItechnology353 mentions
- vision-language-action modeltechnology350 mentions
- U.S. Food and Drug Administrationorganization320 mentions
- Vision-Language Modeltechnology318 mentions
- Microsoftorganization291 mentions
- Googleorganization276 mentions
- NVIDIAorganization264 mentions
- Model Context Protocoltechnology232 mentions
- machine learningtechnology204 mentions
- MarketsandMarketsorganization199 mentions
- Claudeproduct192 mentions
- AI agenttechnology188 mentions
- ChatGPTproduct178 mentions
- Anthropicorganization177 mentions
- integrated sensing and communicationtechnology175 mentions
- Amazon Web Services, Inc.organization174 mentions
- OpenAIorganization172 mentions
- diffusion modeltechnology169 mentions
- IBMorganization163 mentions
Entity
machine-learned interatomic potential
technology28 mentionslast seen Nov 13, 2026
A computational model fine-tuned to ab initio data for predicting atomic interactions.
Relationships 35
- molecular dynamics simulationdepends onmachine-learned interatomic potential99% confidence2 sources
- machine-learned interatomic potentialdepends ondensity-functional theory99% confidence2 sources
- machine-learned interatomic potentialapplies toatomistic simulation92% confidence1 source
- machine-learned interatomic potentialapplies toCrCoNi alloy92% confidence1 source
- machine-learned interatomic potentialdepends onab initio molecular dynamics91% confidence1 source
- Feynman-Kac steeringdepends onmachine-learned interatomic potential91% confidence1 source
- MACEdepends onmachine-learned interatomic potential90% confidence1 source
- M3GNetdepends onmachine-learned interatomic potential90% confidence1 source
- machine-learned interatomic potentialdepends onmessage-passing network90% confidence1 source
- machine-learned interatomic potentialdepends onweighted-sum scalarization90% confidence1 source
- machine-learned interatomic potentialimplementsneuroevolution potential90% confidence1 source
- interfacial phonon biasdepends onmachine-learned interatomic potential90% confidence1 source
- machine-learned interatomic potentialapplies tomolecular dynamics90% confidence1 source
- AtomMOFdepends onmachine-learned interatomic potential90% confidence1 source
- PETdepends onmachine-learned interatomic potential90% confidence1 source
- machine-learned interatomic potentialapplies tocorrosion89% confidence1 source
- machine-learned interatomic potentialapplies tocatalysis89% confidence1 source
- machine-learned interatomic potentialapplies toelectrochemistry89% confidence1 source
- MACEimplementsmachine-learned interatomic potential88% confidence1 source
- machine-learned interatomic potentialapplies toamorphous carbon88% confidence1 source
- machine-learned interatomic potentialapplies tolarge-scale atomistic simulations88% confidence1 source
- machine-learned interatomic potentialdepends onatomic cluster expansion88% confidence1 source
- machine-learned interatomic potentialdepends onspin-polarized ab initio88% confidence1 source
- structure matchingdepends onmachine-learned interatomic potential88% confidence1 source
- two-level systemdepends onmachine-learned interatomic potential85% confidence1 source
- MACEdepends onmachine-learned interatomic potential85% confidence1 source
- molecular dynamicsdepends onmachine-learned interatomic potential85% confidence1 source
- atomic cluster expansiondepends onmachine-learned interatomic potential85% confidence1 source
- Young-E(3) tensor product decompositionapplies tomachine-learned interatomic potential85% confidence1 source
- machine-learned interatomic potentialdepends onshort-range order85% confidence1 source
- machine-learned interatomic potentialdepends onstress fluctuation85% confidence1 source
- high-throughput screeningimplementsmachine-learned interatomic potential85% confidence1 source
- machine-learned interatomic potentialapplies tomolecular crystal polymorph control82% confidence1 source
- machine-learned interatomic potentialapplies toinorganic materials discovery70% confidence1 source
- machine-learned interatomic potentialapplies tocomputational materials science70% confidence1 source
Relationship
MACEdepends onmachine-learned interatomic potential
90% confidence1 supporting mentions
Either name opens that entity’s relationships.
Sources 1