Knowledge Graph
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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
active learning
technology38 mentionslast seen Nov 13, 2026
An inverse-design strategy examined for integrating with conditional generation in materials design.
Relationships 36
- machine learning interatomic potentialdepends onactive learning99% confidence3 sources
- Calpricdepends onactive learning99% confidence2 sources
- active learningdepends onflow matching92% confidence1 source
- LEAPdepends onactive learning92% confidence1 source
- spin-MLIPimplementsactive learning92% confidence1 source
- fractional-order viscoelastic modeldepends onactive learning91% confidence1 source
- closed-loop molecule generation pipelinedepends onactive learning90% confidence1 source
- active logistic regressiondepends onactive learning90% confidence1 source
- active learningdepends ondeep ensemble90% confidence1 source
- ActiveKDdepends onactive learning90% confidence1 source
- active learningdepends onhuman-in-the-loop optimization89% confidence1 source
- High-Utility Sequential Pattern Mining using SHAP valuesdepends onactive learning88% confidence1 source
- gated active learning frameworkdepends onactive learning88% confidence1 source
- Bayesian model-based reinforcement learningdepends onactive learning88% confidence1 source
- uncertainty quantificationapplies toactive learning87% confidence1 source
- last-layer-projection regressiondepends onactive learning85% confidence1 source
- OLASdepends onactive learning85% confidence1 source
- active learningapplies tohydrogen and ion diffusion simulation85% confidence1 source
- active learningapplies toreactive and photochemical dynamics simulation85% confidence1 source
- active learningapplies toferroelectric materials simulation85% confidence1 source
- active learningapplies toelemental and alloy mechanics85% confidence1 source
- active learningdepends onuncertainty quantification85% confidence1 source
- active learningdepends onCALPHAD85% confidence1 source
- active learningdepends onmachine learning interatomic potential85% confidence1 source
- active learningdepends onGaussian Process Regression85% confidence1 source
- Thea active learning platformdepends onactive learning85% confidence1 source
- Ultra Strong Machine Learningdepends onactive learning85% confidence1 source
- bifidelity surrogate modeldepends onactive learning85% confidence1 source
- ActMOFdepends onactive learning85% confidence1 source
- on-the-fly molecular dynamicsdepends onactive learning85% confidence1 source
- surrogate modelingdepends onactive learning85% confidence1 source
- Random Forestimplementsactive learning85% confidence1 source
- active learningapplies tomechanical metamaterials design80% confidence1 source
- active learningdepends onvariance-based acquisition criteria80% confidence1 source
- kernel-based acquisitiondepends onactive learning80% confidence1 source
- deep equivariant neural networkimplementsactive learning75% confidence1 source
Relationship
active learningapplies toreactive and photochemical dynamics simulation
85% confidence1 supporting mentions
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Sources 1