repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
luigibonati/mlcolvar
A unified framework for machine learning collective variables for enhanced sampling simulations
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 46%Human-Machine Collaboration on Generative Meta-Learning: Model and Algorithm →
- PossiblePossibly related (embedding) · 46%QuasiMoTTo: Quasi-Monte Carlo Test-Time Scaling →
- PossiblePossibly related (embedding) · 45%B3O: Scalable Boltzmann Batch Bayesian Optimization →
- PossiblePossibly related (embedding) · 47%Physically Consistent Parameter Inference: Transparent Machine Learning Emulation in High Energy Physics and Cosmology →
Implements
paperHuman-Machine Collaboration on Generative Meta-Learning: Model and AlgorithmpaperQuasiMoTTo: Quasi-Monte Carlo Test-Time ScalingpaperB3O: Scalable Boltzmann Batch Bayesian OptimizationpaperPhysically Consistent Parameter Inference: Transparent Machine Learning Emulation in High Energy Physics and Cosmology
Related across the graph
paperB3O: Scalable Boltzmann Batch Bayesian OptimizationpaperHuman-Machine Collaboration on Generative Meta-Learning: Model and AlgorithmpaperQuasiMoTTo: Quasi-Monte Carlo Test-Time ScalingpaperPhysically Consistent Parameter Inference: Transparent Machine Learning Emulation in High Energy Physics and Cosmology