repoGitHubTrust 82 · PrimaryPublished 2d agoLive · 2d ago
SimonBlanke/Gradient-Free-Optimizers
Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces
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) · 53%Knowing in Advance When an Evolutionary Outer Loop Will Not Help: A Pre-Registered Cheap-Baseline Screening Rule →
- PossiblePossibly related (embedding) · 51%Error-Conditioned Neural Solvers →
- PossiblePossibly related (embedding) · 50%Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks →
- PossiblePossibly related (embedding) · 49%Hierarchical Muon: Tiled Newton-Schulz Updates for Efficient Muon Optimization →
- PossiblePossibly related (embedding) · 47%B3O: Scalable Boltzmann Batch Bayesian Optimization →
Implements
paperKnowing in Advance When an Evolutionary Outer Loop Will Not Help: A Pre-Registered Cheap-Baseline Screening RulepaperError-Conditioned Neural SolverspaperEvolution Fine-Tuning: Learning to Discover Across 371 Optimization TaskspaperHierarchical Muon: Tiled Newton-Schulz Updates for Efficient Muon OptimizationpaperB3O: Scalable Boltzmann Batch Bayesian Optimization
Related across the graph
paperEvolution Fine-Tuning: Learning to Discover Across 371 Optimization TaskspaperError-Conditioned Neural SolverspaperB3O: Scalable Boltzmann Batch Bayesian OptimizationpaperKnowing in Advance When an Evolutionary Outer Loop Will Not Help: A Pre-Registered Cheap-Baseline Screening RulepaperHierarchical Muon: Tiled Newton-Schulz Updates for Efficient Muon Optimization