Flux-Frontiers is an independent research organization specializing in machine learning, structural biophysics, simulation, and AI. Core research areas include manifold-aware geometric machine learning (WaveRider), deterministic knowledge-graph retrieval (KGRAG), and structural bioinformatics.
The lab believes structure is ground truth: when ontologies are well-defined, knowledge graphs derived from them carry the same guarantees as the source material. Domain-specific KG libraries (PyCodeKG, DocKG, DiaryKG, MetaboKG, MemoryKG) implement a shared federated query protocol for AI agents.
This community hosts preprints, software releases, and reproducibility archives from Flux-Frontiers projects.