repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
nolabs-ai/deepfabric
Generate High-Quality Synthetics, Train, Measure, and Evaluate in a Single Pipeline
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
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Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 53%Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials →
- PossiblePossibly related (embedding) · 49%From virtual experiments to biomedical insight with synthetic data →
- PossiblePossibly related (embedding) · 49%URSA: Chemistry-Aware Benchmark for Utilitarian Retrosynthesis Assessment →
- PossiblePossibly related (embedding) · 48%Synthetic Sciences Releases OpenScience: An Open-Source, Model-Agnostic AI Workbench for Machine Learning, Biology, Physics, and Chemistry Research - MarkTechPost →
- PossiblePossibly related (embedding) · 46%Introducing GeneBench-Pro →
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Related across the graph
newsFrom virtual experiments to biomedical insight with synthetic datapaperBeyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic PotentialsnewsSynthetic Sciences Releases OpenScience: An Open-Source, Model-Agnostic AI Workbench for Machine Learning, Biology, Physics, and Chemistry Research - MarkTechPostpaperURSA: Chemistry-Aware Benchmark for Utilitarian Retrosynthesis AssessmentnewsIntroducing GeneBench-Pro