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  1. Home
  2. /Repositories
  3. /google-deepmind/kfac-jax
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repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago

google-deepmind/kfac-jax

Second Order Optimization and Curvature Estimation with K-FAC in JAX.

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) · 51%DeepSeek open-sources inference optimizations with 60–85% faster generation [pdf] →
  • PossiblePossibly related (embedding) · 48%Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials →
  • PossiblePossibly related (embedding) · 46%Hamiltonian Neural Networks from a Differential Geometry Perspective [D] →

Covers

newsDeepSeek open-sources inference optimizations with 60–85% faster generation [pdf]newsHamiltonian Neural Networks from a Differential Geometry Perspective [D]

Implements

paperBeyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials

Related across the graph

paperBeyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic PotentialsnewsHamiltonian Neural Networks from a Differential Geometry Perspective [D]newsDeepSeek open-sources inference optimizations with 60–85% faster generation [pdf]
Knowledge path·PBeyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials→NHamiltonian Neural Networks from a Differential Geometry Perspective [D]→NDeepSeek open-sources inference optimizations with 60–85% faster generation [pdf]→Rgoogle-deepmind/kfac-jax

Topics

bayesian-deep-learningmachine-learningoptimization

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Graph trust82Primary
Graph score326