Skip to main content
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in

Stay Ahead in the AI Revolution

Weekly digest — EPI pulse, top intelligence, fresh lineage. Free, no account.

Follow Angestrom
Global source network
Synced every 5 minutes

Continuous sync from primary AI sources — indexed, enriched, and queryable in real time.

arXivHugging FaceGitHubOpenAIAnthropicDeepMindReutersBBC TechHacker NewsReddit MLVerified feedsFunding
ANGESTROM

The Intelligence Layer of Humanity. Everything AI. All in One Place.

Angestrom connects every piece of the AI ecosystem — data, models, research, companies, tools, and people.

info@angestrom.comwww.angestrom.comLucknow, Uttar Pradesh, India

Product

  • AI Search
  • AI Models
  • Research Papers
  • Companies
  • News & Events
  • GitHub Explorer
  • APIs & Tools
  • Datasets
  • Benchmarks
  • Model lifecycle
  • Funding graph
  • Contributors
  • AI Agents

Resources

  • Weekly digest
  • Documentation
  • Tutorials
  • Guides
  • News
  • Help / Start
  • Community

Company

  • About
  • Contact
  • Privacy Policy
  • Terms of Service
  • Acceptable Use

Enterprise

  • Pricing
  • Workspace
  • Contact Sales

Developer

  • Developer Hub
  • API docs
  • GitHub

Learn

  • Learning Academy
  • Roadmaps
  • Glossary
  • AI for Beginners

Popular Topics

Loading topics…
View All Topics →
© 2026 Angestrom Intelligence Private Limited. All rights reserved.
English
Theme
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in
  1. Home
  2. /Repositories
  3. /iml-wg/HEPML-LivingReview
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 28d agoLive · 27d ago

iml-wg/HEPML-LivingReview

Living Review of Machine Learning for Particle Physics

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) · 54%Path Integral Quantum Mechanics in the Era of Machine Learning - AIP Publishing LLC →
  • PossiblePossibly related (embedding) · 46%Machine learning for next-generation nuclear reactor design - Innovation News Network →
  • PossiblePossibly related (embedding) · 51%Machine learning narrows search for additional particles in the Higgs boson family - Phys.org →

Covers

newsPath Integral Quantum Mechanics in the Era of Machine Learning - AIP Publishing LLCnewsMachine learning for next-generation nuclear reactor design - Innovation News Network

Covers (incoming)

newsMachine learning narrows search for additional particles in the Higgs boson family - Phys.org

Related across the graph

newsMachine learning for next-generation nuclear reactor design - Innovation News NetworknewsMachine learning narrows search for additional particles in the Higgs boson family - Phys.orgnewsPath Integral Quantum Mechanics in the Era of Machine Learning - AIP Publishing LLC
Knowledge path·NMachine learning for next-generation nuclear reactor design - Innovation News Network→NMachine learning narrows search for additional particles in the Higgs boson family - Phys.org→NPath Integral Quantum Mechanics in the Era of Machine Learning - AIP Publishing LLC→Riml-wg/HEPML-LivingReview

Topics

heplatexmachine-learningpapersparticle-physics

Explore

Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score443