repoGitHubTrust 82 · PrimaryPublished 7d agoLive · 6d ago
arogozhnikov/hep_ml
Machine Learning for High Energy Physics.
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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paperAn Optimisation Framework for the Well-Conditioned Training of Physics-Informed Neural NetworkspaperQ-GAIN: A Python Package for Machine Learning and Physically Informed Analysis ApplicationspaperGrounded autonomous research: a fault-tolerant LLM pipeline from corpus to manuscript in frontier computational physics
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paperPhysics-Informed Neural Embeddings of PDE Solution FamiliespaperAn Optimisation Framework for the Well-Conditioned Training of Physics-Informed Neural NetworksnewsAI, Machine Learning and Deep Learning Advances in the Photothermal, Photoacoustic and Diffusion Wave Sciences and Technologies - AIP Publishing LLCnewsIN 2026 ML BOOK OUTDATED? [D]paperGrounded autonomous research: a fault-tolerant LLM pipeline from corpus to manuscript in frontier computational physicspaperQ-GAIN: A Python Package for Machine Learning and Physically Informed Analysis ApplicationsnewsH&P set to launch ROP optimizer combining machine learning with physics-based modeling - Drilling ContractornewsAalto University Team Develops Machine-Learning Optimized Pulses for Dark Matter Searches - Quantum Zeitgeist