Artificial Intelligence for the Electron Ion Collider

Artificial Intelligence for the Electron Ion ColliderArtificial Intelligence for the Electron Ion ColliderArtificial Intelligence for the Electron Ion Collider
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Artificial Intelligence for the Electron Ion Collider

Artificial Intelligence for the Electron Ion ColliderArtificial Intelligence for the Electron Ion ColliderArtificial Intelligence for the Electron Ion Collider
  • Home
  • Events
  • Workshops
  • Hackathons
  • AI-ML-References
  • How-to-Join
  • About Us
  • Community

AI4EIC Community Efforts

In this webpage you can find material/documentation regarding several efforts in our community to disseminate the usage of AI/ML for the EIC. This at the moment includes lectures, outreach events, tutorials. 

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Community EFFORTS on AI/ML for the EIC

Lectures/Tutorials

Below are provided links to lectures, tutorials on AI/ML applications for the EIC detector.

Detector Design with AI, C. Fanelli (MIT)

design

An interactive Jupiter book presented at the NNPSS Summer School at MIT, which includes lectures and hands-on tutorials on AI-assisted design with a fully documented description of the optimization adopted during the EIC detector proposal.  


https://cfteach.github.io/nnpss

Multi-Objective Optimization (Ax, BoTorch), M. Balandat (Meta/AI)

MULTI-OBJECTIVE OPTIMIZATION

Link1

Link2

Unfolding with ML : OmniFold, F. Torales Acosta (LBNL), V. Mikuni (NERSC)

Unfolding - Omnifold

  • GitHub link here: https://github.com/ftoralesacosta/AI4EIC_Omnfold
  • Colab link: https://colab.research.google.com/drive/1zuU9MezTIQGPhXlPG1Y9QilyDcQk6L0K?usp=sharing 
  • Specifically, the notebook: https://github.com/ftoralesacosta/AI4EIC_Omnfold/blob/master/DIS_Omnifold.ipynb
  • Two data files on google drive that the tutorial uses:
    • https://drive.google.com/file/d/1aqxnY0qxTrNZzijoLIUD0StEwmEEVJW7/view?usp=sharing 
    • https://drive.google.com/file/d/1qaeH6Z1xjAzCDuII8DQyDs42F_Ow2rkX/view?usp=sharing

Machine Learning Lifecycle, K. Rajput (Jefferson Lab/Data science)

ML Lifecycle

Colab link: https://colab.research.google.com/drive/1qPIyfefaqofX1wNQ3TYPT_ABy749Ohd2?usp=sharing

MaGraph Neural Networks, Y. (Ray) Ren

Graph Neural Networks

Colab link: https://colab.research.google.com/drive/16fF6q1CSnxnEqRSl7LDAb0evscfqMOrf?usp=sharing

AI/ML examples for the EIC

Contributors

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