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1. particle_fmparticle_fmPublic

   Easily train and evaluate multiple flow matching generative models on various particle physics datasets

   Python 8

2. erum-data-idt/pd4mlerum-data-idt/pd4mlPublic

   Python 28 12

3. uhh-pd-ml/EPiC-FMuhh-pd-ml/EPiC-FMPublic

   EPiC Flow Matching Implementation for Generating Jets as Point Clouds (https://arxiv.org/abs/2310.00049)

   Python 6 1

4. uhh-pd-ml/LHCO_EPiC-FMuhh-pd-ml/LHCO_EPiC-FMPublic

   Flow Matching Generative Models for 'Full Phase Space Resonant Anomaly Detection' (https://arxiv.org/abs/2310.06897)

   Jupyter Notebook 2

5. CNN-exercisesCNN-exercisesPublic

   Exercises on Convolutional Neural Networks (CNNs) created for the ErUM Data Deep Learning School 2023

   Jupyter Notebook 1 2

6. uhh-pd-ml/sk_cathodeuhh-pd-ml/sk_cathodePublic

   An instructive notebook implementation of anomaly detection algorithms, such as CATHODE, hiding the technical implementation details behind a scikit-learn-like API.

   Python 14 12