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clic/clusters/v1.6/README.md
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- **Developed by:** Joosep Pata, Eric Wulff, Farouk Mokhtar, Mengke Zhang, David Southwick, Maria Girone, David Southwick
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- **Model type:** graph neural network with learnable structure in locality-sensitive hashing bins
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- **License:** Apache License
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- **Developed by:** Joosep Pata, Eric Wulff, Farouk Mokhtar, Mengke Zhang, David Southwick, Maria Girone, David Southwick, Javier Duarte
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- **Model type:** graph neural network with learnable structure in locality-sensitive hashing bins
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- **License:** Apache License
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cms/2024_04_05/pyg-cms_20240324_235743_208080/README.md
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# Model Card for cms-2024-04-05
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This model reconstructs particles in a detector, based on the tracks and calorimeter clusters recorded by the detector.
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## Model Details
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### Model Description
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- **Developed by:** Joosep Pata, Eric Wulff, Farouk Mokhtar, Javier Duarte
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- **Model type:** full attention
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- **License:** Apache License
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### Model Sources
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- **Repository:** https://github.com/jpata/particleflow/releases/tag/v1.7.0
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- **Slides:** https://indico.cern.ch/event/1399688/#1-ml-for-pf
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## Uses
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### Direct Use
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This model may be used to study the physics and computational performance on ML-based reconstruction in CMS simulation.
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It should only be used within the CMS collaboration.
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### Out-of-Scope Use
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This model is not intended for physics measurements on real data.
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## Bias, Risks, and Limitations
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The model has only been trained on simulation data and has not been validated against real data.
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It should not be used outside of the CMS collaboration.
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## How to Get Started with the Model
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## Training Details
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### Training Data
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Trained on 400k events from `cms_pf_ttbar`, version `v1.7.1`.
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https://github.com/jpata/particleflow/blob/v1.7.0/mlpf/heptfds/cms_pf/ttbar.py
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## Model Card Contact
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Joosep Pata, [email protected]
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