Vision Transformers for End-to-End Particle Reconstruction for the CMS Experiment


The field of Computer Vision has for years been dominated by Convolutional Neural Networks (CNNs) which use filters and create feature used by a multi-layer perceptron to perform the desired classification. But recently this field has been incredibly revolutionized by the architecture of Vision Transformers (ViT), which through the mechanism of self-attention has proven to obtain excellent results on many tasks.

Please contact us once you have completed the prerequisite challenges designed for this project to give you a better idea of what you will be working on over the summer. Potential candidates can email their solutions to the challenges (Zip file containing Jupyter notebooks and trained machine learning models) along with their CV @


Total project length: 175/350 hours.

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Please DO NOT contact mentors directly by email. Instead, please email with Project Title and include your CV and test results. The mentors will then get in touch with you.

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