Omkar2118/datasets huggingface dataset:
TrackML challenge Accuracy phase dataset
Full name: Tracking Machine Learning Challenge

The dataset comprises multiple independent events, where each event contains simulated measurements (essentially 3D points) of particles generated in a collision between proton bunches at the Large Hadron Collider at CERN. The goal of the tracking machine learning challenge is to group the recorded measurements or hit for each event into tracks, sets of hits that belong to the same initial particle. A solution must uniquely associate each hit to one track. The training dataset contains the recorded hit, their ground truth counterpart and their association to particles, and the initial parameters of those particles. The test dataset contains only the recorded hits.

The dataset was used for the Accuracy Phase of the Tracking Machine Learning challenge on Kaggle.

See more details in the home page url.

Introducing paper: The Tracking Machine Learning challenge : Accuracy phase