The competitions has run in two phases
This is the official annnouncement of the "Throughput" phase of the TrackML competition. The final leaderboard is:
They were able to maintain high score with speed well below 10s per event (even below 1s for the first two), well below the state of the art.
They have been invited to participate to the TrackML Grand Finale workshop at CERN in July 2019, were they reported on their techniques. A write-up is in preparation.
This is the official announcement of the first « Accuracy" phase of the TrackML competition
The final leaderboard https://www.kaggle.com/c/trackml-particle-identification/leaderboard has been confirmed
In additional, the TrackML International Advisory Committee composed of High Energy Physicists and Computer Scientists Markus Elsing, Frank Gaede, Alison Lowndes, Maurizio Pierini, Danilo Rezende and Marc Schoenauer (as detailed in https://sites.google.com/site/trackmlparticle/international-advisory-committee), has examined the contributions submitted:
The proposed methods clearly demonstrate a necessity of further synergy between model-based and data-based approaches. The organizing committee and international advisory committee are glad to acknowledge that the winning solutions tried to elaborate along this direction. Being original and innovative the proposed methods attempted at incorporating the best from physical models and machine learning targeting a trade off between the performance and complexity. We do believe that the experience and lessons learned in the TrackML challenge will further stimulate a dialog between these communities and will be mutually beneficial and enriching.
A dedicated 75' TrackML session has taken place at Montreal NIPS 2018 Competition workshop Friday 7th December , with talks from Andreas Salzburger and David Rousseau for the organisers, Johan Sokrates Wind "icecuber", Nicole and Liam Finnies, and Sergei Gorbunov: https://nips.cc/Conferences/2018/Schedule?showEvent=10945 . A chapter for the NeurIPS 2018 Competition Book has been accepted for publication.