TAILOR is participating in the organisation of a new Challenge! The Challenge is organized by IRT SystemX and the RTE company, with Marc Schoenauer and Sébastien Treguer from Inria contributing to the organization with other researchers, and will be TAILOR representatives for this initiative. This competition aims at promoting the use of ML based surrogate …
Machine Learning for Physical Simulation Challenge Read More »
The Brain Age Prediction Challenge, available on the Codalab platform, was launched as part of the NeurotechX Hackathon. In this challenge, participants are invited to use AI to predict the age of an individual from an electroencephalogram (EEG) recording time series. Such age predictions can be an important path to the development of computational psychiatry diagnosis methods. The brain age prediction challenge is running from November 4-22.
As data is at the heart of the industry 4.0, 11 large international groups and the TAILOR network challenge european students from Oct 3 to Dec 3, with the Smarter Mobility Data Challenge for a Greener Future on Codalab. The challenge has been developped by INRIA scientists Marc Schoenaeur and Sebastien Treguer in collaboration with …
Meta-learning aims to leverage the experience from previous tasks to solve new tasks using only little training data, train faster and/or get better performance. The proposed challenge focuses on “cross-domain meta-learning” for few-shot image classification using a novel “any-way” and “any-shot” setting. This challenge is part of TAILOR WP2 (see more information here). Goal The …
The “Learning to run a power network challenge 2022” is concerned with AI for smart grids, and it has been built by RTE, the French Power Grid operator, and the TAU team, in collaboration with EPRI, CHA Learn, Google research, UCL and IQT labs.
