Development of LSTM and GRU layers in TMVA


Toolkit for Multivariate Analysis (TMVA) is a multi-purpose machine learning toolkit integrated into the ROOT scientific software framework, used in many particle physics data analyses and applications. In the past years we have expanded TMVA’s capabilities to include various deep learning architectures: Fully-connected (DNN), Convolutional (CNN) and Recurrent (RNN) Neural Networks. Currently the RNN implementation includes only the standard (vanilla) type layer. This summer we would like to expand the implementations to include the LSTM and GRU layer types. The candidate is expected to develop CPU and GPU based implementations.

Both layer types have very promising applications in particle physics such as jet tagging and particle tracking. For more information see this publication.

Task ideas

Expected results


C++ skills, experience with large scale software development and machine learning tools is a plus.


Corresponding Project

Participating Organizations