- Machine Learning Tools in HEP
- Falcon: Ultrafast Nonparametric Detector Simulator
- MAGENTA: Monte Carlo Generator Tune Optimization
- Deep learning and MEMs
- Deep learning in FPGAs
ROOT R |
||
R is a multi-platform software environment (programming language) for statistical computing. ROOT is an object-oriented framework for large scale data analysis commonly used in high-energy physics. ROOT-R is an interface between ROOT and R that allows a large set of statistical tools provided by R to be used within the ROOT framework. | ||
ROOT-R Website |
TMVA new design |
||
The Toolkit for Multivariate Analysis (TMVA) is a ROOT-integrated machine-learning environment for the processing and parallel evaluation of multivariate classification and regression. TMVA is designed specifically to the needs of high-energy physics (HEP) applications. We are creating a new version of the toolkit with increased functionality and interfaces to other statistical packages such as R. |
RMVA (R TMVA) | ||
RMVA is a set of plugins for TMVA based on ROOTR that allows the use of R methods for classification and regression in TMVA |
PyMVA (Python TMVA) | ||
PyMVA is a set of plugins for TMVA based on Python that allows the use python-based classification and regression methods in TMVA. |
Variable Importance | ||
Feature selection and reduction are key to robust machine-learning analyses. We are integrating the FAST algorithm into TMVA to allow users make better-informed decisions about their parameter space. |
For more details please the TMVA5.0 webpage: TMVA New Design Page |
Falcon: Ultrafast Nonparametric Detector Simulator |
||
TODO |
MAGENTA: Monte Carlo Generator Tune Optimization |
||
TODO |
Deep learning and MEMs |
||
TODO |
Deep learning in FPGAs |
||
TODO |