DScribe: Library of descriptors for machine learning in materials science

Theory-Guided Machine Learning in Materials Science

Materials scientists are increasingly adopting the use of machine learning tools to discover hidden trends in data and make predictions. Applying concepts from data science without foreknowledge of their limitations and the unique qualities of materials data, however, could lead to errant conclusions. The differences that exist between various kinds of experimental and calculated data require c...

Machine Learning in Materials Science: Recent Progress and Emerging Applications

development and implementation of an optimized control strategy for induction machine in an electric vehicle

in the area of automotive engineering there is a tendency to more electrification of power train. in this work control of an induction machine for the application of electric vehicle is investigated. through the changing operating point of the machine, adapting the rotor magnetization current seems to be useful to increase the machines efficiency. in the literature there are many approaches wh...

HLearn: A Machine Learning Library for Haskell

HLearn is a Haskell-based library for machine learning. Its distinguishing feature is that it exploits the algebraic properties of learning models. Every model in the library is an instance of the HomTrainer type class, which ensures that the batch trainer is a monoid homomorphism. This is a restrictive condition that not all learning models satisfy; however, it is useful for two reasons. First...

Brainy: A Machine Learning Library

Brainy is a newly created cross-platform machine learning library written in Java. It defines interfaces for common types of machine learning tasks and implementations of the most popular algorithms. Brainy utilizes a complex mathematical infrastructure which is also part of the library. The main difference compared to other ML libraries is the sophisticated system for feature definition and ma...