ChemML: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data
Abstract
ChemML is an open machine learning (ML) and informatics program suite that is designed to support and advance the data‐driven research paradigm that is currently emerging in the chemical and materials domain. ChemML allows its users to perform various data science tasks and execute ML workflows that are adapted specifically for the chemical and materials context. Key features are automation, general‐purpose utility, versatility, and user‐friendliness in order to make the application of modern data science a viable and widely accessible proposition in the broader chemistry and materials community. ChemML is also designed to facilitate methodological innovation, and it is one of the cornerstones of the software ecosystem for data‐driven in silico research.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 30, 2020
- Source ID
- 10.1002/wcms.1458
Entities
People
- Aditya Sonpal
- Bhargava U. Kota
- Doaa Altarawy
- Gaurav Vishwakarma
- Johannes Hachmann
- Mojtaba Haghighatlari
- Ramachandran Subramanian
- Srirangaraj Setlur
Organizations
- Alexandria University
- National Science Foundation
- Office of Science
- United States Army Armament Research, Development and Engineering Center
- University at Buffalo
- Virginia Tech