Microstructure optimization of constrained design objectives using machine learning based feedback aware data generation
- MATLAB 9.2.0.556344 (R2017a)
- Python 2.7.1 or above
- Scikit-Learn 0.19.1
If you use this code or data, please cite:
A. Paul, P. Acar, W. Liao, A. Choudhary, V. Sundararaghavan and A. Agrawal. Microstructure Optimization with Constrained Design Objectives using Machine Learning-Based Feedback-Aware Data-Generation. Journal of Computational Materials Science, 2019
The code was developed by the CUCIS group at the Electrical and Computer Engineering Department in Northwestern University.
- Arindam Paul (arindam.paul@eecs.northwestern.edu)
- Ankit Agrawal (ankitag@eecs.northwestern.edu)
- Wei-keng Liao (wkliao@eecs.northwestern.edu)
- Alok Choudhary (choudhar@eecs.northwestern.edu)
The development team would like thank the collaborators Prof. Pinar Acar at Virginia Tech and Prof. Veera Sundararaghavan.
email: arindam.paul@eecs.northwestern.edu or ankitag@eecs.northwestern.edu
Copyright (C) 2019, Northwestern University.
See COPYRIGHT notice in top-level directory.
This work is supported primarily by the AFOSR MURI award FA9550-12-1-0458. Partial support is also acknowledged from the following grants: NIST award 70NANB14H012; NSF award CCF-1409601; DOE awards DE-SC0007456, DE-SC0014330; and Northwestern Data Science Initiative.