chenebuah / evapd

A deep evolutionary learning framework for discovering stable and synthesizable energy (perovskite) materials.

EVAPD

An Evolutionary Variational Autoencoder for Perovskite Discovery

(Chenebuah ET, Nganbe M and Tchagang AB (2023), An evolutionary variational autoencoder for perovskite discovery. Front. Mater. 10:1233961. https://doi.org/10.3389/fmats.2023.1233961)

Authors: *Ericsson Tetteh Chenebuah, Michel Nganbe and Alain Beaudelaire Tchagang

Department of Mechanical Engineering, University of Ottawa, 161 Louis-Pasteur, Ottawa, ON, K1N 6N5 Canada

Digital Technologies Research Centre, National Research Council of Canada, 1200 Montréal Road, Ottawa, ON, K1A 0R6 Canada

*Corresponding author: [email protected]

Citing

If you are using this resource, please cite as:

@ARTICLE{10.3389/fmats.2023.1233961,
AUTHOR={Chenebuah, Ericsson Tetteh and Nganbe, Michel and Tchagang, Alain Beaudelaire},   
TITLE={An evolutionary variational autoencoder for perovskite discovery},      
JOURNAL={Frontiers in Materials},      
VOLUME={10},           
YEAR={2023},      
URL={https://www.frontiersin.org/articles/10.3389/fmats.2023.1233961},       
DOI={10.3389/fmats.2023.1233961},      
ISSN={2296-8016}   
}