Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
A proof-of-concept system comprising a miniaturized sensor array, feature extraction and machine learning pipeline was evaluated for the direct quantification of the concentrations of three major cations, Ca2+, Mg2+, and Na+, in drinking water. Feature importance methods were applied to discover dependencies between the transient potentiometric responses of sensing materials and the cation concentrations. The proposed framework supports design of cross-sensitive sensor arrays to accelerate water testing, providing a complementary approach to traditional chemical analysis for monitoring water quality.
Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
Yidi Wu, Thomas Bohnstingl, et al.
ICML 2025
Haoran Zhu, Pavankumar Murali, et al.
NeurIPS 2020