Zois Boukouvalas
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Deep learning for molecular design—a review of the state of the art
DC Elton, Z Boukouvalas, MD Fuge, PW Chung
Molecular Systems Design & Engineering 4 (4), 828-849, 2019
Applying machine learning techniques to predict the properties of energetic materials
DC Elton, Z Boukouvalas, MS Butrico, MD Fuge, PW Chung
Scientific reports 8 (1), 1-12, 2018
An efficient multivariate generalized Gaussian distribution estimator: Application to IVA
Z Boukouvalas, GS Fu, T Adalı
2015 49th Annual Conference on Information Sciences and Systems (CISS), 1-4, 2015
Sparsity and independence: Balancing two objectives in optimization for source separation with application to fMRI analysis
Z Boukouvalas, Y Levin-Schwartz, VD Calhoun, T Adalı
Journal of the Franklin Institute 355 (4), 1873-1887, 2018
Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corpora
DC Elton, D Turakhia, N Reddy, Z Boukouvalas, MD Fuge, RM Doherty, ...
arXiv preprint arXiv:1903.00415, 2019
Non-orthogonal constrained independent vector analysis: Application to data fusion
S Bhinge, Q Long, Y Levin-Schwartz, Z Boukouvalas, VD Calhoun, ...
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
A new blind source separation framework for signal analysis and artifact rejection in functional near-infrared spectroscopy
A von Lühmann, Z Boukouvalas, KR Müller, T Adalı
NeuroImage 200, 72-88, 2019
Consistent run selection for independent component analysis: Application to fMRI analysis
Q Long, C Jia, Z Boukouvalas, B Gabrielson, D Emge, T Adali
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
A new Riemannian averaged fixed-point algorithm for MGGD parameter estimation
Z Boukouvalas, S Said, L Bombrun, Y Berthoumieu, T Adalı
IEEE Signal Processing Letters 22 (12), 2314-2318, 2015
Machine learning of energetic material properties
BC Barnes, DC Elton, Z Boukouvalas, DCE Taylor, WD Mattson, MD Fuge, ...
arXiv preprint arXiv:1807.06156, 2018
Enhancing ICA performance by exploiting sparsity: Application to FMRI analysis
Z Boukouvalas, Y Levin-Schwartz, T Adalı
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
The role of diversity in data‐driven analysis of multi‐subject fMRI data: Comparison of approaches based on independence and sparsity using global performance metrics
Q Long, S Bhinge, Y Levin‐Schwartz, Z Boukouvalas, VD Calhoun, ...
Human brain mapping 40 (2), 489-504, 2019
Independent vector analysis for data fusion prior to molecular property prediction with machine learning
Z Boukouvalas, DC Elton, PW Chung, MD Fuge
arXiv preprint arXiv:1811.00628, 2018
Development of ICA and IVA Algorithms with Application to Medical Image Analysis
Z Boukouvalas
arXiv preprint arXiv:1801.08600, 2018
Independent component analysis by entropy maximization with Kernels
Z Boukouvalas, R Mowakeaa, GS Fu, T Adali
arXiv preprint arXiv:1610.07104, 2016
IVA for abandoned object detection: Exploiting dependence across color channels
S Bhinge, Z Boukouvalas, Y Levin-Schwartz, T Adali
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
Density estimation by entropy maximization with kernels
GS Fu, Z Boukouvalas, T Adalı
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
Independent component analysis using semi-parametric density estimation via entropy maximization
Z Boukouvalas, Y Levin-Schwartz, R Mowakeaa, GS Fu, T Adalı
2018 IEEE Statistical Signal Processing Workshop (SSP), 403-407, 2018
On the characterization, generation, and efficient estimation of the complex multivariate GGD
R Mowakeaa, Z Boukouvalas, T Adalı, C Cavalcante
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 1-5, 2016
Independent Component Analysis for Trustworthy Cyberspace during High Impact Events: An Application to Covid-19
Z Boukouvalas, C Mallinson, E Crothers, N Japkowicz, A Piplai, M Sudip, ...
arXiv preprint arXiv:2006.01284, 2020
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