Dr. Vahid Mirjalili
Dr. Vahid Mirjalili
Research Scientist
Verified email at - Homepage
Cited by
Cited by
Python Machine Learning, 2nd Ed.
S Raschka, V Mirjalili
Packt Publishing, 2017
ASD-DiagNet: a hybrid learning approach for detection of autism spectrum disorder using fMRI data
T Eslami, V Mirjalili, A Fong, AR Laird, F Saeed
Frontiers in neuroinformatics 13, 70, 2019
Rank consistent ordinal regression for neural networks with application to age estimation
W Cao, V Mirjalili, S Raschka
Pattern Recognition Letters 140, 325-331, 2020
Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images
V Mirjalili, S Raschka, A Namboodiri, A Ross
11th IAPR International Conference on Biometrics (ICB 2018), 2018
Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
S Raschka, YH Liu, V Mirjalili, D Dzhulgakov
Packt Publishing Ltd, 2022
Physics‐based protein structure refinement through multiple molecular dynamics trajectories and structure averaging
V Mirjalili, K Noyes, M Feig
Proteins: Structure, Function, and Bioinformatics 82, 196-207, 2014
Protein structure refinement through structure selection and averaging from molecular dynamics ensembles
V Mirjalili, M Feig
Journal of chemical theory and computation 9 (2), 1294-1303, 2013
Soft biometric privacy: Retaining biometric utility of face images while perturbing gender
V Mirjalili, A Ross
International Joint Conference on Biometrics (IJCB 2017), 2017
PrivacyNet: Semi-adversarial networks for multi-attribute face privacy
V Mirjalili, S Raschka, A Ross
IEEE Transactions on Image Processing 29, 9400-9412, 2020
Direct simulation Monte Carlo solution of subsonic flow through micro/nanoscale channels
E Roohi, M Darbandi, V Mirjalili
Some research problems in biometrics: The future beckons
A Ross, S Banerjee, C Chen, A Chowdhury, V Mirjalili, R Sharma, ...
2019 international conference on biometrics (ICB), 1-8, 2019
Protein structure refinement via molecular‐dynamics simulations: what works and what does not?
M Feig, V Mirjalili
Proteins: Structure, Function, and Bioinformatics 84, 282-292, 2016
Python 機械学習プログラミング
S Raschka, Y Liu, V Mirjalili
(No Title), 2018
Gender privacy: An ensemble of semi adversarial networks for confounding arbitrary gender classifiers
V Mirjalili, S Raschka, A Ross
2018 IEEE 9th International Conference on Biometrics Theory, Applications …, 2018
Flowsan: Privacy-enhancing semi-adversarial networks to confound arbitrary face-based gender classifiers
V Mirjalili, S Raschka, A Ross
IEEE Access 7, 99735-99745, 2019
Python machine learning
V Mirjalili, S Raschka
Marcombo, 2020
Density-biased sampling: a robust computational method for studying pore formation in membranes
V Mirjalili, M Feig
Journal of chemical theory and computation 11 (1), 343-350, 2015
DSMC solution of supersonic scale to choked subsonic flow in micro to nano channels
E Roohi, M Darbandi, V Mirjalili
ASME ICNMM 62282, 23-25, 2008
Interactions of amino acid side-chain analogs within membrane environments
V Mirjalili, M Feig
The Journal of Physical Chemistry B 119 (7), 2877-2885, 2015
Inverse biometrics: Generating vascular images from binary templates
C Kauba, S Kirchgasser, V Mirjalili, A Uhl, A Ross
IEEE Transactions on Biometrics, Behavior, and Identity Science 3 (4), 464-478, 2021
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