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Graph neural networks (GNN) rely on graph operations that include neural network training for various graph related tasks.
A comprehensive survey on graph neural networks
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Graph embedding using infomax for asd classification and brain functional difference detection
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A reduction of a graph to a canonical form and an algebra arising during this reduction
Weisfeiler, B. and Lehman, A. A. (1968) · 1968
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Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
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Understanding graph isomorphism network for brain mr functional connectivity analysis
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Small-world networks and disturbed functional connectivity in schizophrenia
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Default mode network connectivity: effects of age, sex, and analytic approach
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Visualizing data using t-sne
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Human brain networks in health and disease
Bassett, D. S. and Bullmore, E. T. (2009) · 2009
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Toward discovery science of human brain function
Biswal, B. B., Mennes, M., Zuo, X.-N., Gohel, S., Kelly, C., Smith, S. M., et al. (2010) · 2010
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Graph theoretical modeling of brain connectivity
He, Y. and Evans, A. (2010) · 2010
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Graph-based network analysis of resting-state functional mri
Wang, J., Zuo, X., and He, Y. (2010) · 2010
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A baseline for the multivariate comparison of resting-state networks
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., et al. (2011) · 2011
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Wavelets on graphs via spectral graph theory
Hammond, D. K., Vandergheynst, P., and Gribonval, R. (2011) · 2011
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Weisfeiler-Lehman graph kernels
Shervashidze, N., Schweitzer, P., Leeuwen, E. J. v., Mehlhorn, K., and Borgwardt, K. M. (2011) · 2011
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The organization of the human cerebral cortex estimated by intrinsic functional connectivity
Thomas Yeo, B., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. (2011) · 2011
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Hemisphere-and gender-related differences in small-world brain networks: a resting-state functional mri study
Tian, L., Wang, J., Yan, C., and He, Y. (2011) · 2011
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Spectral networks and locally connected networks on graphs
Bruna, J., Zaremba, W., Szlam, A., and LeCun, Y. (2013) · 2013
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The minimal preprocessing pipelines for the human connectome project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., et al. (2013) · 2013
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The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
Shuman, D. I., Narang, S. K., Frossard, P., Ortega, A., and Vandergheynst, P. (2013) · 2013
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The wu-minn human connectome project: an overview
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E., Yacoub, E., Ugurbil, K., et al. (2013) · 2013
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Ica-based artefact removal and accelerated fmri acquisition for improved resting state network imaging
Griffanti, L., Salimi-Khorshidi, G., Beckmann, C. F., Auerbach, E. J., Douaud, G., Sexton, C. E., et al. (2014) · 2014
Grad-cam: Visual explanations from deep networks via gradient-based localization
Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., and Batra, D. (2017) · 2017
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Assessing and tuning brain decoders: cross-validation, caveats, and guidelines
Varoquaux, G., Raamana, P. R., Engemann, D. A., Hoyos-Idrobo, A., Schwartz, Y., and Thirion, B. (2017) · 2017
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Graph saliency maps through spectral convolutional networks: Application to sex classification with brain connectivity
Arslan, S., Ktena, S. I., Glocker, B., and Rueckert, D. (2018) · 2018
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A graph signal processing perspective on functional brain imaging
Huang, W., Bolton, T. A., Medaglia, J. D., Bassett, D. S., Ribeiro, A., and Van De Ville, D. (2018) · 2018
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Metric learning with spectral graph convolutions on brain connectivity networks
Ktena, S. I., Parisot, S., Ferrante, E., Rajchl, M., Lee, M., Glocker, B., et al. (2018) · 2018
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Resting states are resting traits–an fmri study of sex differences and menstrual cycle effects in resting state cognitive control networks
Hjelmervik, H., Hausmann, M., Osnes, B., Westerhausen, R., and Specht, K. (2014) · 2014
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Automatic denoising of functional mri data: combining independent component analysis and hierarchical fusion of classifiers
Salimi-Khorshidi, G., Douaud, G., Beckmann, C. F., Glasser, M. F., Griffanti, L., and Smith, S. M. (2014) · 2014
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Gretna: a graph theoretical network analysis toolbox for imaging connectomics
Wang, J., Wang, X., Xia, M., Liao, X., Evans, A., and He, Y. (2015) · 2015
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Gender differences in cerebral regional homogeneity of adult healthy volunteers: a resting-state fmri study
Xu, C., Li, C., Wu, H., Wu, Y., Hu, S., Zhu, Y., et al. (2015) · 2015
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Semi-supervised classification with graph convolutional networks
Kipf, T. N. and Welling, M. (2016) · 2016
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Learning deep features for discriminative localization
Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., and Torralba, A. (2016) · 2016
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Network neuroscience
Bassett, D. S. and Sporns, O. (2017) · 2017
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Similarity learning with higher-order proximity for brain network analysis
Ma, G., Ahmed, N. K., Willke, T., Sengupta, D., Cole, M. W., Turk-Browne, N., et al. (2018) · 2018
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Graph signal processing: Overview, challenges, and applications
Ortega, A., Frossard, P., Kovačević, J., Moura, J. M., and Vandergheynst, P. (2018) · 2018
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Disease prediction using graph convolutional networks: Application to autism spectrum disorder and alzheimer’s disease
Parisot, S., Ktena, S. I., Ferrante, E., Lee, M., Guerrero, R., Glocker, B., et al. (2018) · 2018
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Graph theory methods: applications in brain networks
Sporns, O. (2018) · 2018
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Veličković, P., Fedus, W., Hamilton, W. L., Liò, P., Bengio, Y., and Hjelm, R. D. (2018) · 2018
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Functional connectivity predicts gender: evidence for gender differences in resting brain connectivity
Zhang, C., Dougherty, C. C., Baum, S. A., White, T., and Michael, A. M. (2018) · 2018
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Regression activation mapping on the cortical surface using graph convolutional networks
Duffy, B. A., Liu, M., Flynn, T., Toga, A., Barkovich, A. J., Xu, D., et al. (2019) · 2019
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Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics
He, T., Kong, R., Holmes, A. J., Nguyen, M., Sabuncu, M. R., Eickhoff, S. B., et al. (2019) · 2019
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Individual-specific fmri-subspaces improve functional connectivity prediction of behavior
Kashyap, R., Kong, R., Bhattacharjee, S., Li, J., Zhou, J., and Yeo, B. T. (2019) · 2019
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Sex Classification by Resting State Brain Connectivity
Weis, S., Patil, K. R., Hoffstaedter, F., Nostro, A., Yeo, B. T. T., and Eickhoff, S. B. (2019) · 2019
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Understanding geometry of encoder-decoder CNNs
Ye, J. C. and Sung, W. K. (2019) · 2019
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