Gang Qu

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All published works

Action	Title	Year	Authors
+ PDF Chat	Integrated Brain Connectivity Analysis with fMRI, DTI, and sMRI Powered by Interpretable Graph Neural Networks.	2024	Gang Qu Ziyu Zhou Vince D. Calhoun Aiying Zhang Yu‐Ping Wang
+ PDF Chat	A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds	2024	Anton Orlichenko Gang Qu Ziyu Zhou Anqi Liu Hong‐Wen Deng Zhengming Ding Julia M. Stephen Tony W. Wilson Vince D. Calhoun Yu-Ping Wang
+ PDF Chat	A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds	2024	Anton Orlichenko Gang Qu Ziyu Zhou Anqi Liu Hong‐Wen Deng Zhengming Ding Julia M. Stephen Tony W. Wilson Vince D. Calhoun Yu-Ping Wang
+ PDF Chat	An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis	2024	Ziyu Zhou Anton Orlichenko Gang Qu Zening Fu Vince D. Calhoun Zhengming Ding Yu‐Ping Wang
+	Exploring General Intelligence via Gated Graph Transformer in Functional Connectivity Studies	2024	Gang Qu Anton Orlichenko Junqi Wang Gemeng Zhang Xiao Li Aiying Zhang Zheng‐Ming Ding Yu-Ping Wang
+	Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results	2023	Anton Orlichenko Gang Qu Kuan-Jui Su Anqi Liu Hui Shen Hong‐Wen Deng Yu‐Ping Wang
+	Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results	2023	Anton Orlichenko Gang Qu Kuan-Jui Su Anqi Liu Hui Shen Hong‐Wen Deng Yu‐Ping Wang
+ PDF Chat	Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results	2023	Anton Orlichenko Gang Qu Kuan-Jui Su Anqi Liu Hui Shen Hong‐Wen Deng Yu‐Ping Wang
+	Angle Basis: a Generative Model and Decomposition for Functional Connectivity	2023	Anton Orlichenko Gang Qu Ziyu Zhou Zheng‐Ming Ding Yu‐Ping Wang
+	Angle Basis: a Generative Model and Decomposition for Functional Connectivity	2023	Anton Orlichenko Gang Qu Ziyu Zhou Zheng‐Ming Ding Yu‐Ping Wang
+	Angle Basis: a Generative Model and Decomposition for Functional Connectivity	2023	Anton Orlichenko Gang Qu Ziyu Zhou Zhengming Ding Yu‐Ping Wang
+	Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results	2023	Anton Orlichenko Gang Qu Kuan-Jui Su Anqi Liu Hui Shen Hong‐Wen Deng Yu‐Ping Wang
+ PDF Chat	Latent Similarity Identifies Important Functional Connections for Phenotype Prediction	2022	Anton Orlichenko Gang Qu Gemeng Zhang Binish Patel Tony W. Wilson Julia M. Stephen Vince D. Calhoun Yu‐Ping Wang
+	Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies	2022	Li Xiao Biao Cai Gang Qu Gemeng Zhang Julia M. Stephen Tony W. Wilson Vince D. Calhoun Yu‐Ping Wang
+	Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction	2021	Gang Qu Li Xiao Wenxing Hu Junqi Wang Kun Zhang Vince D. Calhoun Yu‐Ping Wang
+	Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition	2021	Wenxing Hu Xiang-He Meng Yuntong Bai Aiying Zhang Gang Qu Biao Cai Gemeng Zhang Tony W. Wilson Julia M. Stephen Vince D. Calhoun
+	Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction	2021	Gang Qu Li Xiao Wenxing Hu Kun Zhang Vince D. Calhoun Yu‐Ping Wang
+	Distance Correlation Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies	2020	Xiao Li Biao Cai Gang Qu Julia M. Stephen Tony W. Wilson Vince D. Calhoun Yu‐Ping Wang

Common Coauthors

Coauthor	Papers Together
Yu‐Ping Wang	15
Vince D. Calhoun	10
Anton Orlichenko	7
Hong‐Wen Deng	6
Tony W. Wilson	6
Julia M. Stephen	6
Anton Orlichenko	5
Anqi Liu	5
Hui Shen	4
Zhengming Ding	4
Gemeng Zhang	4
Kuan-Jui Su	4
Li Xiao	3
Yu-Ping Wang	3
Ziyu Zhou	3
Aiying Zhang	3
Wenxing Hu	3
Ziyu Zhou	3
Zheng‐Ming Ding	3
Biao Cai	2
Kun Zhang	2
Junqi Wang	2
Xiang-He Meng	1
Anqi Liu	1
Yuntong Bai	1
Xiao Li	1
Ziyu Zhou	1
Zening Fu	1
Binish Patel	1
Xiao Li	1
Biao Cai	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction	2021	Gang Qu Li Xiao Wenxing Hu Junqi Wang Kun Zhang Vince D. Calhoun Yu‐Ping Wang	5
+ PDF Chat	Quality of Education Predicts Performance on the Wide Range Achievement Test-4th Edition Word Reading Subtest	2014	Philip Sayegh Alyssa Arentoft Nicholas S. Thaler A. C. Dean April D. Thames	5
+ PDF Chat	A real-world demonstration of machine learning generalizability in the detection of intracranial hemorrhage on head computerized tomography	2021	Hojjat Salehinejad Jumpei Kitamura Noah Ditkofsky Amy Lin Aditya Bharatha Suradech Suthiphosuwan Hui-Ming Lin Jefferson R. Wilson Muhammad Mamdani Errol Colak	4
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	4
+ PDF Chat	Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization	2017	Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra	3
+	Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition	2021	Wenxing Hu Xiang-He Meng Yuntong Bai Aiying Zhang Gang Qu Biao Cai Gemeng Zhang Tony W. Wilson Julia M. Stephen Vince D. Calhoun	3
+	Promises and pitfalls of topological data analysis for brain connectivity analysis	2021	Luigi Caputi Anna Pidnebesna Jaroslav Hlinka	3
+	Semi-Supervised Classification with Graph Convolutional Networks	2016	Thomas Kipf Max Welling	3
+ PDF Chat	Brain age prediction based on resting-state functional connectivity patterns using convolutional neural networks	2018	Hongming Li Theodore D. Satterthwaite Yong Fan	3
+ PDF Chat	BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks	2022	Hejie Cui Wei Dai Yanqiao Zhu Xuan Kan Antonio Aodong Chen Gu Joshua Lukemire Liang Zhan Lifang He Ying Guo Carl Yang	3
+ PDF Chat	Latent Similarity Identifies Important Functional Connections for Phenotype Prediction	2022	Anton Orlichenko Gang Qu Gemeng Zhang Binish Patel Tony W. Wilson Julia M. Stephen Vince D. Calhoun Yu‐Ping Wang	3
+	ImageNomer: developing an fMRI and omics visualization tool to detect racial bias in functional connectivity	2023	Anton Orlichenko Grant Daly Yu‐Ping Wang Anqi Liu Hui Shen Hong‐Wen Deng Ziyu Zhou	3
+	Angle Basis: a Generative Model and Decomposition for Functional Connectivity	2023	Anton Orlichenko Gang Qu Ziyu Zhou Zheng‐Ming Ding Yu‐Ping Wang	3
+ PDF Chat	Confound-leakage: confound removal in machine learning leads to leakage	2022	Sami Hamdan Bradley C. Love Georg G. von Polier Susanne Weis Holger Schwender Simon B. Eickhoff Kaustubh R. Patil	3
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James T. Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	2
+	Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease	2018	Xi Zhang Lifang He Kun Chen Yuan Luo Jiayu Zhou Fei Wang	2
+	Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates	2016	Anders Eklund Thomas E. Nichols Hans Knutsson	2
+	Latent Similarity Identifies Important Functional Connections for Phenotype Prediction	2023	Anton Orlichenko	2
+ PDF Chat	Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks	2018	Aditya Chattopadhay Anirban Sarkar Prantik Howlader Vineeth N Balasubramanian	2
+	Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation	2022	Yee Fan Tan Chee-Ming Ting Fuad Noman Raphaël C. -W. Phan Hernando Ombao	2
+	mixup: Beyond Empirical Risk Minimization	2017	Hongyi Zhang Moustapha Cissé Yann Dauphin David López-Paz	2
+	RELATIONS BETWEEN TWO SETS OF VARIATES	1936	Harold Hotelling	2
+ PDF Chat	Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease	2018	Sarah Parisot Sofia Ira Ktena Enzo Ferrante Matthew Lee Ricardo Guerrero Ben Glocker Daniel Rueckert	2
+	Enforcing Co-Expression Within a Brain-Imaging Genomics Regression Framework	2017	Pascal Zillé Vince D. Calhoun Yu‐Ping Wang	2
+	Diabetic Retinopathy Detection via Deep Convolutional Networks for Discriminative Localization and Visual Explanation.	2017	Zhiguang Wang Jianbo Yang	2
+	Spectral Networks and Locally Connected Networks on Graphs	2013	Joan Bruna Wojciech Zaremba Arthur Szlam Yann LeCun	2
+ PDF Chat	Interpretable Explanations of Black Boxes by Meaningful Perturbation	2017	Ruth Fong Andrea Vedaldi	1
+	An overview of deep learning in medical imaging focusing on MRI	2018	Alexander Selvikvåg Lundervold Arvid Lundervold	1
+ PDF Chat	Progress in Brain Computer Interface: Challenges and Opportunities	2021	Simanto Saha Khondaker A. Mamun Khawza I. Ahmed Raqibul Mostafa Ganesh R. Naik Sam Darvishi Ahsan H. Khandoker Mathias Baumert	1
+	Graph neural networks: A review of methods and applications	2020	Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun	1
+ PDF Chat	Digital medicine and the curse of dimensionality	2021	Visar Berisha Chelsea Krantsevich P. Richard Hahn Shira Hahn Gautam Dasarathy Pavan Turaga Julie Liss	1
+	Transparency of deep neural networks for medical image analysis: A review of interpretability methods	2021	Zohaib Salahuddin Henry C. Woodruff Avishek Chatterjee Philippe Lambin	1
+ PDF Chat	SimMatch: Semi-supervised Learning with Similarity Matching	2022	Mingkai Zheng Shan You Lang Huang Fei Wang Chen Qian Chang Xu	1
+ PDF Chat	Machine learning for medical imaging: methodological failures and recommendations for the future	2022	Gaël Varoquaux Veronika Cheplygina	1
+	Joint Sparse Collaborative Regression on Imaging Genetics Study of Schizophrenia	2022	Xueli Song Rongpeng Li Kaiming Wang Yuntong Bai Yuzhu Xiao Yu‐Ping Wang	1
+	Room-temperature superconductivity — or not? Comment on <i>Nature</i> <b>586</b>, 373 (2020) by E. Snider <i>et al.</i>	2022	D. van der Marel J. E. Hirsch	1
+	Graph Attention Networks	2017	Petar Veličković Guillem Cucurull Arantxa Casanova Adriana Romero Píetro Lió Yoshua Bengio	1
+ PDF Chat	High-Resolution Image Synthesis with Latent Diffusion Models	2022	Robin Rombach Andreas Blattmann Dominik Lorenz Patrick Esser Björn Ommer	1
+	A kernel method for canonical correlation analysis	2006	Shotaro Akaho	1
+	ImageNomer: Description of a functional connectivity and omics analysis tool and case study identifying a race confound	2023	Anton Orlichenko Grant Daly Ziyu Zhou Anqi Liu Hui Shen Hong‐Wen Deng Yu‐Ping Wang	1
+	Spectral Networks and Locally Connected Networks on Graphs	2013	Joan Bruna Wojciech Zaremba Arthur Szlam Yann LeCun	1
+	The distance correlation<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si38.gif" display="inline" overflow="scroll"><mml:mi>t</mml:mi></mml:math>-test of independence in high dimension	2013	Gábor J. Székely Maria L. Rizzo	1
+ PDF Chat	Modeling disease progression via fused sparse group lasso	2012	Jiayu Zhou Jun Liu Vaibhav A. Narayan Jieping Ye	1
+ PDF Chat	A Method for Finding Structured Sparse Solutions to Nonnegative Least Squares Problems with Applications	2013	Ernie Esser Yifei Lou Jack Xin	1
+ PDF Chat	A well-conditioned estimator for large-dimensional covariance matrices	2003	Olivier Ledoit Michael Wolf	1
+	Striving for Simplicity: The All Convolutional Net	2014	Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller	1
+	How to control confounding effects by statistical analysis.	2012	Mohamad Amin Pourhoseingholi Ahmad Reza Baghestani Mohsen Vahedi	1
+ PDF Chat	Machine learning for neuroimaging with scikit-learn	2014	Alexandre Abraham Fabian Pedregosa Michael Eickenberg Philippe Gervais Andreas Mueller Jean Kossaifi Alexandre Gramfort Bertrand Thirion Gaël Varoquaux	1
+ PDF Chat	Learning Deep Features for Discriminative Localization	2016	Bolei Zhou Aditya Khosla Àgata Lapedriza Aude Oliva Antonio Torralba	1
+ PDF Chat	DeepChrome: deep-learning for predicting gene expression from histone modifications	2016	Ritambhara Singh Jack Lanchantin Gabriel Robins Yanjun Qi	1