Investigating the predictive value of whole-brain structural MR scans in autism: A pattern classification approach. - Christine Ecker; Vanessa Rocha-Rego; Patrick J. Johnston; Janaina Mourão Miranda; Andre F. Marquand; Eileen M. Daly; Michael J. Brammer; Clodagh Murphy; Declan G. M. Murphy (NeuroImage, 2010)

Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes. - Andre F. Marquand; Matthew Howard 002; Michael John Brammer; Carlton Chu; Steven Coen; Janaina Mourão Miranda (NeuroImage, 2010)

Data-Driven Modeling of BOLD Drug Response Curves Using Gaussian Process Learning. - Orla M. Doyle; Mitul A. Mehta; Michael J. Brammer; Adam J. Schwarz; Sara De Simoni; Andre F. Marquand (MLINI, 2011)

Prognostic prediction of therapeutic response in depression using high-field MR imaging. - Qiyong Gong; Qizhu Wu; Cristina Scarpazza; Su Lui; Zhiyun Jia; Andre F. Marquand; Xiaoqi Huang; Philip K. McGuire; Andrea Mechelli (NeuroImage, 2011)

Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine. - Janaina Mourão Miranda; David R. Hardoon; Tim Hahn; Andre F. Marquand; Steven C. R. Williams; John Shawe-Taylor; Michael J. Brammer (NeuroImage, 2011)

Dissociable effects of methylphenidate, atomoxetine and placebo on regional cerebral blood flow in healthy volunteers at rest: A multi-class pattern recognition approach. - Andre F. Marquand; Owen G. O'Daly; Sara De Simoni; David C. Alsop; Ralph Paul Maguire; Steven C. R. Williams; Fernando O. Zelaya; Mitul A. Mehta (NeuroImage, 2012)

Multivariate decoding of brain images using ordinal regression. - Orla M. Doyle; John Ashburner; Fernando O. Zelaya; Stephen C. R. Williams; Mitul A. Mehta; Andre F. Marquand (NeuroImage, 2013)

Test-retest reliability of the BOLD pharmacological MRI response to ketamine in healthy volunteers. - Sara De Simoni; Adam J. Schwarz; Owen G. O'Daly; Andre F. Marquand; Claire Brittain; C. Gonzales; S. Stephenson; Stephen C. R. Williams; Mitul A. Mehta (NeuroImage, 2013)

PRoNTo: Pattern Recognition for Neuroimaging Toolbox. - Jessica Schrouff; Maria João Duarte Rosa; Jane M. Rondina; Andre F. Marquand; Carlton Chu; John Ashburner; Christophe Phillips; Jonas Richiardi; Janaina Mourão Miranda (Neuroinformatics, 2013)

Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data. - Andrew D. O'Harney; Andre F. Marquand; Katya Rubia; Kaylita Chantiluke; Anna B. Smith; Ana Cubillo; Camilla Blain; Maurizio Filippone (ICPR, 2014)

Full Bayesian multi-task learning for multi-output brain decoding and accommodating missing data. - Andre F. Marquand; Steven C. R. Williams; Orla M. Doyle; Maria João Duarte Rosa (PRNI, 2014)

Bayesian multi-task learning for decoding multi-subject neuroimaging data. - Andre F. Marquand; Michael J. Brammer; Steven C. R. Williams; Orla M. Doyle (NeuroImage, 2014)

SCoRS - A Method Based on Stability for Feature Selection and Apping in Neuroimaging. - Jane M. Rondina; Tim Hahn; Leticia de Oliveira; Andre F. Marquand; Thomas Dresler; Thomas Leitner; Andreas J. Fallgatter; John Shawe-Taylor; Janaina Mourão Miranda (IEEE Trans. Medical Imaging, 2014)

Correction to "SCoRS - A Method Based on Stability for Feature Selection and Mapping in Neuroimaging". - Jane M. Rondina; Tim Hahn; Leticia de Oliveira; Andre F. Marquand; Thomas Dresler; Thomas Leitner; Andreas J. Fallgatter; John Shawe-Taylor; Janaina Mourão Miranda (IEEE Trans. Medical Imaging, 2014)

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions. - Ismael Huertas; Marianne Oldehinkel; Erik S. B. van Oort; David Garcia-Solis; Pablo Mir; Christian F. Beckmann; Andre F. Marquand (NeuroImage, 2017)

Normative Modeling of Neuroimaging Data Using Scalable Multi-task Gaussian Processes. - Seyed Mostafa Kia; Andre F. Marquand (MICCAI (3), 2018)

Scalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data. - Seyed Mostafa Kia; Christian F. Beckmann; Andre F. Marquand (CoRR, 2018)

Connectopic mapping with resting-state fMRI. - Koen V. Haak; Andre F. Marquand; Christian F. Beckmann (NeuroImage, 2018)

Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging Data. - Seyed Mostafa Kia; Andre F. Marquand (MIDL, 2019)

Hierarchical Bayesian Regression for Multi-site Normative Modeling of Neuroimaging Data. - Seyed Mostafa Kia; Hester Huijsdens; Richard Dinga; Thomas Wolfers; Maarten Mennes; Ole A. Andreassen; Lars T. Westlye; Christian F. Beckmann; Andre F. Marquand (MICCAI (7), 2020)

Warped Bayesian linear regression for normative modelling of big data. - Charlotte J. Fraza; Richard Dinga; Christian F. Beckmann; Andre F. Marquand (NeuroImage, 2021)

Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression. - Julio E. Villalon-Reina; Clara Moreau; Talia M. Nir; Neda Jahanshad; Anne M. Maillard; David Romascano; Bogdan Draganski; Sarah Lippé; Carrie E. Bearden; Seyed Mostafa Kia; Andre F. Marquand; Sébastien Jacquemont; et al. (MICCAI (1), 2022)

PROMISSING: Pruning Missing Values in Neural Networks. - Seyed Mostafa Kia; Nastaran Mohammadian Rad; Daniel van Opstal; Bart van Schie; Andre F. Marquand; Josien P. W. Pluim; Wiepke Cahn; Hugo G. Schnack (CoRR, 2022)

Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models. - Johanna M. M. Bayer; Richard Dinga; Seyed Mostafa Kia; Akhil R. Kottaram; Thomas Wolfers; Jinglei Lv; Andrew Zalesky; Lianne Schmaal; Andre F. Marquand (NeuroImage, 2022)

Deep neural networks learn general and clinically relevant representations of the ageing brain. - Esten H. Leonardsen; Han Peng; Tobias Kaufmann 001; Ingrid Agartz; Ole A. Andreassen; Elisabeth Gulowsen Celius; Thomas Espeseth; Hanne F. Harbo; Einar A. Høgestøl; Ann-Marie G. de Lange; Andre F. Marquand; Dídac Vidal-Piñeiro; et al. (NeuroImage, 2022)

Learning Cortical Anomaly through Masked Encoding for Unsupervised Heterogeneity Mapping. - Hao-Chun Yang; Ole A. Andreassen; Lars Tjelta Westlye; Andre F. Marquand; Christian F. Beckmann; Thomas Wolfers (ISBI, 2024)

To which reference class do you belong? Measuring racial fairness of reference classes with normative modeling. - Saige Rutherford; Thomas Wolfers; Charlotte J. Fraza; Nathaniel G. Harnett; Christian F. Beckmann; Henricus G. Ruhe; Andre F. Marquand (MLHC, 2024)

To which reference class do you belong? Measuring racial fairness of reference classes with normative modeling. - Saige Rutherford; Thomas Wolfers; Charlotte J. Fraza; Nathaniel G. Harrnet; Christian F. Beckmann; Henricus G. Ruhe; Andre F. Marquand (CoRR, 2024)

Self-Supervised Masked Mesh Learning for Unsupervised Anomaly Detection on 3D Cortical Surfaces. - Hao-Chun Yang; Sicheng Dai; Saige Rutherford; Christian Gaser; Andre F. Marquand; Christian F. Beckmann; Thomas Wolfers (CoRR, 2024)

Smartphone keyboard dynamics predict affect in suicidal ideation. - Loran Knol; Anisha Nagpal; Imogen E. Leaning; Elena Idda; Faraz Hussain 002; Emma Ning; Tory A. Eisenlohr-Moul; Christian F. Beckmann; Andre F. Marquand; Alex D. Leow (npj Digit. Medicine, 2024)

Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence. - Esten H. Leonardsen; Karin Persson; Edvard Grødem; Nicola Dinsdale; Till Schellhorn; James M. Roe; Dídac Vidal-Piñeiro; Øystein Sørensen; Tobias Kaufmann 001; Eric Westman; Andre F. Marquand; Geir Selbæk; et al. (npj Digit. Medicine, 2024)