Giovanni Montana

发表

Adaptive regularization for Lasso models in the context of nonstationary data streams

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2016, Stat. Anal. Data Min..

A Skew-t-Normal Multi-Level Reduced-Rank Functional PCA Model with Applications to Replicated `Omics Time Series Data Sets

Giovanni Montana, Maurice Berk, 2011 .

Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks

Giovanni Montana, Samuel Withey, Robert Bakewell, 2016, Louhi@EMNLP.

Brain image classification based on automated morphometry and penalised linear discriminant analysis with resampling

Giovanni Montana, Daniel Schwarz, Eva Janousová, 2015, 2015 Federated Conference on Computer Science and Information Systems (FedCSIS).

Measuring the functional connectome "on-the-fly": towards a new control signal for fMRI-based brain-computer interfaces

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2015, 1502.02309.

Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression☆

Paul M. Thompson, Giovanni Montana, Xue Hua, 2012, NeuroImage.

Special Issue on Advances in Data Mining and Robust Statistics

Stefan Van Aelst, Ruben H. Zamar, Giovanni Montana, 2016, Comput. Stat. Data Anal..

Sparse partial least squares regression for on-line variable selection with multivariate data streams

Giovanni Montana, Brian McWilliams, Brian McWilliams, 2010 .

Classifying HCP task-fMRI networks using heat kernels

Ricardo Pio Monti, Giovanni Montana, A. W. Chung, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Dynamic modeling of mean-reverting spreads for statistical arbitrage

Giovanni Montana, Kostas Triantafyllopoulos, G. Montana, 2008, Comput. Manag. Sci..

The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2016, NeuroImage.

Classifier calibration using splined empirical probabilities in clinical risk prediction

Giovanni Montana, Simon Jones, Alex Bottle, 2015, Health care management science.

Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks

Giovanni Montana, Adrien Payan, G. Montana, 2015, ICPRAM 2015.

Learning population and subject-specific brain connectivity networks via Mixed Neighborhood Selection

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2015, 1512.01947.

Automated Segmentation on the Entire Cardiac Cycle Using a Deep Learning Work - Flow

Pablo Lamata, Giovanni Montana, Nicoló Savioli, 2018, 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS).

Deep neural networks for anatomical brain segmentation

Giovanni Montana, Alexandre de Brébisson, A. D. Brébisson, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Deep metric learning for multi-labelled radiographs

Giovanni Montana, Mauro Annarumma, Mauro Annarumma, 2017, SAC.

Distance-based differential analysis of gene curves

Giovanni Montana, Christopher Minas, Simon J. Waddell, 2011, Bioinform..

Functional modelling of microarray time series with covariate curves

Giovanni Montana, Maurice Berk, 2009 .

Data stream mining for market-neutral algorithmic trading

Giovanni Montana, Kostas Triantafyllopoulos, Theodoros Tsagaris, 2008, SAC '08.

Multi-agent Deep Reinforcement Learning with Extremely Noisy Observations pdf

Giovanni Montana, Ozsel Kilinc, G. Montana, 2018, ArXiv.

A statistical framework for biomarker discovery in metabolomic time course data

Giovanni Montana, Maurice Berk, Timothy M. D. Ebbels, 2011, Bioinform..

Longitudinal detection of radiological abnormalities with time-modulated LSTM pdf

Giovanni Montana, Samuel Withey, Ruggiero Santeramo, 2018, DLMIA/ML-CDS@MICCAI.

Text-mining the neurosynth corpus using deep boltzmann machines

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Recurrent Convolutional Networks for Pulmonary Nodule Detection in CT Imaging pdf

Giovanni Montana, Petros-Pavlos Ypsilantis, G. Montana, 2016, ArXiv.

Network-guided regression for detecting associations between DNA methylation and gene expression

Zi Wang, Giovanni Montana, Edward W. J. Curry, 2014, Bioinform..

A distance-based test of association between paired heterogeneous genomic data

Giovanni Montana, Christopher Minas, Edward W. J. Curry, 2013, Bioinform..

Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2017, Front. Comput. Neurosci..

A framework for adaptive regularization in streaming Lasso models pdf

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2016, ArXiv.

A Generative Adversarial Model for Right Ventricle Segmentation pdf

Pablo Lamata, Giovanni Montana, Nicoló Savioli, 2018, ArXiv.

Learning what to look in chest X-rays with a recurrent visual attention model pdf

Giovanni Montana, Petros-Pavlos Ypsilantis, G. Montana, 2017, ArXiv.

Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

Ricardo Pio Monti, Giovanni Montana, Robert Leech, 2017 .

False positives in neuroimaging genetics using voxel-based morphometry data

Thomas E. Nichols, Giovanni Montana, Matt Silver, 2011, NeuroImage.

Characterising brain network topologies: A dynamic analysis approach using heat kernels

Paul Aljabar, Giovanni Montana, A. W. Chung, 2016, NeuroImage.

Multi‐view predictive partitioning in high dimensions

Giovanni Montana, Brian McWilliams, Brian McWilliams, 2012, Stat. Anal. Data Min..

Exploring Brain Transcriptomic Patterns: A Topological Analysis Using Spatial Expression Networks

Giovanni Montana, Zhana Kuncheva, Michelle L. Krishnan, 2016, PSB.

Estimating time-varying brain connectivity networks from functional MRI time series

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2013, NeuroImage.

V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation pdf

Pablo Lamata, Giovanni Montana, Nicoló Savioli, 2018, STACOM@MICCAI.

Subspace clustering of high-dimensional data: a predictive approach

Giovanni Montana, Brian McWilliams, Brian McWilliams, 2012, Data Mining and Knowledge Discovery.

Statistical software for gene mapping by admixture linkage disequilibrium

Giovanni Montana, Clive J. Hoggart, C. Hoggart, 2007, Briefings Bioinform..

Learning to Trade with Incremental Support Vector Regression Experts

Giovanni Montana, Francesco Parrella, G. Montana, 2008, HAIS.

Sparse partial least squares regression for on‐line variable selection with multivariate data streams

Giovanni Montana, Brian McWilliams, Brian McWilliams, 2010, Stat. Anal. Data Min..

Improving coordination in small-scale multi-agent deep reinforcement learning through memory-driven communication

Giovanni Montana, Emanuele Pesce, G. Montana, 2019, Mach. Learn..

Predictive Subspace Clustering

Giovanni Montana, Brian McWilliams, Brian McWilliams, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation pdf

Pablo Lamata, Giovanni Montana, Rudra P. K. Poudel, 2016, RAMBO+HVSMR@MICCAI.

Differential analysis of biological networks

Giovanni Montana, Da Ruan, Alastair Young, 2015, BMC Bioinformatics.

Multi-scale Community Detection in Temporal Networks Using Spectral Graph Wavelets

Giovanni Montana, Zhana Kuncheva, G. Montana, 2017, PAP@PKDD/ECML.

Learning Attention from Multi-Modal Imaging and Text: Application for Lesion Localisation in DWI

Liang Chen, Daniel Rueckert, Giovanni Montana, 2018 .

A Bayesian mixture of lasso regressions with t-errors

Giovanni Montana, Ajay Jasra, Adam Persing, 2014, Comput. Stat. Data Anal..

A Skew-t-Normal Multi-level Reduced-Rank Functional PCA Model for the Analysis of Replicated Genomics Time Course Data

Giovanni Montana, Maurice Berk, 2012, IDA.

Stopping criteria for boosting automatic experimental design using real-time fMRI with Bayesian optimization

Christoforos Anagnostopoulos, Giovanni Montana, Robert Leech, 2015 .

Statistical methods in genetics

Giovanni Montana, G. Montana, 2006, Briefings Bioinform..

Sparse partial least squares for on-line variable selection in multivariate data streams

Giovanni Montana, Brian McWilliams, 2009 .

Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Studying the brain from adolescence to adulthood through sparse multi-view matrix factorisations

Chiara Nosarti, Zi Wang, Giovanni Montana, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Flexible least squares for temporal data mining and statistical arbitrage

Giovanni Montana, Kostas Triantafyllopoulos, Theodoros Tsagaris, 2007, Expert Syst. Appl..

Fast Brain-Wide Search of Highly Discriminative Regions in Medical Images: an Application to Alzheimers Disease

Daniel Rueckert, Robin Wolz, Giovanni Montana, 2011, MIUA.

Community detection in multiplex networks using Locally Adaptive Random walks

Giovanni Montana, Zhana Kuncheva, G. Montana, 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

An Agent Based Architecture for Manufacturing E-Marketplaces

Giovanni Montana, Giovanni Perrone, 2005 .

CRAN Task View: Statistical Genetics

Giovanni Montana, G. Montana, 2019 .

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

Limsoon Wong, Giovanni Montana, Yue Wang, 2013, BMC Bioinformatics.

Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data

Christoforos Anagnostopoulos, Ricardo Pio Monti, Giovanni Montana, 2015, 2015 International Workshop on Pattern Recognition in NeuroImaging.

Distance‐based analysis of variance: Approximate inference

Giovanni Montana, Christopher Minas, G. Montana, 2014, Stat. Anal. Data Min..

Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound pdf

Pablo Lamata, Giovanni Montana, Enrico Grisan, 2018, ICANN.