Bayesian Machine Learning: EEG\/MEG signal processing measurements
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[1] Hubert Cecotti,et al. Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Wei Wu,et al. A hierarchical Bayesian approach for learning sparse spatio-temporal decompositions of multichannel EEG , 2011, NeuroImage.
[3] Emery N. Brown,et al. A Subspace Pursuit-based Iterative Greedy Hierarchical solution to the neuromagnetic inverse problem , 2013, NeuroImage.
[4] Karl J. Friston,et al. Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM☆ , 2014, NeuroImage.
[5] David B. Dunson,et al. Hierarchical Latent Dictionaries for Models of Brain Activation , 2012, AISTATS.
[6] Mark J. Schervish,et al. Nonstationary Covariance Functions for Gaussian Process Regression , 2003, NIPS.
[7] Dong Yu,et al. Deep Learning: Methods and Applications , 2014, Found. Trends Signal Process..
[8] Karl J. Friston,et al. Classical and Bayesian Inference in Neuroimaging: Theory , 2002, NeuroImage.
[9] Karl J. Friston,et al. Dynamic causal modeling for EEG and MEG , 2009, Human brain mapping.
[10] Emery N. Brown,et al. A spatiotemporal dynamic distributed solution to the MEG inverse problem , 2011, NeuroImage.
[11] Seungjin Choi,et al. Bayesian common spatial patterns with Dirichlet process priors for multi-subject EEG classification , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).
[12] Lawrence Carin,et al. Bayesian Compressive Sensing , 2008, IEEE Transactions on Signal Processing.
[13] J. Sarvas. Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. , 1987, Physics in medicine and biology.
[14] Kensuke Sekihara,et al. A probabilistic algorithm for robust interference suppression in bioelectromagnetic sensor data. , 2007, Statistics in medicine.
[15] David Heckerman,et al. A Tutorial on Learning with Bayesian Networks , 1999, Innovations in Bayesian Networks.
[16] David P. Wipf,et al. A unified Bayesian framework for MEG/EEG source imaging , 2009, NeuroImage.
[17] Julia P. Owen,et al. Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG , 2010, NeuroImage.
[18] Hagai Attias,et al. A graphical model for estimating stimulus-evoked brain responses from magnetoencephalography data with large background brain activity , 2006, NeuroImage.
[19] Zoubin Ghahramani,et al. Bayesian non-parametrics and the probabilistic approach to modelling , 2013, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[20] William P. Marnane,et al. Gaussian Process Modeling of EEG for the Detection of Neonatal Seizures , 2007, IEEE Transactions on Biomedical Engineering.
[21] Seungjin Choi,et al. Bayesian common spatial patterns for multi-subject EEG classification , 2014, Neural Networks.
[22] Gareth Roberts,et al. An adaptive approach to Langevin MCMC , 2012, Stat. Comput..
[23] Karl J. Friston,et al. MEG source localization under multiple constraints: An extended Bayesian framework , 2006, NeuroImage.
[24] Bhaskar D. Rao,et al. Latent Variable Bayesian Models for Promoting Sparsity , 2011, IEEE Transactions on Information Theory.
[25] K.-R. Muller,et al. Optimizing Spatial filters for Robust EEG Single-Trial Analysis , 2008, IEEE Signal Processing Magazine.
[26] Robert D. Nowak,et al. Space–time event sparse penalization for magneto-/electroencephalography , 2009, NeuroImage.
[27] Zhu Han,et al. Non-parametric Bayesian learning with deep learning structure and its applications in wireless networks , 2014, 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).
[28] Christian P. Robert,et al. The Bayesian choice : from decision-theoretic foundations to computational implementation , 2007 .
[29] F. L. D. Silva,et al. EEG signal processing , 2000, Clinical Neurophysiology.
[30] Karl J. Friston,et al. Electromagnetic source reconstruction for group studies , 2008, NeuroImage.
[31] David P. Wipf,et al. A New View of Automatic Relevance Determination , 2007, NIPS.
[32] Trevor Hastie,et al. Learning the Structure of Mixed Graphical Models , 2015, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.
[33] Wei Wu,et al. Probabilistic Common Spatial Patterns for Multichannel EEG Analysis , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[34] Julia P. Owen,et al. Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG data , 2012, NeuroImage.
[35] David P. Wipf,et al. Variational Bayesian Inference Techniques , 2010, IEEE Signal Processing Magazine.
[36] Tzyy-Ping Jung,et al. Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy Consumption and Inexpensive Hardware , 2012, IEEE Transactions on Biomedical Engineering.
[37] Richard M. Leahy,et al. Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..
[38] Trevor J. Hastie,et al. Structure Learning of Mixed Graphical Models , 2013, AISTATS.
[39] Anatole Lécuyer,et al. Classifying EEG for brain computer interfaces using Gaussian processes , 2008, Pattern Recognit. Lett..
[40] E.J. Candes,et al. An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.
[41] Wei Wu,et al. Bayesian estimation of ERP components from multicondition and multichannel EEG , 2014, NeuroImage.
[42] S. Baillet,et al. Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatio-temporal clustering , 2004, Clinical Neurophysiology.
[43] Karl J. Friston,et al. A Parametric Empirical Bayesian framework for fMRI‐constrained MEG/EEG source reconstruction , 2010, Human brain mapping.
[44] Hagai Attias,et al. Independent Factor Analysis , 1999, Neural Computation.
[45] Peter Green,et al. Markov chain Monte Carlo in Practice , 1996 .
[46] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[47] Yong Xu,et al. Sparse Representation for Brain Signal Processing: A tutorial on methods and applications , 2014, IEEE Signal Processing Magazine.
[48] Karl J. Friston,et al. Multiple sparse priors for the M/EEG inverse problem , 2008, NeuroImage.
[49] Hagai Attias,et al. A probabilistic algorithm integrating source localization and noise suppression for MEG and EEG data , 2006, NeuroImage.
[50] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.