Joint Hierarchical Bayesian Learning of Full-structure Noise for Brain Source Imaging
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[1] Hejia Zhang,et al. Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis , 2020, Neuropsychologia.
[2] Danna Zhou,et al. d. , 1840, Microbial pathogenesis.
[3] Bhaskar D. Rao,et al. Sparse Bayesian learning for basis selection , 2004, IEEE Transactions on Signal Processing.
[4] Stefan Haufe,et al. Improving EEG Source Localization Through Spatio-Temporal Sparse Bayesian Learning , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[5] M. Burger,et al. Variational regularisation for inverse problems with imperfect forward operators and general noise models , 2020, Inverse problems.
[6] Mohammad Rostami,et al. Efficient Environmental Temperature Monitoring Using Compressed Sensing , 2016, 2016 Data Compression Conference (DCC).
[7] Daniel P. Palomar,et al. A Signal Processing Perspective of Financial Engineering , 2016, Found. Trends Signal Process..
[8] Julia P. Owen,et al. Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG , 2010, NeuroImage.
[9] Giuseppe Caire,et al. Massive MIMO Channel Subspace Estimation From Low-Dimensional Projections , 2015, IEEE Transactions on Signal Processing.
[10] Prabhu Babu,et al. Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning , 2017, IEEE Transactions on Signal Processing.
[11] David P. Wipf,et al. Iterative Reweighted 1 and 2 Methods for Finding Sparse Solutions , 2010, IEEE J. Sel. Top. Signal Process..
[12] Alexandre Gramfort,et al. Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression , 2017, AISTATS.
[13] Sandeep Kumar,et al. A Unified Framework for Structured Graph Learning via Spectral Constraints , 2019, J. Mach. Learn. Res..
[14] Bhaskar D. Rao,et al. Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach , 2015, IEEE Transactions on Signal Processing.
[15] I. Holopainen. Riemannian Geometry , 1927, Nature.
[16] Mohamed Hebiri,et al. Learning Heteroscedastic Models by Convex Programming under Group Sparsity , 2013, ICML.
[17] Jonathan D. Cohen,et al. Matrix-normal models for fMRI analysis , 2017, AISTATS.
[18] Hendrik Bernd Petersen,et al. Robust Instance-Optimal Recovery of Sparse Signals at Unknown Noise Levels , 2020, Information and Inference: A Journal of the IMA.
[19] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[20] Hongzhe Li,et al. High‐Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis , 2012, Biometrics.
[21] Ali Hashemi,et al. Thermal Source Localization Through Infinite-Dimensional Compressed Sensing , 2017, 1710.02016.
[22] Wei Wu,et al. Bayesian Machine Learning: EEG\/MEG signal processing measurements , 2016, IEEE Signal Processing Magazine.
[23] Giuseppe Caire,et al. Structured Channel Covariance Estimation from Limited Samples in Massive MIMO , 2019, ICC 2020 - 2020 IEEE International Conference on Communications (ICC).
[24] Chang Cai,et al. Robust estimation of noise for electromagnetic brain imaging with the champagne algorithm , 2021, NeuroImage.
[25] J. Jost. Riemannian geometry and geometric analysis , 1995 .
[26] Bhaskar D. Rao,et al. Sparse Signal Recovery With Temporally Correlated Source Vectors Using Sparse Bayesian Learning , 2011, IEEE Journal of Selected Topics in Signal Processing.
[27] Bertrand Thirion,et al. Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates , 2019, IPMI.
[28] Adeel Razi,et al. Bayesian fusion and multimodal DCM for EEG and fMRI , 2019, NeuroImage.
[29] D. Lehmann,et al. Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. , 1994, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[30] Leonidas J. Guibas,et al. The Earth Mover's Distance as a Metric for Image Retrieval , 2000, International Journal of Computer Vision.
[31] George Eastman House,et al. Sparse Bayesian Learning and the Relevance Vector Machine , 2001 .
[32] Christoph F. Mecklenbräuker,et al. Multisnapshot Sparse Bayesian Learning for DOA , 2016, IEEE Signal Processing Letters.
[33] Jonathan W. Pillow,et al. A Bayesian method for reducing bias in neural representational similarity analysis , 2016, bioRxiv.
[34] A. Gramfort,et al. Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods , 2012, Physics in medicine and biology.
[35] Andreas Ziehe,et al. Combining sparsity and rotational invariance in EEG/MEG source reconstruction , 2008, NeuroImage.
[36] Stefan Haufe,et al. Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework , 2020, NeuroImage.
[37] Axel Flinth,et al. Approximate Recovery of Initial Point-like and Instantaneous Sources from Coarsely Sampled Thermal Fields via Infinite-Dimensional Compressed Sensing , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[38] Bhaskar D. Rao,et al. An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem , 2007, IEEE Transactions on Signal Processing.
[39] Ming Bo Cai,et al. Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias , 2019, PLoS Comput. Biol..