On Shift-Invariant Sparse Coding. - Thomas Blumensath; Mike E. Davies 001 (ICA, 2004)

Unsupervised learning of sparse and shift-invariant decompositions of polyphonic music. - Thomas Blumensath; Mike E. Davies 001 (ICASSP (5), 2004)

A fast importance sampling algorithm for unsupervised learning of over-complete dictionaries. - Thomas Blumensath; Mike E. Davies 001 (ICASSP (5), 2005)

Sparse representations of polyphonic music. - Mark D. Plumbley; Samer A. Abdallah; Thomas Blumensath; Michael E. Davies 001 (Signal Process., 2006)

Sparse and shift-Invariant representations of music. - Thomas Blumensath; Mike E. Davies 001 (IEEE Trans. Speech Audio Process., 2006)

In greedy PURSUIT of new directions: (Nearly) Orthogonal Matching Pursuit by directional optimisation. - Thomas Blumensath; Mike E. Davies 001 (EUSIPCO, 2007)

Compressed Sensing and Source Separation. - Thomas Blumensath; Mike E. Davies 001 (ICA, 2007)

Iterative Hard Thresholding and L0 Regularisation. - Thomas Blumensath; Mehrdad Yaghoobi; Mike E. Davies 001 (ICASSP (3), 2007)

Quantized Sparse Approximation with Iterative Thresholding for Audio Coding. - Mehrdad Yaghoobi; Thomas Blumensath; Mike E. Davies 001 (ICASSP (1), 2007)

Monte Carlo Methods for Adaptive Sparse Approximations of Time-Series. - Thomas Blumensath; Michael E. Davies 001 (IEEE Trans. Signal Process., 2007)

Gradient pursuit for non-linear sparse signal modelling. - Thomas Blumensath; Mike E. Davies 001 (EUSIPCO, 2008)

Regularized dictionary learning for sparse approximation. - Mehrdad Yaghoobi; Thomas Blumensath; Mike E. Davies 001 (EUSIPCO, 2008)

Iterative Hard Thresholding for Compressed Sensing - Thomas Blumensath; Mike E. Davies 001 (CoRR, 2008)

Gradient Pursuits. - Thomas Blumensath; Michael E. Davies 001 (IEEE Trans. Signal Process., 2008)

A simple, efficient and near optimal algorithm for compressed sensing. - Thomas Blumensath; Mike E. Davies 001 (ICASSP, 2009)

Parsimonious dictionary learning. - Mehrdad Yaghoobi; Thomas Blumensath; Michael E. Davies 001 (ICASSP, 2009)

Sampling Theorems for Signals From the Union of Finite-Dimensional Linear Subspaces. - Thomas Blumensath; Michael E. Davies 001 (IEEE Trans. Inf. Theory, 2009)

Stagewise weak gradient pursuits. - Thomas Blumensath; Mike E. Davies 001 (IEEE Trans. Signal Process., 2009)

Dictionary learning for sparse approximations with the majorization method. - Mehrdad Yaghoobi; Thomas Blumensath; Mike E. Davies 001 (IEEE Trans. Signal Process., 2009)

Normalized Iterative Hard Thresholding: Guaranteed Stability and Performance. - Thomas Blumensath; Michael E. Davies 001 (IEEE J. Sel. Top. Signal Process., 2010)

Sparse Representations in Audio and Music: From Coding to Source Separation. - Mark D. Plumbley; Thomas Blumensath; Laurent Daudet; Rémi Gribonval; Mike E. Davies 001 (Proc. IEEE, 2010)

Sampling and Reconstructing Signals From a Union of Linear Subspaces. - Thomas Blumensath (IEEE Trans. Inf. Theory, 2011)

Greedy algorithms for compressed sensing. - Thomas Blumensath; Michael E. Davies 001; Gabriel Rilling (Compressed Sensing, 2012)

Resting-State FMRI Single Subject Cortical Parcellation Based on Region Growing. - Thomas Blumensath; Timothy Edward John Behrens; Stephen M. Smith 001 (MICCAI (2), 2012)

Compressed Sensing with Nonlinear Observations and Related Nonlinear Optimisation Problems - Thomas Blumensath (CoRR, 2012)

Accelerated iterative hard thresholding. - Thomas Blumensath (Signal Process., 2012)

Spatially constrained hierarchical parcellation of the brain with resting-state fMRI. - Thomas Blumensath; Saâd Jbabdi; Matthew F. Glasser; David C. Van Essen; Kâmil Ugurbil; Timothy Edward John Behrens; Stephen M. Smith 001 (NeuroImage, 2013)

Compressed Sensing With Nonlinear Observations and Related Nonlinear Optimization Problems. - Thomas Blumensath (IEEE Trans. Inf. Theory, 2013)

A spatially constrained low-rank matrix factorization for the functional parcellation of the brain. - Alexis Benichoux; Thomas Blumensath (EUSIPCO, 2014)

Sparse matrix decompositions for clustering. - Thomas Blumensath (EUSIPCO, 2014)

Monte Carlo methods for compressed sensing. - Thomas Blumensath (ICASSP, 2014)

Directional Clustering Through Matrix Factorization. - Thomas Blumensath (IEEE Trans. Neural Networks Learn. Syst., 2016)

Distributed Computation of Linear Inverse Problems with Application to Computed Tomography. - Yushan Gao; Thomas Blumensath (CoRR, 2017)

BSGD-TV: A parallel algorithm solving total variation constrained image reconstruction problems. - Yushan Gao; Thomas Blumensath (CoRR, 2018)

Backprojection inverse filtration for laminographic reconstruction. - Thomas Blumensath (IET Image Process., 2018)

A Joint Row and Column Action Method for Cone-Beam Computed Tomography. - Yushan Gao; Thomas Blumensath (IEEE Trans. Computational Imaging, 2018)

Block stochastic gradient descent for large-scale tomographic reconstruction in a parallel network. - Yushan Gao; Ander Biguri; Thomas Blumensath (CoRR, 2019)

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox. - Ander Biguri; Reuben Lindroos; Robert Bryll; Hossein Towsyfyan; Hans Deyhle; Richard P. Boardman; Mark Mavrogordato; Manjit Dosanjh; Steven Hancock; Thomas Blumensath (CoRR, 2019)

Numerically robust tetrahedron-based tomographic forward and backward projectors on parallel architectures. - Ander Biguri; Hossein Towsyfyan; Richard P. Boardman; Thomas Blumensath (CoRR, 2019)

Arbitrarily large tomography with iterative algorithms on multiple GPUs using the TIGRE toolbox. - Ander Biguri; Reuben Lindroos; Robert Bryll; Hossein Towsyfyan; Hans Deyhle; Ibrahim El Khalil Harrane; Richard P. Boardman; Mark Mavrogordato; Manjit Dosanjh; Steven Hancock; Thomas Blumensath (J. Parallel Distributed Comput., 2020)

Scalable FBP decomposition for cone-beam CT reconstruction. - Peng Chen 035; Mohamed Wahib; Xiao Wang 004; Takahiro Hirofuchi; Hirotaka Ogawa; Ander Biguri; Richard P. Boardman; Thomas Blumensath; Satoshi Matsuoka (SC, 2021)

Quantity Over Quality? Investigating the Effects of Volume and Strength of Training Data in Marine Bioacoustics. - Andrea Napoli; Paul R. White; Thomas Blumensath (DCASE, 2022)

Sinogram Enhancement with Generative Adversarial Networks using Shape Priors. - Emilien Valat; Katayoun Farrahi; Thomas Blumensath (CoRR, 2022)

Data-Driven Interpolation for Super-Scarce X-Ray Computed Tomography. - Emilien Valat; Katayoun Farrahi; Thomas Blumensath (CoRR, 2022)

Stereo X-ray Tomography. - Zhenduo Shang; Thomas Blumensath (CoRR, 2023)

Invertible Low-Dimensional Modelling of X-ray Absorption Spectra for Potential Applications in Spectral X-ray Imaging. - Raziye Kubra Kumrular; Thomas Blumensath (CoRR, 2023)

TIGRE v3: Efficient and easy to use iterative computed tomographic reconstruction toolbox for real datasets. - Ander Biguri; Tomoyuki Sadakane; Reuben Lindroos; Yi Liu; Malena Sabaté Landman; Yi Du; Manasavee Lohvithee; Stefanie Kaser; Sepideh Hatamikia; Robert Bryll; Emilien Valat; Sarinrat Wonglee; et al. (CoRR, 2024)