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Seminars |
Sparse signal reconstruction using variational methods with fractional derivatives10 Sep 2019
Self-similar stochastic processes have many applications in signal processing (image analysis, speech synthesis, road/Ethernet traffic modeling...). These signals of varying sparsity can be reconstructed efficiently using variational methods. Since fractional derivatives are whitening operators for these processes, we formulate a continous inverse problem with gTV regularization and generalized fractional derivatives as regularization operators. We then discretize this problem in the basis of periodic fractional B-splines, and propose an algorithm to solve this discretized problem in an exact way.
Multivariate Haar wavelets and B-splines13 Aug 2019
Deep Learning for Magnetic Resonance Image Reconstruction and Analysis06 Aug 2019
The Interpolation Problem with TV(2) Regularization30 Jul 2019
Duality and Unicity for the gTV problem.23 Jul 2019
An Introduction to Convolutional Neural Networks for Inverse Problems in Imaging09 Jul 2019
Multiple Kernel Regression with Sparsity Constraints18 Jun 2019
Optimal Spline Generators for Derivative Sampling18 Jun 2019
Total variation minimization through Domain Decomposition28 May 2019
Cell detection by functional inverse diffusion and non-negative group sparsity07 May 2019
Can neural networks always be trained? On the boundaries of deep learning06 May 2019
Measure Digital, Reconstruct Analog16 Apr 2019
Deep Learning for Non-Linear Inverse Problems02 Apr 2019
Numerical Investigation of Continuous-Domain Lp-norm Regularization in Generalized Interpolation19 Feb 2019
Inner-Loop-Free ADMM for Cryo-EM15 Jan 2019
Fast PET reconstruction: the home stretch11 Dec 2018
Self-Supervised Deep Active Accelerated MRI27 Nov 2018
Minimum Support Multi-Splines20 Nov 2018
Sparse Coding with Projected Gradient Descent for Inverse Problems 23 Oct 2018
Adversarially-Sandwiched VAEs for Inverse Problems02 Oct 2018
PSF-Extractor: from fluorescent beads measurements to continuous PSF model11 Sep 2018
Analysis of Planar Shapes through Shape Dictionary Learning with an Extension to Splines28 Aug 2018
Complex-order scale-invariant operators and self-similar processes21 Aug 2018
Variational Framework for Continuous Angular Refinement and Reconstruction in Cryo-EM14 Aug 2018
Looking beyond Pixels: Theory, Algorithms and Applications of Continuous Sparse Recovery07 Aug 2018
A L1 representer theorem of vector-valued learning17 Jul 2018
Computational Super-Sectioning for Single-Slice Structured-Illumination Microscopy 19 Jun 2018
Theoretical and Numerical Analysis of Super-Resolution without Grid19 Jun 2018
Fast rotational dictionary learning using steerability 08 May 2018
Hybrid spline dictionaries for continuous-domain inverse problems24 Apr 2018
Fast Multiresolution Reconstruction for Cryo-EM17 Apr 2018
Direct Reconstruction of Clipped Peaks in Bandlimited OFDM Signals13 Mar 2018