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Seminars |
Sparse Coding with Projected Gradient Descent for Inverse Problems 23 Oct 2018
I will present a novel method for sparse coding for nonlinear inverse problem. It relies on a specific formulation of the optimisation problem allowing the use of the projected gradient descent (PGD) method. The main advantage of PGD over the conventional ADMM-based approach is that the costly step of inverting the forward model is avoided. Instead, we only require the computation of the gradient of the data fidelity term (without an explicit inversion of the forward model). We will discuss of the projection on the set of constraints as well as the convergence of the algorithm. Finally, I will present some preliminary results.
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
Sparsity-based techniques for diffraction tomography27 Feb 2018
Structured Illumination and the Analysis of Single Molecules in Cells09 Feb 2018
Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems30 Jan 2018
Fast Piecewise-Affine Motion Estimation Without Segmentation19 Dec 2017
Continuous Representations in Bioimage Analysis: a Bridge from Pixels to the Real World12 Dec 2017
Steer&Detect on Images 14 Nov 2017
Fundamental computational barriers in inverse problems and the mathematics of information27 Oct 2017
Variational use of B-splines and Kernel Based Functions27 Oct 2017
Deep learning based data manifold projection - a new regularization for inverse problems17 Oct 2017
GlobalBioIm Lib - v2: new tools, more flexibility, and improved composition rules.03 Oct 2017
Fractional Integral transforms and Time-Frequency Representations02 Jun 2017
First steps toward fast PET reconstruction30 May 2017
Lipid membranes and surface reconstruction - a biologically inspired method for 3D segmentation16 May 2017
Optical Diffraction Tomography: Principles and Algorithms09 May 2017