skip to content
 

Seminars (VMVW02)

Videos and presentation materials from other INI events are also available.

Search seminar archive

Event When Speaker Title Presentation Material
VMVW02 30th October 2017
09:50 to 10:40
James Nagy Spectral Computed Tomography
VMVW02 30th October 2017
11:10 to 12:00
Eldad Haber tba
VMVW02 30th October 2017
12:00 to 12:50
Christoph Brune Cancer ID - From Spectral Segmentation to Deep Learning
VMVW02 30th October 2017
14:00 to 14:50
Lars Ruthotto PDE-based Algorithms for Convolution Neural Network
VMVW02 30th October 2017
14:50 to 15:40
Gitta Kutyniok Optimal Approximation with Sparsely Connected Deep Neural Networks
VMVW02 30th October 2017
15:40 to 16:00
Eva-Maria Brinkmann Enhancing fMRI Reconstruction by Means of the ICBTV-Regularisation Combined with Suitable Subsampling Strategies and Temporal Smoothing
VMVW02 30th October 2017
16:30 to 17:20
Joan Bruna Geometry and Topology of Neural Network Optimization
VMVW02 30th October 2017
17:20 to 18:10
Justin Romberg Structured solutions to nonlinear systems of equations
VMVW02 31st October 2017
09:00 to 09:50
Stacey Levine Denoising Geometric Image Features
VMVW02 31st October 2017
09:50 to 10:40
Ozan Öktem Task Oriented Reconstruction using Deep Learning
VMVW02 31st October 2017
11:10 to 12:00
Lior Horesh Accelerated Free-Form Model Discovery of Interpretable Models using Small Data
VMVW02 31st October 2017
12:00 to 12:50
Martin Benning Nonlinear Eigenanalysis of sparsity-promoting regularisation operators
VMVW02 31st October 2017
14:00 to 14:50
Alfred Hero The tensor graphical lasso (Teralasso)
VMVW02 31st October 2017
14:50 to 15:40
Francis Bach Breaking the Curse of Dimensionality with Convex Neural Networks
VMVW02 31st October 2017
15:40 to 16:00
Jonas Adler Learned forward operators: Variational regularization for black-box models
VMVW02 31st October 2017
16:30 to 17:20
Julianne Chung Advancements in Hybrid Iterative Methods for Inverse Problems
VMVW02 31st October 2017
17:20 to 18:10
Andreas Hauptmann Learning iterative reconstruction for high resolution photoacoustic tomography
VMVW02 1st November 2017
09:00 to 09:50
Mila Nikolova Below the Surface of the Non-Local Bayesian Image Denoising Method
VMVW02 1st November 2017
09:50 to 10:40
Xavier Bresson Convolutional Neural Networks on Graphs
VMVW02 1st November 2017
11:10 to 12:00
Julie Delon High-Dimensional Mixture Models For Unsupervised Image Denoising (HDMI)
VMVW02 1st November 2017
12:00 to 12:50
Bangti Jin Sparse Recovery by l0 Penalty
VMVW02 2nd November 2017
09:00 to 09:50
Silvia Gazzola Krylov Subspace Methods for Sparse Reconstruction
VMVW02 2nd November 2017
09:50 to 10:40
Pierre Weiss Generating sampling patterns in MRI
VMVW02 2nd November 2017
11:10 to 12:00
Anders Hansen On computational barriers in data science and the paradoxes of deep learning
VMVW02 2nd November 2017
12:00 to 12:50
Josiane Zerubia Stochastic geometry for automatic object detection and tracking
VMVW02 2nd November 2017
14:00 to 14:50
Mario Figueiredo Divide and Conquer: Patch-based Image Denoising, Restoration, and Beyond
VMVW02 2nd November 2017
14:50 to 15:40
Marcelo Pereyra Bayesian analysis and computation for convex inverse problems: theory, methods, and algorithms
VMVW02 2nd November 2017
15:40 to 16:00
Pol del Aguila Pla Cell detection by functional inverse diffusion and group sparsity
VMVW02 2nd November 2017
16:30 to 17:20
Claire Boyer Structured compressed sensing and recent theoretical advances on optimal sampling
VMVW02 2nd November 2017
17:20 to 18:10
Tuomo Valkonen What do regularisers do?
VMVW02 3rd November 2017
09:00 to 09:50
Irene Waldspurger Alternating projections for phase retrieval with random sensing vectors
VMVW02 3rd November 2017
09:50 to 10:40
Martin Holler Analysis and applications of structural-prior-based total variation regularization for inverse problems
VMVW02 3rd November 2017
11:10 to 12:00
Raymond Chan A Nuclear-norm Model for Multi-Frame Super-resolution Reconstruction
VMVW02 3rd November 2017
12:00 to 12:50
Mihaela Pricop-jeckstadt From spatial learning to machine learning: an unsupervised approach with applications to behavioral science
VMVW02 3rd November 2017
14:00 to 14:50
Robert Plemmons Sparse Recovery Algorithms for 3D Imaging using Point Spread Function Engineering
VMVW02 3rd November 2017
14:50 to 15:40
Jeff Calder The weighted p-Laplacian and semi-supervised learning
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons