# Variational methods and effective algorithms for imaging and vision

Created: | 2017-08-31 09:05 |
---|---|

Institution: | Isaac Newton Institute for Mathematical Sciences |

Description: | Programme
29th August 2017 to 20th December 2017 Organisers: Ke Chen (University of Liverpool), Andrew Fitzgibbon (Microsoft Research), Michael Hintermüller (Humboldt-Universität zu Berlin), Carola-Bibiane Schönlieb (University of Cambridge), and Xue-Cheng Tai (Hong Kong Baptist University) Scientific committee: Andrea Bertozzi (UCLA, USA); Andrew Blake (Alan Turing Institute, UK); Tony Chan (HKUST, CHINA); Bill Freeman (MIT, USA); Ron Kimmel (Technion, Israel); David Mumford (Brown, USA); Mila Nikolova (E.N.S. Cachan, France); Stanley Osher (UCLA, USA); Joachim Weickert (Saarland, Germany). Programme Theme In our modern society, mathematical imaging, image processing and computer vision have become fundamental for gaining information on various aspects in medicine, the sciences, and technology, in the public and private sector equally. The rapid development of new imaging hardware, the advance in medical imaging, the advent of multi-sensor data fusion and multimodal imaging, as well as the advances in computer vision have sparked numerous research endeavours leading to highly sophisticated and rigorous mathematical models and theories. An evidence of this trend can be found in the still increasing use of variational models, shapes and flows, differential geometry, optimization theory, numerical analysis, statistical / Bayesian graphical models, and machine learning. Still, the ever growing challenges in applications and technology constantly generate new demands that cannot be met by existing mathematical concepts and algorithms. As a consequence, new mathematical models have to be found, analyzed and realized in practice. This four-month programme will foster exchange between different groups of researchers and practitioners, who are involved in mathematical imaging science, and discussions on new horizons in theory, numerical methods and applications of mathematical imaging and vision. |

# Media items

This collection contains 95 media items.

### Media items

#### A convexity based method for approximation and interpolation of sampled functions

Zhang, K( University of Nottingham)

Wednesday 8th November 2017 - 15:30 to 16:30

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 5 Jan 2018

#### A Nuclear-norm Model for Multi-Frame Super-resolution Reconstruction

Chan, R

Friday 3rd November 2017 - 11:10 to 12:00

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 6 Nov 2017

#### Accelerated Free-Form Model Discovery of Interpretable Models using Small Data

Horesh, L

Tuesday 31st October 2017 - 11:10 to 12:00

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Thu 2 Nov 2017

#### Adaptive and Move Making Auxiliary Cuts for Binary Pairwise Energies

Veksler, O

Friday 8th September 2017 - 12:00 to 12:50

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 11 Sep 2017

#### Advancements in Hybrid Iterative Methods for Inverse Problems

Chung, J

Tuesday 31st October 2017 - 16:30 to 17:20

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Thu 2 Nov 2017

#### Alternating projections for phase retrieval with random sensing vectors

Waldspurger,I

Friday 3rd November 2017 - 09:00 to 09:50

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 6 Nov 2017

#### Alternating proximal gradient descent for nonconvex regularised problems with multiconvex coupling terms

Nikolova, M

Friday 8th September 2017 - 09:00 to 09:50

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Thu 14 Sep 2017

#### An interpolating distance between Wasserstein and Fisher-Rao

Vialard, F-X (Université Paris-Dauphine, INRIA Paris - Rocquencourt)

Friday 15th December 2017 - 11:30 to 12:30

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 15 Dec 2017

#### Analysis and applications of structural-prior-based total variation regularization for inverse problems

Holler, M

Friday 3rd November 2017 - 09:50 to 10:40

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 6 Nov 2017

#### Augmented Lagrangian method for image segmentation using elastica energy that prefers convex contours

Tai, X

Thursday 7th September 2017 - 09:00 to 09:50

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 8 Sep 2017

#### Automating stochastic gradient methods with adaptive batch sizes

Goldstein, T

Wednesday 6th September 2017 - 09:50 to 10:40

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Thu 7 Sep 2017

#### Bayesian analysis and computation for convex inverse problems: theory, methods, and algorithms

Pereyra, M

Thursday 2nd November 2017 - 14:50 to 15:40

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 3 Nov 2017

#### Below the Surface of the Non-Local Bayesian Image Denoising Method

Nikolova, M

Wednesday 1st November 2017 - 09:00 to 09:50

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Thu 2 Nov 2017

#### Breaking the Curse of Dimensionality with Convex Neural Networks

Bach, F

Tuesday 31st October 2017 - 14:50 to 15:40

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 3 Nov 2017

#### Cancer ID - From Spectral Segmentation to Deep Learning

Brune, C

Monday 30th October 2017 - 12:00 to 12:50

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Tue 31 Oct 2017

#### Capturing 3D models of deformable objects from monocular sequences

Agapito, L (University College London)

Tuesday 12th December 2017 - 11:30 to 12:30

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 15 Dec 2017

#### Cell detection by functional inverse diffusion and group sparsity

del Aguila Pla, P

Thursday 2nd November 2017 - 15:40 to 16:00

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 6 Nov 2017

#### Compact Rank Models and Optimization

Olsson, C (Lund University, Chalmers University of Technology)

Tuesday 12th December 2017 - 16:00 to 17:00

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 15 Dec 2017

#### Compensated convexity, multiscale medial axis maps, and sharp regularity of the squared distance function

Crooks, E (Swansea University)

Friday 15th December 2017 - 10:00 to 11:00

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 15 Dec 2017

#### Convex regularization of discrete-valued inverse problems

Clason, C

Thursday 7th September 2017 - 16:10 to 17:00

**Collection**:
Variational methods and effective algorithms for imaging and vision

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 8 Sep 2017