Anisotropic nonlinear PDE models and dynamical systems in biology
Geometric numerical integration for optimisation
Variational Multi-Task Models for Image Analysis: Applications to Magnetic Resonance Imaging
Anisotropic variational models and PDEs for inverse imaging problems
Mathematical Imaging Tools in Cancer Research - From Mitosis Analysis to Sparse Regularisation
Shell-Based Geometric Image and Video Inpainting
Mapping individual trees from airborne multi-sensor imagery
New PDE models for imaging problems and applications
Novel higher order regularisation methods for image reconstruction
First-order gradient regularisation methods for image restoration: reconstruction of tomographic images with thin structures and denoising piecewise affine images
Structure-preserving machine learning for inverse problems
Mathematical Challenges in Electron Microscopy
Machine Learning in Inverse Problems - Learning Regularisation Functionals and Operator Corrections
Minimal Labels, Maximum Gain. Image Classification with Graph-Based Semi-Supervised Learning
Machine Learning for COVID-19 Diagnosis and Prognostication: Lessons for Amplifying the Signal While Reducing the Noise.
Neural Network Training and Inversion with a Bregman Learning Framework
Deep Learning Approaches for PDE-based Image Analysis and Beyond: From the Total Variation Flow to Medieval Paper Analysis
Cross-Modality Profiling of High-Content Microscopy Images with Deep Learning
