#303,055

Most Influential Person

Austrian mathematician

By AI Staff

Carola-Bibiane Schönlieb currently holds the title of Professor in Applied and Computational Analysis in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge. She is also a Turing Fellow of the Alan Turing Institute, Director of the EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging, and Director of the Cantab Capital Institute for the Mathematics of Information. Schönlieb is Austrian, and completed her MA in mathematics at the University of Salzburg in 2004. She earned her PhD in 2009 at Cambridge, and completed postdoctoral studies at the University of Göttingen.

Schönlieb ’s work is primarily focused in image processing and partial differential equations. In particular, Schönlieb has made significant progress in applying partial differential equations in image analysis and inverse imaging problems, and problems in 3D and 4D imaging. As an interdisciplinarian, Schönlieb’s work has significant implications for a wide range of fields that employ video imaging, including chemical engineering, biomedical sciences, and art.

In addition to her research, Schönlieb is active in encouraging and advocating for women in mathematics, and is active with the European Women in Mathematics Association, and the Committee for Women in Mathematics.

For her work, Schönlieb has received awards and honors including the Whitehead Prize of the London Mathematical Society, the Philip Leverhulme Prize, and was named the Mary Cartwright Lecturer of the London Mathematical Society.

**Featured in Top Influential Mathematicians Today**

According to Wikipedia, Carola-Bibiane Schönlieb is an Austrian mathematician who works in image processing and partial differential equations. She is a Fellow of Jesus College, Cambridge and a Professor in Applied and Computational Analysis in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge. She is the author of the book Partial Differential Equation Methods for Image Inpainting , on methods for using the solutions to partial differential equations to fill in gaps in digital images.

- A Combined First and Second Order Variational Approach for Image Reconstruction (217)
- Learning to Diversify Deep Belief Networks for Hyperspectral Image Classification (172)
- Cahn--Hilliard Inpainting and a Generalization for Grayvalue Images (161)
- Solving inverse problems using data-driven models (142)
- Unconditionally stable schemes for higher order inpainting (108)
- Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications (97)
- Adversarial Regularizers in Inverse Problems (84)
- Imaging with Kantorovich-Rubinstein Discrepancy (73)
- Combined First and Second Order Total Variation Inpainting using Split Bregman (73)
- Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization (71)
- Partial Differential Equation Methods for Image Inpainting (70)
- Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models (70)
- Oriented diffusion filtering for enhancing low-quality fingerprint images (66)
- Variational Depth From Focus Reconstruction (60)
- Subspace Correction Methods for Total Variation and 1-Minimization (59)
- On the Connection Between Adversarial Robustness and Saliency Map Interpretability (58)
- Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans (54)
- Regularized Regression and Density Estimation based on Optimal Transport (53)
- Bilevel approaches for learning of variational imaging models (51)
- A convergent overlapping domain decomposition method for total variation minimization (50)
- Phase reconstruction from velocity-encoded MRI measurements--a survey of sparsity-promoting variational approaches. (48)
- A generalized model for optimal transport of images including dissipation and density modulation (45)
- Total Variation Regularisation in Measurement and Image space for PET reconstruction (45)
- A Variational Model for Joint Motion Estimation and Image Reconstruction (43)
- Individual Tree Species Classification From Airborne Multisensor Imagery Using Robust PCA (40)
- The structure of optimal parameters for image restoration problems (38)
- Liquid phase blending of metal-organic frameworks (34)
- Deep learning as optimal control problems: models and numerical methods (33)
- Preconditioned ADMM with Nonlinear Operator Constraint (31)
- Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation (27)
- Graph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images (26)
- Infimal Convolution of Data Discrepancies for Mixed Noise Removal (25)
- Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems (24)
- Nonparametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Wooded Landscapes (22)
- Local Convergence Properties of SAGA/Prox-SVRG and Acceleration (21)
- GraphXNET-Chest X-Ray Classification Under Extreme Minimal Supervision (21)
- Bregmanized Domain Decomposition for Image Restoration (20)
- Learning optimal spatially-dependent regularization parameters in total variation image restoration (19)
- Accurate Measurement of Tropical Forest Canopy Heights and Aboveground Carbon Using Structure From Motion (19)
- Discrete gradient methods for solving variational image regularisation models (18)
- Infimal Convolution Regularisation Functionals of BV and $$\varvec{\mathrm {L}}^{\varvec{p}}$$Lp Spaces (18)
- Choose Your Path Wisely: Gradient Descent in a Bregman Distance Framework (17)
- Nonlinear Spectral Image Fusion (17)
- Image Inpainting Using a Fourth-Order Total Variation Flow (16)
- Directional sinogram inpainting for limited angle tomography (16)
- Inverse Scale Space Decomposition (16)
- Learning the Sampling Pattern for MRI (16)
- Task adapted reconstruction for inverse problems (16)
- Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification (15)
- Enhancing joint reconstruction and segmentation with non-convex Bregman iteration (14)
- Wavelet Decomposition Method for L2//TV-Image Deblurring (14)
- Faster PET Reconstruction with Non-Smooth Priors by Randomization and Preconditioning (13)
- Domain decomposition methods for compressed sensing (13)
- Dynamic Sampling Schemes for Optimal Noise Learning Under Multiple Nonsmooth Constraints (13)
- ADI splitting schemes for a fourth-order nonlinear partial differential equation from image processing (13)
- Variational Image Regularization with Euler's Elastica Using a Discrete Gradient Scheme (12)
- Pattern formation of a nonlocal, anisotropic interaction model (12)
- RainFlow: Optical Flow Under Rain Streaks and Rain Veiling Effect (12)
- Image denoising: learning noise distribution via PDE-constrained optimization (12)
- Infimal Convolution Regularisation Functionals of BV and Lp Spaces. The Case p=∞ (11)
- Applying physical science techniques and CERN technology to an unsolved problem in radiation treatment for cancer: the multidisciplinary 'VoxTox' research programme. (10)
- TOTAL VARIATION MINIMIZATION WITH AN H − 1 CONSTRAINT (10)
- Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review (10)
- Analysis and Application of a Nonlocal Hessian (10)
- 3D Segmentation of Trees Through a Flexible Multiclass Graph Cut Algorithm (10)
- Anisotropic Third-Order Regularization for Sparse Digital Elevation Models (9)
- Unveiling the invisible: mathematical methods for restoring and interpreting illuminated manuscripts (9)
- Learned convex regularizers for inverse problems. (9)
- Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction (9)
- Mathematical imaging methods for mitosis analysis in live-cell phase contrast microscopy (9)
- The Willmore functional and instabilities in the Cahn-Hilliard equation (9)
- A graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery (9)
- Improving "Fast Iterative Shrinkage-Thresholding Algorithm": Faster, Smarter and Greedier (9)
- A Primal-Dual Approach for a Total Variation Wasserstein Flow (9)
- Faster PET reconstruction with a stochastic primal-dual hybrid gradient method (8)
- Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian (8)
- On Learned Operator Correction in Inverse Problems (8)
- Linkage between Piecewise Constant Mumford-Shah model and ROF model and its virtue in image segmentation (8)
- An anisotropic interaction model for simulating fingerprints (8)
- A DBN-crf for spectral-spatial classification of hyperspectral data (7)
- A multi-task U-net for segmentation with lazy labels (7)
- Infimal convolution regularisation functionals of BV and $\mathrm{L}^{p}$ spaces. Part I: The finite $p$ case (7)
- Decoding the Interdependence of Multiparametric Magnetic Resonance Imaging to Reveal Patient Subgroups Correlated with Survivals12 (7)
- Linkage Between Piecewise Constant Mumford-Shah Model and Rudin-Osher-Fatemi Model and Its Virtue in Image Segmentation (7)
- A geometric integration approach to nonsmooth, nonconvex optimisation (7)
- Learning Filter Functions in Regularisers by Minimising Quotients (7)
- Gradient descent in a generalised Bregman distance framework (7)
- Total Variation Meets Topological Persistence: A First Encounter (7)
- Structure preserving deep learning (7)
- Artificial intelligence in clinical imaging: a health system approach. (7)
- Multi-tasking to Correct: Motion-Compensated MRI via Joint Reconstruction and Registration (6)
- A DIVERSIFIED DEEP BELIEF NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION (6)
- Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance) (6)
- Stability Analysis of Line Patterns of an Anisotropic Interaction Model (6)
- Higher-Order Total Directional Variation. Part I: Imaging Applications (6)
- A high-contrast fourth-order PDE from imaging: numerical solution by ADI splitting (6)
- Two Cycle Learning: Clustering Based Regularisation for Deep Semi-Supervised Classification (5)
- Template-Based Image Reconstruction from Sparse Tomographic Data (5)
- Accuracy of manual and automated rectal contours using helical tomotherapy image guidance scans during prostate radiotherapy. (5)
- Peekaboo-Where are the Objects? Structure Adjusting Superpixels (5)
- Explorations on anisotropic regularisation of dynamic inverse problems by bilevel optimisation (5)
- Learning to Segment Microscopy Images with Lazy Labels (5)
- Faster FISTA (5)
- Random simulations for generative art construction – some examples (5)
- iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems (5)
- SPRING: A fast stochastic proximal alternating method for non-smooth non-convex optimization. (5)
- Mirror, Mirror, on the Wall, Who’s Got the Clearest Image of Them All?—A Tailored Approach to Single Image Reflection Removal (5)
- Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC) (5)
- GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays (4)
- Learning parametrised regularisation functions via quotient minimisation (4)
- Entropic Comparison of Atomic-Resolution Electron Tomography of Crystals and Amorphous Materials. (4)
- A multi‐contrast MRI approach to thalamus segmentation (4)
- Individual tree species classification from airborne multi-sensor imagery (4)
- Mapping individual trees from airborne multi-sensor imagery (4)
- iUNets: Fully invertible U-Nets with Learnable Up- and Downsampling (4)
- Anisotropic osmosis filtering for shadow removal in images. (4)
- Variational regularisation for inverse problems with imperfect forward operators and general noise models (4)
- The Use of Fractal Dimension in Arts Analysis (3)
- Introduction: Big data and partial differential equations† (3)
- THE BEST CONSTANT AND EXTREMALS OF THE SOBOLEV EMBEDDINGS IN DOMAINS WITH HOLES: THE L∞ CASE (3)
- Learning parametrised regularisation functions via quotient minimisation: Learning parametrised regularisation functions via quotient minimisation (3)
- Guidefill: GPU Accelerated, Artist Guided Geometric Inpainting for 3D Conversion of Film (3)
- Learning optimal orders of the underlying Euclidean norm in total variation image denoising (3)
- Accelerating Variance-Reduced Stochastic Gradient Methods. (3)
- Rethinking Medical Image Reconstruction via Shape Prior, Going Deeper and Faster: Deep Joint Indirect Registration and Reconstruction (3)
- Variational Osmosis for Non-Linear Image Fusion (3)
- Tomographic Reconstruction with Spatially Varying Parameter Selection (3)
- Nonlocal higher order evolution equations (3)
- N A ] 3 0 O ct 2 01 5 Infimal Convolution Regularisation Functionals of BV and L p Spaces . The Case p = ∞ (3)
- A total variation based regularizer promoting piecewise-Lipschitz reconstructions (3)
- GraphX $$^\mathbf{\small NET } -$$ -Chest X-Ray Classification Under Extreme Minimal Supervision (3)
- Optical flow analysis reveals that Kinesin-mediated advection impacts on the orientation of microtubules in the Drosophila oocyte (3)
- A Variational Model Dedicated to Joint Segmentation, Registration and Atlas Generation for Shape Analysis (3)
- Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination (3)
- Higher-Order Total Directional Variation. Part II: Analysis (3)
- A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation (3)
- Machine Learning for COVID-19 Diagnosis and Prognostication: Lessons for Amplifying the Signal While Reducing the Noise (3)
- Phase diagrams of liquid-phase mixing in multi-component metal-organic framework glasses constructed by quantitative elemental nano-tomography (3)
- TGV sinogram inpainting for limited angle tomography (3)
- SLIC-UAV: A Method for monitoring recovery in tropical restoration projects through identification of signature species using UAVs (2)
- Semi-Supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification (2)
- Chaos, Noise, Randomness and Coincidence as Constitutional for Generative Art (2)
- Higher-Order Total Directional Variation: Analysis (2)
- The best constant and extremals of the Sobolev embeddings in domains with holes: The $L^\infty$ case (2)
- Joint phase reconstruction and magnitude segmentation from velocity-encoded MRI data (2)
- Supporting Material for Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation (2)
- Total Directional Variation for Video Denoising (2)
- A generalization of Cahn-Hilliard inpainting for grayvalue images (2)
- Optical flow analysis reveals that Kinesin-mediated advection impacts the orientation of microtubules in the Drosophila oocyte (2)
- ALTERNATING REGULARISATION IN MEASUREMENT-AND IMAGE SPACE FOR PET RECONSTRUCTION (2)
- GANReDL: Medical Image Enhancement Using a Generative Adversarial Network with Real-Order Derivative Induced Loss Functions (2)
- Binary Based Fresco Restoration (2)
- Bregman Itoh–Abe Methods for Sparse Optimisation (2)
- Adversarially learned iterative reconstruction for imaging inverse problems (2)
- On Learned Operator Correction (2)
- Equilibria of an anisotropic nonlocal interaction equation: Analysis and numerics (2)
- Variational Multi-Task MRI Reconstruction: Joint Reconstruction, Registration and Super-Resolution (2)
- A hybrid analytical–numerical algorithm for determining the neuronal current via electroencephalography (1)
- Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation (1)
- Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events (1)
- ANALYSIS AND APPLICATION OF A NON-LOCAL HESSIAN (1)
- Ground Truth Free Denoising by Optimal Transport (1)
- AN OPTIMIZATION PROBLEM RELATED TO THE BEST SOBOLEV TRACE CONSTANT IN THIN DOMAINS (1)
- Joint Motion Estimation and Source Identification using Convective Regularisation with an Application to the Analysis of Laser Nanoablations (1)
- Numerical analysis of shell-based geometric image inpainting algorithms and their semi-implicit extension (1)
- Analysis of Artifacts in Shell-Based Image Inpainting: Why They Occur and How to Eliminate Them (1)
- SUBSPACE CORRECTION METHODS FOR TOTAL VARIATION AND l 1 − MINIMIZATION MASSIMO (1)
- Research data supporting "Deep learning as optimal control problems" (1)
- Infimal Convolution Regularisation Functionals of BV and [Formula: see text] Spaces: Part I: The Finite [Formula: see text] Case. (1)
- PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds (1)
- Multi-Task Deep Learning for Image Segmentation Using Recursive Approximation Tasks (1)
- Tree-centric mapping of forest carbon density from airborne LiDAR and hyperspectral data (1)
- Gradient flows: from theory to application (1)
- Dynamic Spectral Residual Superpixels (1)
- Anisotropic Diffusion Filtering with Apriori Estimated Orientation Field for Enhancing Low-quality Fingerprint Images (1)
- A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation (1)
- 105 Machine learning and carotid artery CT radiomics identify significant differences between culprit and non-culprit lesions in patients with stroke and transient ischaemic attack (1)
- Unsupervised Image Restoration Using Partially Linear Denoisers (1)
- Scanning electron diffraction tomography of strain (1)
- On Biased Stochastic Gradient Estimation (1)
- Higher-Order Total Directional Variation: Imaging Applications (1)
- Deep Reflection Prior (1)
- Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination (1)
- How Differential Equations can Make a Bungee Jumper Jump Without a (0)
- Unveiling the Invisible — Mathematical Approaches for Virtual Image Restoration in the Arts (0)
- Improving a Stochastic Algorithm for Regularized PET Image Reconstruction (0)
- Author Correction: A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images (0)
- Joint Motion Estimation and Source Identification Using Convective Regularisation with an Application to the Analysis of Laser Nanoablations (0)
- Contrast CT classification of asymptomatic and symptomatic carotids in stroke and transient ischaemic attack with deep learning and interpretability (0)
- Art Speaks Maths, Maths Speaks Art (0)
- Equivariant neural networks for inverse problems (0)
- Line Segmentation and Analysis with Special Interest to the Duct of a Line (0)
- A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images. (0)
- A Linear Transportation $\mathrm{L}^p$ Distance for Pattern Recognition (0)
- 3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning (0)
- Deeply Learned Spectral Total Variation Decomposition (0)
- P14.129 Predicting glioblastoma invasion using multiparametric MRI and a bi-level machine learning approach (0)
- Preface for Inverse Problems special issue on learning and inverse problems (0)
- Identifying Multiple Invasive Intratumor Habitats in Glioblastoma Using Multi-Parametric Magnetic Resonance Imaging and Copula Transform (0)
- Nonlinear Spectral Image Fusion Supplementary Material (0)
- Radiomics applied to carotid CT angiograms can identify significant differences between culprit and non-culprit lesions in patients with stroke and transient ischaemic attack (0)
- Cahn-Hilliard inpainting and the Willmore functional (0)
- Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients (0)
- Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations (0)
- Inpainting Mechanisms of Transport and Diffusion (0)
- Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization (0)
- CAFLOW: Conditional Autoregressive Flows (0)
- Non-parametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Forests (0)
- Deep Learning and Inverse Problems (0)
- Advances in Artificial Intelligence to Reduce Polyp Miss Rates during Colonoscopy (0)
- Research data supporting 'Pattern formation of a nonlocal, anisotropic interaction model' (0)
- Learning Regularisers for Imaging Inverse Problems: From Quotient Minimisation to Adversarial Neural Networks (0)
- Deep learning for inverse imaging problems: some recent approaches (Conference Presentation) (0)
- Unsupervised clustering of Roman pottery profiles from their SSAE representation (0)
- Efficient Global Optimization of Non-differentiable, Symmetric Objectives for Multi Camera Placement (0)
- Second-Order Diffusion Equations for Inpainting (0)
- An end-to-end Optical Character Recognition approach for ultra-low-resolution printed text images (0)
- Liquid phase blending of metal-organic frameworks (vol 9, 2135, 2018) (0)
- End-to-end reconstruction meets data-driven regularization for inverse problems (0)
- Efficient Global Optimization of Non-differentiable, Symmetric Objectives for Multi Camera Placement (0)
- A hybrid analytical-numerical algorithm for determining the neuronal current via EEG (0)
- Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy (0)
- Research data supporting the publication "Inverse Scale Space Decomposition". (0)
- TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems (0)
- Mini-Workshop: Deep Learning and Inverse Problems (0)
- Research Data Supporting "Learning Filter Functions in Regularisers by Minimising Quotients" (0)
- Semi-supervised Superpixel-based Multi-Feature Graph Learning for Hyperspectral Image Data (0)
- Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma (0)
- The Principle of Good Continuation (0)
- Overview of Mathematical Inpainting Methods (0)
- Higher-Order PDE Inpainting (0)
- Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding (0)
- Density Estimation and Smoothing based on Regularised Optimal Transport Martin Burger (0)
- Learning optical flow for fast MRI reconstruction (0)
- Mathematics of Information – The Second Industrial Revolution (0)
- Research data supporting 'An Anisotropic Interaction Model for Simulating Fingerprints' (0)
- SUPPLEMENTARY MATERIALS : A Variational Model Dedicated to Joint 1 Segmentation , Registration and Atlas Generation for Shape Analysis ∗ 2 (0)
- Image reconstruction in light-sheet microscopy: spatially varying deconvolution and mixed noise (0)
- Preface for the special issue ‘Variational methods and effective algorithms for imaging and vision’ (0)
- The use of discrete gradient methods for total variation type regularization problems in image processing (0)
- LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification (0)
- HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation (0)
- Mechanisms Underlying Vascular Endothelial Growth Factor Receptor Inhibition–Induced Hypertension (0)
- Symposium: Geometric Models and Applications in Image and Surface Processing (0)
- Research data supporting the publication 'Nonlinear Spectral Image Fusion' (0)
- Bayesian optimization assisted unsupervised learning for efficient intra-tumor partitioning in MRI and survival prediction for glioblastoma patients (0)
- A Linear Transportation Lp Distance for Pattern Recognition (0)
- Aalborg Universitet Liquid phase blending of metal-organic frameworks (0)
- Mathematics of Information (0)
- The Mumford-Shah Image Model for Inpainting (0)
- Publisher Correction: Liquid phase blending of metal-organic frameworks (0)
- Total Variation Regularisation with Spatially Variable Lipschitz Constraints (0)
- Motion Correction Resolved for MRI via Multi-Tasking: A Simultaneous Reconstruction and Registration Approach (0)
- EP-1893: Automatic contouring of soft organs for image-guided prostate radiotherapy (0)
- Contrastive Registration for Unsupervised Medical Image Segmentation (0)
- An anisotropic interactionmodel for simulating fingerprints (0)
- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma (0)
- Image reconstruction in dynamic inverse problems with temporal models (0)
- Inpainting of Ancient Austrian frescoes Wolfgang Baatz (0)

This paper list is powered by the following services:

Carola-Bibiane Schönlieb is affiliated with the following schools:

This website uses cookies to enhance the user experience. Privacy Policy

Want to be an Academic Influence Insider?

Sign up to get the latest news, information, and rankings in our upcoming newsletter.