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Currently displaying 21 - 40 of 314 publications

TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations

Z Shen, Y Cheng, RH Chan, P Liò, C-B Schönlieb, AI Aviles-Rivero

(2023)

(link to publication)

Contrastive Registration for Unsupervised Medical Image Segmentation.

L Liu, AI Aviles-Rivero, C-B Schonlieb

– IEEE Trans Neural Netw Learn Syst

(2023)

PP,

(doi: 10.1109/tnnls.2023.3332003)

Traffic Video Object Detection using Motion Prior

L Liu, Y Cheng, D Chen, J He, P Liò, C-B Schönlieb, AI Aviles-Rivero

(2023)

(link to publication)

Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks

M Eliasof, D Murari, F Sherry, C-B Schönlieb

(2023)

(link to publication)

Multi-Modal Learning for Predicting the Genotype of Glioma

Y Wei, X Chen, L Zhu, L Zhang, C-B Schonlieb, S Price, C Li

– IEEE Trans Med Imaging

(2023)

42,

3167

(doi: 10.1109/TMI.2023.3244038)

Recent Methodological Advances in Federated Learning for Healthcare

F Zhang, D Kreuter, Y Chen, S Dittmer, S Tull, T Shadbahr, B Collaboration, J Preller, JHF Rudd, JAD Aston, C-B Schönlieb, N Gleadall, M Roberts

(2023)

(doi: 10.48550/arxiv.2310.02874)

(link to publication)

Adaptive mixed FEM combined with the method of characteristics for stationary convection–diffusion–reaction problems

MC Antony Oliver, M González

– Finite Elements in Analysis and Design

(2023)

227,

104045

(doi: 10.1016/j.finel.2023.104045)

Elliptic PDE learning is provably data-efficient

N Boullé, D Halikias, A Townsend

– Proceedings of the National Academy of Sciences

(2023)

120,

e2303904120

(doi: 10.1073/pnas.2303904120)

The impact of imputation quality on machine learning classifiers for datasets with missing values.

T Shadbahr, M Roberts, J Stanczuk, J Gilbey, P Teare, S Dittmer, M Thorpe, RV Torné, E Sala, P Lió, M Patel, J Preller, AIX-COVNET Collaboration, JHF Rudd, T Mirtti, AS Rannikko, JAD Aston, J Tang, C-B Schönlieb

– Communications Medicine

(2023)

139

(doi: 10.1038/s43856-023-00356-z)

Deep Learning Approaches for PDE-based Image Analysis and Beyond: From the Total Variation Flow to Medieval Paper Analysis

T Großmann

(2023)

(doi: 10.17863/CAM.106705)

Extracting chain lines and laid lines from digital images of medieval paper using spectral total variation decomposition

T Großmann, C-B Schönlieb, O Da Rold

– Herit Sci

(2023)

11,

180

(doi: 10.1186/s40494-023-01013-3)

Riemannian geometry for efficient analysis of protein dynamics data

W Diepeveen, C Esteve-Yagüe, J Lellmann, O Öktem, C-B Schönlieb

(2023)

(link to publication)

Regularizing Orientation Estimation in Cryogenic Electron Microscopy Three-Dimensional Map Refinement through Measure-Based Lifting over Riemannian Manifolds

W Diepeveen, J Lellmann, O Oktem, CB Schonlieb

– SIAM Journal on Imaging Sciences

(2023)

16,

1440

(doi: 10.1137/22m1520773)

Common methodological pitfalls in ICI pneumonitis risk prediction studies.

YK Chen, S Welsh, AM Pillay, B Tannenwald, K Bliznashki, E Hutchison, JAD Aston, C-B Schönlieb, JHF Rudd, J Jones, M Roberts

– Frontiers in immunology

(2023)

14,

1228812

(doi: 10.3389/fimmu.2023.1228812)

Mathematics of biomedical imaging today-a perspective

MM Betcke, CB Schönlieb

– Progress in Biomedical Engineering

(2023)

043002

(doi: 10.1088/2516-1091/acd973)

Shortcut Learning: Reduced But Not Resolved.

IA Selby, M Roberts, A Breger, JHF Rudd, JR Weir-McCall

– Radiology

(2023)

308,

e230379

(doi: 10.1148/radiol.230379)

Reinterpreting survival analysis in the universal approximator age

S Dittmer, M Roberts, J Preller, AIX COVNET, JHF Rudd, JAD Aston, C-B Schönlieb

(2023)

(doi: 10.48550/arxiv.2307.13579)

(link to publication)

Stain normalization gives greater generalizability than stain jittering in neural network training for the classification of coeliac disease in duodenal biopsy whole slide images.

BA Schreiber, J Denholm, JD Gilbey, C-B Schönlieb, EJ Soilleux

– Journal of Pathology Informatics

(2023)

14,

100324

(doi: 10.1016/j.jpi.2023.100324)