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  • Currently displaying 121 - 140 of 1600 publications
Evidence Communication Rules for Policy (ECR-P) critical appraisal tool
E Danopoulos, JAD Aston, A Shah, CR Schneider
– Syst Rev
(2025)
14,
10
(doi: 10.1186/s13643-025-02757-8)
Testing conditional independence under isotonicity
R Hore, JA Soloff, RF Barber, RJ Samworth
(2025)
(link to publication)
Contrastive Registration for Unsupervised Medical Image Segmentation
L Liu, AI Aviles-Rivero, C-B Schonlieb
– IEEE transactions on neural networks and learning systems
(2025)
36,
147
(doi: 10.1109/TNNLS.2023.3332003)
Artificial immunofluorescence in a flash: Rapid synthetic imaging from brightfield through residual diffusion
X Xing, C Tang, S Murdoch, G Papanastasiou, Y Guo, X Xiao, J Cross-Zamirski, C-B Schönlieb, KX Liang, Z Niu, EF Fang, Y Wang, G Yang
– Neurocomputing
(2025)
612,
128715
(doi: 10.1016/j.neucom.2024.128715)
Maximum entropy on the mean and the Cramér rate function in statistical estimation and inverse problems: properties, models, and algorithms
Y Vaisbourd, R Choksi, A Goodwin, T Hoheisel, C-B Schönlieb
– Mathematical Programming
(2025)
214,
441
(doi: 10.1007/s10107-024-02189-7)
Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation
C Liu, Z Qiao, C Li, C-B Schönlieb
– SIAM Journal on Mathematics of Data Science
(2025)
7,
55
(doi: 10.1137/24M1633662)
AI for Net Zero: Energy and Transport. White Paper
J Aston, E Broadway, S Laizet, L Magri, A Mole, A Nóvoa, G Rigas, G Tretola, K Vogiatzaki, M Weiland, M Weissenbacher, L Benson, E Danopoulos, I Fumarola, X Jiang, A Plaksin, D Ozan, E Essmann, M Klaisoongnoen
(2025)
(doi: 10.17863/CAM.121198)
Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings
BJ Franks, M Eliasof, S Cantürk, G Wolf, CB Schönlieb, S Fellenz, M Kloft
– Transactions on Machine Learning Research
(2025)
2025-February,
Preface
TA Bubba, R Gaburro, S Gazzola, K Papafitsoros, M Pereyra, CB Schönlieb
– Lecture Notes in Computer Science
(2025)
15667 LNCS,
v
ESTIMATION OF SINGLE-CELL AND TISSUE PERTURBATION EFFECT IN SPATIAL TRANSCRIPTOMICS VIA SPATIAL CAUSAL DISENTANGLEMENT
S Megas, DG Chen, K Polanski, M Eliasof, CB Schönlieb, SA Teichmann
– 13th International Conference on Learning Representations Iclr 2025
(2025)
82875
Preface
TA Bubba, R Gaburro, S Gazzola, K Papafitsoros, M Pereyra, CB Schönlieb
– Lecture Notes in Computer Science
(2025)
15668 LNCS,
v
G-Adaptivity: optimised graph-based mesh relocation for finite element methods
J Rowbottom, G Maierhofer, T Deveney, E Mueller, A Paganini, K Schratz, P Lio, C-B Schonlieb, C Budd
– Proceedings of Machine Learning Research
(2025)
267,
52173
(link to publication)
Neural varifolds: an aggregate representation for quantifying the geometry of point clouds
J Lee, X Cai, CB Schönlieb, S Masnou
– Transactions on Machine Learning Research
(2025)
2025-June,
Graph Adaptive Autoregressive Moving Average Models
M Eliasof, A Gravina, A Ceni, C Gallicchio, D Bacciu, C-B Schonlieb
– Proceedings of Machine Learning Research
(2025)
267,
15232
(link to publication)
Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows
W Diepeveen, G Batzolis, Z Shumaylov, CB Schönlieb
– Proceedings of Machine Learning Research
(2025)
267,
13746
Towards Efficient Training of Graph Neural Networks: A Multiscale Approach
E Gal, M Eliasof, CB Schönlieb, II Kyrchei, E Haber, E Treister
– Transactions on Machine Learning Research
(2025)
2025-November,
LIE ALGEBRA CANONICALIZATION: EQUIVARIANT NEURAL OPERATORS UNDER ARBITRARY LIE GROUPS
Z Shumaylov, P Zaika, J Rowbottom, F Sherry, M Weber, CB Schönlieb
– 13th International Conference on Learning Representations Iclr 2025
(2025)
13401
A Study on the Adequacy of Common IQA Measures for Medical Images
A Breger, C Karner, I Selby, J Gröhl, S Dittmer, E Lilley, J Babar, J Beckford, TR Else, TJ Sadler, S Shahipasand, A Thavakumar, M Roberts, C-B Schönlieb
(2025)
1372,
451
(doi: 10.1007/978-981-96-3863-5_41)
Does probability exist?
D Spiegelhalter
– Nature
(2024)
636,
560
(doi: 10.1038/d41586-024-04096-5)
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation.
Z Deng, Y Chen, L Liu, S Wang, R Ke, C-B Schönlieb, AI Aviles-Rivero
– IEEE trans Intell Transp Syst
(2024)
26,
2747
(doi: 10.1109/tits.2024.3510551)

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