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  • Currently displaying 101 - 120 of 1600 publications
Learning Regularization for Graph Inverse Problems
M Eliasof, MSR Siddiqui, C-B Schönlieb, E Haber
– Proceedings of the AAAI Conference on Artificial Intelligence
(2025)
39,
16471
(doi: 10.1609/aaai.v39i16.33809)
Iterative Operator Sketching Framework for Large-Scale Imaging Inverse Problems
J Tang, S Mukherjee, C-B Schönlieb
– ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings
(2025)
00,
1
(doi: 10.1109/ICASSP49660.2025.10890355)
Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations
Y Zhang, C-W Cheng, J He, Z He, C-B Schönlieb, Y Chen, AI Aviles-Rivero
– Proceedings of the AAAI Conference on Artificial Intelligence
(2025)
39,
10302
(doi: 10.1609/aaai.v39i10.33118)
On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
A Gravina, M Eliasof, C Gallicchio, D Bacciu, C-B Schönlieb
– Proceedings of the Aaai Conference on Artificial Intelligence
(2025)
39,
16906
(doi: 10.1609/aaai.v39i16.33858)
SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events
YK Chen, S Dittmer, K Bernatowicz, J Arús-Pous, K Bliznashki, J Aston, JHF Rudd, C-B Schönlieb, J Jones, M Roberts
(2025)
(doi: 10.48550/arxiv.2504.04997)
Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction
L Yang, J Huang, Y Fang, AI Aviles-Rivero, C-B Schönlieb, D Zhang, G Yang
– IEEE Transactions on Instrumentation and Measurement
(2025)
74,
1
(doi: 10.1109/TIM.2025.3554318)
Enhancing Brain Age Prediction and Neurodegeneration Detection with Contrastive Learning on Regional Biomechanical Properties
J Träuble, LV Hiscox, C Johnson, A Aviles-Rivero, CB Schönlieb, GSK Schierle
(2025)
(doi: 10.1101/2025.03.25.645330)
A Study of Why We Need to Reassess Full Reference Image Quality Assessment with Medical Images
A Breger, A Biguri, MS Landman, I Selby, N Amberg, E Brunner, J Gröhl, S Hatamikia, C Karner, L Ning, S Dittmer, M Roberts, AIX-COVNET Collaboration, C-B Schönlieb
– J Imaging Inform Med
(2025)
38,
3444
(doi: 10.1007/s10278-025-01462-1)
TIGRE v3: Efficient and easy to use iterative computed tomographic reconstruction toolbox for real datasets
A Biguri, T Sadakane, R Lindroos, Y Liu, MS Landman, Y Du, M Lohvithee, S Kaser, S Hatamikia, R Bryll, E Valat, S Wonglee, T Blumensath, C-B Schönlieb
– Engineering Research Express
(2025)
7,
015011
(doi: 10.1088/2631-8695/adbb3a)
Domain generalization and punch mark classification
W Peaslee, L Wrapson, C-B Schönlieb
– Journal of Cultural Heritage
(2025)
72,
226
(doi: 10.1016/j.culher.2025.02.001)
Artificial intelligence assisted identification of newborn auricular deformities via smartphone application.
L-J Ren, R-J Yang, L-L Chen, S-Y Wang, C-L Li, Y Huang, T-Y Zhang, Y-Y Fu, S Wang
– Eclinicalmedicine
(2025)
81,
103124
(doi: 10.1016/j.eclinm.2025.103124)
On the caveats of AI autophagy
X Xing, F Shi, J Huang, Y Wu, Y Nan, S Zhang, Y Fang, M Roberts, C-B Schönlieb, J Del Ser, G Yang
– Nature Machine Intelligence
(2025)
7,
172
(doi: 10.1038/s42256-025-00984-1)
Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses
Y Xiong, L Yao, J Lin, J Yao, Q Bai, Y Huang, X Zhang, R Huang, R Wang, K Wang, Y Qi, P Zhu, H Wang, L Liu, J Zhou, J Guo, F Chen, C Dai, S Wang
– Nature Communications
(2025)
16,
1425
(doi: 10.1038/s41467-025-56784-z)
Conscious and unconscious processes in vision and homeostasis
AS Fokas, NK Logothetis
– Frontiers in Behavioral Neuroscience
(2025)
19,
1516127
(doi: 10.3389/fnbeh.2025.1516127)
The Troublesome Kernel: On Hallucinations, No Free Lunches, and the Accuracy-Stability Tradeoff in Inverse Problems
NM Gottschling, V Antun, AC Hansen, B Adcock
– SIAM Review
(2025)
67,
73
(doi: 10.1137/23m1568739)
The Troublesome Kernel: On Hallucinations, No Free Lunches, and the Accuracy-Stability Tradeoff in Inverse Problems
A Hansen
– SIAM Review
(2025)
(doi: 10.1137/23M1568739)
A Pipeline for Automated Quality Control of Chest Radiographs.
IA Selby, E González Solares, A Breger, M Roberts, L Escudero Sánchez, J Babar, JHF Rudd, NA Walton, E Sala, C-B Schönlieb, JR Weir-McCall, AIX-COVNET Collaboration
– Radiology: Artificial Intelligence
(2025)
7,
e240003
(doi: 10.1148/ryai.240003)
Development and External Validation of [18F]FDG PET-CT-Derived Radiomic Models for Prediction of Abdominal Aortic Aneurysm Growth Rate
SS Dhesi, P Adusumilli, N Ravikumar, MA Waduud, R Frood, AF Frangi, G McDermott, JHF Rudd, Y Huang, JR Boyle, M Elkhawad, DE Newby, N Joshi, JY Kwan, P Coughlin, MA Bailey, AF Scarsbrook
– Algorithms
(2025)
18,
86
(doi: 10.3390/a18020086)
Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey
A Essakine, Y Cheng, CW Cheng, L Zhang, Z Deng, L Zhu, CB Schönlieb, AI Aviles-Rivero
– Transactions on Machine Learning Research
(2025)
2025-February,
1
Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis
X Chen, Y Huang, B Jessney, J Sangha, S Gu, C-B Schönlieb, M Bennett, M Roberts
(2025)
(doi: 10.48550/arxiv.2501.18614)
(link to publication)

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