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Beyond Task Success: A Theory of Representation Reuse
Zibo Meng, Andrew C. M. Austin, Alin Achim
A learned representation is useful beyond its source task only if later tasks can make use of what the encoder has already learned. Source-task performance, however, gives no guara…
Diffusion Meets Unrolling: Compressive SAR Image Reconstruction with Interleaved Learned Corrections
Odysseas Pappas, Andrew C. M. Austin, Perla Mayo +2
Compressive Synthetic Aperture Radar (SAR) imaging, typically formulated as an inverse problem and solved with traditional iterative optimisation methods, can be very computational…
WBCBench 2026: A Challenge for Robust White Blood Cell Classification Under Class Imbalance
Xin Tian, Xudong Ma, Tianqi Yang +4
We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulties: (i) severe class imbalan…
Single Image Super-Resolution via Bivariate `A Trous Wavelet Diffusion
Maryam Heidari, Nantheera Anantrasirichai, Alin Achim
The effectiveness of super resolution (SR) models hinges on their ability to recover high frequency structure without introducing artifacts. Diffusion based approaches have recentl…
AWDiff: An a trous wavelet diffusion model for lung ultrasound image synthesis
Maryam Heidari, Nantheera Anantrasirichai, Steven Walker +2
Lung ultrasound (LUS) is a safe and portable imaging modality, but the scarcity of data limits the development of machine learning methods for image interpretation and disease moni…
An InSAR Phase Unwrapping Framework for Large-scale and Complex Events
Yijia Song, Juliet Biggs, Alin Achim +3
Phase unwrapping remains a critical and challenging problem in InSAR processing, particularly in scenarios involving complex deformation patterns. In earthquake-related deformation…