Special session on Advances in Model-based deep Learning in EUSIPCO 2023 co-organized by Aleksandra featured six papers on different aspects of model-aware deep learning, ranging from asymptotic analysis and stability of unfolded optimization algorithms, and non-linear state estimation to federated learning, clustering and convolutional framelets in various applications, in computer vision for smart cities, remote sensing and medical imaging.
In this special session, Xianlu Li presented our paper Model-Aware Deep Learning for the Clustering of Hyperspectral Images with Context Preservation.
Two other papers from GAIM were accepted and presented at EUSIPCO in Helsinki.
Nicolas Vercheval presented the paper on counterfactuals in functional brain imaging Counterfactual Functional Connectomes for Neurological Classifier Selection.
Nicolas Nadisic co-authored a paper on the theoretical aspects of simultaneous sparse coding Exact and Heuristic Methods for Simultaneous Sparse Coding.
