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Found 3 papers, 2 papers with code
A primal-dual data-driven method for computational optical imaging with a photonic lantern
A proximal algorithm based on a sparsity prior, dubbed SARA-COIL, has been further proposed to solve the associated inverse problem, to enable image reconstructions for high resolution COIL microendoscopy.
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
Machine Unlearning (MU) is an increasingly important topic in machine learning safety, aiming at removing the contribution of a given data point from a training procedure.
On the pitfalls of entropy-based uncertainty for multi-class semi-supervised segmentation
Semi-supervised learning has emerged as an appealing strategy to train deep models with limited supervision.
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