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Found 3 papers, 2 papers with code
Open Problem: Active Representation Learning
In this work, we introduce the concept of Active Representation Learning, a novel class of problems that intertwines exploration and representation learning within partially observable environments.
Representation Learning
Simultaneous Localization and Mapping
Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration
Our approach combines a pre-trained network to extract deep features from the input image with iterative Richardson-Lucy deconvolution steps.
LUCYD: A Feature-Driven Richardson-Lucy Deconvolution Network
Our results demonstrate that LUCYD outperforms the state-of-the-art methods in both synthetic and real microscopy images, achieving superior performance in terms of image quality and generalisability.
