A Bayesian framework for Multi-Frame Image Super-Resolution. Based on "Bayesian Image Super-Resolution" (ME Tipping and CM Bishop, NeurIPS 2003)
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Updated
May 18, 2021 - Jupyter Notebook
A Bayesian framework for Multi-Frame Image Super-Resolution. Based on "Bayesian Image Super-Resolution" (ME Tipping and CM Bishop, NeurIPS 2003)
A MAP-MRF Framework for Image Denoising
Research website
Verified the robustness to outliers of Huber Loss with Hinge loss for classification over different datasets.
Regression Analysis using dataset from different Industries
Compute the modified Huber loss gradient with respect to a model parameter.
Compute the Huber loss gradient with respect to a model parameter.
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