Abstract: Seismic deconvolution is essential for extracting layer information from noisy seismic data, but it is an ill-posed problem with nonunique solutions. Inspired by classical optimization ...
This is the official implementation of our paper GaussianImage, a groundbreaking paradigm of image representation and compression by 2D Gaussian Splatting. With compact 2D Gaussian representation and ...
Abstract: Conventional deconvolution methods utilize hand-crafted image priors to constrain the optimization. While deep-learning-based methods have simplified the optimization by end-to-end training, ...
Methods to deconvolute experimental mixture spectra via a model that is trained on experimental pure-component spectra. This is documentation for https://github.com ...
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