sunshineatnoon/Paper-Implementations
Use PyTorch to implement some classic frameworks
This collection provides ready-to-use PyTorch code examples for common machine learning tasks, such as classifying images, generating new images, or applying artistic styles to photos. It helps AI researchers and deep learning practitioners quickly understand and apply the techniques from various influential academic papers. You input your datasets or images, and the code produces trained models, new generated images, or artistically styled images.
622 stars. No commits in the last 6 months.
Use this if you are a deep learning practitioner or researcher looking for practical PyTorch implementations of classic machine learning models to jumpstart your projects or learn how these models work.
Not ideal if you are a non-technical user seeking a no-code solution for image classification or generation, or if you need a high-level API for deployment without diving into model architecture.
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May 27, 2017
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