deeplearning-models is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
These projects were analysed and named deeplearning-models among their alternatives. The relationship is not symmetric — how deeplearning-models rates them is a separate judgement, made when deeplearning-models is analysed in its own right.
calls deeplearning-models “Model-by-model notebooks spanning PyTorch, TF and Keras; choose it to look up a specific architecture instead of following a book linearly.”
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.