This is a TensorFlow implementation of the (Variational) Graph Auto-Encoder model as described in paper Variational Graph Auto-Encoders, T. N. Kipf, M. Welling, NIPS Workshop on Bayesian Deep Learning ...

Variational-Graph-Auto-Encoders This is the implementation of paper "Variational Graph Auto-Encoders", which is published in NIPS 2016 Workshop. Thomas N. Kipf, Max Welling, Variational Graph ...

A consequence of this is that the graph used for decoding the D-codeword, which is different from the encoder graph, is of low complexity. Moreover, with the appropriate modification of the RA encoder ...

Graph based clustering plays an important role in clustering area. Recent studies about graph convolution neural networks have achieved impressive success on graph type data. However, in traditional ...

To sum it up CodeT5+ is a new family of open-source, large-language models with an encoder-decoder architecture that may function in several modes (encoder-only, decoder-only, and encoder-decoder) to ...