Package for Multimodal Autoencoders in TensorFlow / Keras
GPL-3.0 License
Tensorflow implementation of conditional variational auto-encoder for MNIST
Disentangled representation learning model for digital pathology data as a custom similarity metr...
Tensorflow implementation of adversarial auto-encoder for MNIST
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g...
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in ...
A collection of computer vision pre-trained models.
Tensorflow implementation of variational auto-encoder for MNIST
TensorFlow 2.0 library for distributed training, evaluation, model selection, and fast prototyping.
Header-only library for using Keras (TensorFlow) models in C++.