Advanced-Deep-Learning-with-Keras VS ALAE

Compare Advanced-Deep-Learning-with-Keras vs ALAE and see what are their differences.

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Advanced-Deep-Learning-with-Keras ALAE
1 1
1,716 3,494
0.2% -
0.0 0.0
about 1 year ago over 3 years ago
Python Python
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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Advanced-Deep-Learning-with-Keras

Posts with mentions or reviews of Advanced-Deep-Learning-with-Keras. We have used some of these posts to build our list of alternatives and similar projects.

ALAE

Posts with mentions or reviews of ALAE. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Advanced-Deep-Learning-with-Keras and ALAE you can also consider the following projects:

AdaVAE - [Preprint] AdaVAE: Exploring Adaptive GPT-2s in VAEs for Language Modeling PyTorch Implementation

jukebox - Code for the paper "Jukebox: A Generative Model for Music"

PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.

dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).

Speech_driven_gesture_generation_with_autoencoder - This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".

simsiam-cifar10 - Code to train the SimSiam model on cifar10 using PyTorch

generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)

Keras-GAN - Keras implementations of Generative Adversarial Networks.

lightweight-gan - Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two

denoising-diffusion-pytorch - Implementation of Denoising Diffusion Probabilistic Model in Pytorch

torch-metrics - Metrics for model evaluation in pytorch