Machine learning, in numpy
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Updated
Oct 29, 2023 - Python
Machine learning, in numpy
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
A Collection of Variational Autoencoders (VAE) in PyTorch.
DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络(GAN,Generative Adversarial Network)图像生成的理论与实践研究。
Collection of generative models in Tensorflow
Advanced Deep Learning with Keras, published by Packt
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
Vector Quantized VAEs - PyTorch Implementation
Experiments for understanding disentanglement in VAE latent representations
A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).
PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349
Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch
Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)
Pytorch implementation of β-VAE
Tensorflow implementation of variational auto-encoder for MNIST
Minimalist implementation of VQ-VAE in Pytorch
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"
Optimus: the first large-scale pre-trained VAE language model
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