Tf VqvaeTensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).
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tensorflow-mnist-AAETensorflow implementation of adversarial auto-encoder for MNIST
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Tensorflow Mnist VaeTensorflow implementation of variational auto-encoder for MNIST
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Generative ModelsAnnotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Stars: ✭ 438 (+1268.75%)
Tensorflow Mnist CvaeTensorflow implementation of conditional variational auto-encoder for MNIST
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Vae protein functionProtein function prediction using a variational autoencoder
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DraganA stable algorithm for GAN training
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Gan TutorialSimple Implementation of many GAN models with PyTorch.
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Link PredictionRepresentation learning for link prediction within social networks
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Discogan PytorchPyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
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Tensorflow 101中文的 tensorflow tutorial with jupyter notebooks
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Pytorch Vq VaePyTorch implementation of VQ-VAE by Aäron van den Oord et al.
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Neuralnetworks.thought ExperimentsObservations and notes to understand the workings of neural network models and other thought experiments using Tensorflow
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probabilistic nlgTensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).
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vqvae-2PyTorch implementation of VQ-VAE-2 from "Generating Diverse High-Fidelity Images with VQ-VAE-2"
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Fun-with-MNISTPlaying with MNIST. Machine Learning. Generative Models.
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VAE-Gumbel-SoftmaxAn implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.
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style-vaeImplementation of VAE and Style-GAN Architecture Achieving State of the Art Reconstruction
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haskell-vaeLearning about Haskell with Variational Autoencoders
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srVAEVAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.
Stars: ✭ 56 (+75%)
ZhihuThis repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
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Neural OdeJupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
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Medmnist[ISBI'21] MedMNIST Classification Decathlon: A Lightweight AutoML Benchmark for Medical Image Analysis
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Disentangling VaeExperiments for understanding disentanglement in VAE latent representations
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Joint VaePytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation 🌟
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Awesome VaesA curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
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Motion SenseMotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope)
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Mnist drawThis is a sample project demonstrating the use of Keras (Tensorflow) for the training of a MNIST model for handwriting recognition using CoreML on iOS 11 for inference.
Stars: ✭ 139 (+334.38%)
Pytorch VaeA CNN Variational Autoencoder (CNN-VAE) implemented in PyTorch
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Generative adversarial networks 101Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
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Deep Learning With PythonExample projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
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catseyeNeural network library written in C and Javascript
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InpaintNetCode accompanying ISMIR'19 paper titled "Learning to Traverse Latent Spaces for Musical Score Inpaintning"
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generative deep learningGenerative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)
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char-VAEInspired by the neural style algorithm in the computer vision field, we propose a high-level language model with the aim of adapting the linguistic style.
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DiffuseVAEA combination of VAE's and Diffusion Models for efficient, controllable and high-fidelity generation from low-dimensional latents
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First Order ModelThis repository contains the source code for the paper First Order Motion Model for Image Animation
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Alae[CVPR2020] Adversarial Latent Autoencoders
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Generative models tutorial with demoGenerative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..
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Dsprites DatasetDataset to assess the disentanglement properties of unsupervised learning methods
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Deepsvg[NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data.
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Keras Idiomatic ProgrammerBooks, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
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Tensorflow BookAccompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
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Generative ModelsCollection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
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DancenetDanceNet -💃💃Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)
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Vae TensorflowA Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).
Stars: ✭ 117 (+265.63%)
DeeptimeDeep learning meets molecular dynamics.
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Cifar-AutoencoderA look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.
Stars: ✭ 42 (+31.25%)
Sentence VaePyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349
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