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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tt-vae-ganTimbre transfer with variational autoencoding and cycle-consistent adversarial networks. Able to transfer the timbre of an audio source to that of another.
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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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CIKM18-LCVACode for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
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deep-blueberryIf you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!
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SIVIUsing neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)
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Tensorflow Mnist CvaeTensorflow implementation of conditional variational auto-encoder for MNIST
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Pytorch RlThis repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
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KvaeKalman Variational Auto-Encoder
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vaeganAn implementation of VAEGAN (variational autoencoder + generative adversarial network).
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normalizing-flowsPyTorch implementation of normalizing flow models
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Variational AutoencoderVariational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
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Rectorchrectorch is a pytorch-based framework for state-of-the-art top-N recommendation
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haskell-vaeLearning about Haskell with Variational Autoencoders
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TextboxTextBox is an open-source library for building text generation system.
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Repo 2017Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano
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Awesome VaesA curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
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Deep Generative ModelsDeep generative models implemented with TensorFlow 2.0: eg. Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Deep Boltzmann Machine (DBM), Convolutional Variational Auto-Encoder (CVAE), Convolutional Generative Adversarial Network (CGAN)
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CS231nPyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
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sqairImplementation of Sequential Attend, Infer, Repeat (SQAIR)
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vae-torchVariational autoencoder for anomaly detection (in PyTorch).
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tganThe implementation of Temporal Generative Adversarial Nets with Singular Value Clipping
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multimodal-vae-publicA PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)
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GAN-Project-2018GAN in Tensorflow to be run via Linux command line
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BicycleGAN-pytorchPytorch implementation of BicycleGAN with implementation details
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gan tensorflowAutomatic feature engineering using Generative Adversarial Networks using TensorFlow.
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GAN-auto-writeGenerative Adversarial Network that learns to generate handwritten digits. (Learning Purposes)
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AdverseBiNetImproving Document Binarization via Adversarial Noise-Texture Augmentation
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tfjs-ganSimple GAN example using tensorflow JS core
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probai-2021-pyroRepo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
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BicycleGANTensorflow implementation of the NIPS paper "Toward Multimodal Image-to-Image Translation"
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DropoutsPyTorch Implementations of Dropout Variants
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CWRCode and dataset for Single Underwater Image Restoration by Contrastive Learning, IGARSS 2021, oral.
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ganbert-pytorchEnhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace
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srganPytorch implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
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artificial neural networksA collection of Methods and Models for various architectures of Artificial Neural Networks
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GAN-Anime-CharactersApplied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.
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AdvSegLossOfficial Pytorch implementation of Adversarial Segmentation Loss for Sketch Colorization [ICIP 2021]
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IrwGANOfficial pytorch implementation of the IrwGAN for unaligned image-to-image translation
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vae-pytorchAE and VAE Playground in PyTorch
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VINFRepository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
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cmdstanrCmdStanR: the R interface to CmdStan
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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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ganA 1D toy example of optimizing a generative model using the WGAN-GP model.
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adVAEImplementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection'
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