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Search results for python variational autoencoder

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211 search results found

Pytorch Vae ⭐ 5,292

A Collection of Variational Autoencoders (VAE) in PyTorch.

Tensorflow Generative Model Collections ⭐ 3,570

Collection of generative models in Tensorflow

Benchmark_vae ⭐ 1,597

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

Continual Learning ⭐ 1,190

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Repo 2017 ⭐ 1,146

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Next RecSys Library

Disentangling Vae ⭐ 668

Experiments for understanding disentanglement in VAE latent representations

Normalizing Flows ⭐ 520

PyTorch implementation of normalizing flow models

Vae Cvae Mnist ⭐ 508

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Focal Frequency Loss ⭐ 407

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

Tensorflow Mnist Vae ⭐ 379

Tensorflow implementation of variational auto-encoder for MNIST

Pytorch Rl ⭐ 356

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Pytorch Generative ⭐ 355

Easy generative modeling in PyTorch.

Icml18 Jtnn ⭐ 305

Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

Dalle Mtf ⭐ 296

Open-AI's DALL-E for large scale training in mesh-tensorflow.

Variational Recurrent Autoencoder Tensorflow ⭐ 226

A tensorflow implementation of "Generating Sentences from a Continuous Space"

S Vae Pytorch ⭐ 214

Pytorch implementation of Hyperspherical Variational Auto-Encoders

Variational autoencoder for metagenomic binning

Video_prediction ⭐ 199

Stochastic Adversarial Video Prediction

S Vae Tf ⭐ 178

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

Generative And Discriminative Voxel Modeling ⭐ 170

Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification

Brain Inspired Replay ⭐ 169

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

Deep and Machine Learning for Microscopy

Variational Autoencoder for Dimensionality Reduction of Time-Series

Numalogic ⭐ 156

Collection of operational time series ML models and tools

Vae_vampprior ⭐ 151

Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling

Vae Celeba ⭐ 150

Variational auto-encoder trained on celebA . All rights reserved.

Vae_anomaly_detection ⭐ 148

Codeslam ⭐ 146

Implementation of CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM paper (https://arxiv.org/pdf/1804.00874.pdf)

Python World ⭐ 143

Official implementation of Dynamical VAEs

Pytorch implementation of Block Neural Autoregressive Flow

Musemorphose ⭐ 140

PyTorch implementation of MuseMorphose, a Transformer-based model for music style transfer.

Variational Animal Motion Embedding - A tool for time series embedding and clustering

Tensorflow Mnist Cvae ⭐ 134

Tensorflow implementation of conditional variational auto-encoder for MNIST

Unsupervised_anomaly_detection_brain_mri ⭐ 123

Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study

Fusilli ⭐ 120

A Python package housing a collection of deep-learning multi-modal data fusion method pipelines! From data loading, to training, to evaluation - fusilli's got you covered 🌸

Unsupervised Real Image Super-Resolution via Variational AutoEncoder in CVPR2020

Variational Autoencoder Pytorch ⭐ 114

Variational Autoencoder implemented with PyTorch, Trained over CelebA Dataset

Neuraldialog Larl ⭐ 107

PyTorch implementation of latent space reinforcement learning for E2E dialog published at NAACL 2019. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU

Rectorch ⭐ 104

rectorch is a pytorch-based framework for state-of-the-art top-N recommendation

Data Augmentation with Variational Autoencoders (TPAMI)

Mojitalk ⭐ 98

Code for "MojiTalk: Generating Emotional Responses at Scale" https://arxiv.org/abs/1711.04090

Kalman Variational Auto-Encoder

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

Deepwriting ⭐ 94

Code for `DeepWriting: Making Digital Ink Editable via Deep Generative Modeling` paper

Carla Ppo ⭐ 86

This repository hosts a customized PPO based agent for Carla. The goal of this project is to make it easier to interact with and experiment in Carla with reinforcement learning based agents -- this, by wrapping Carla in a gym like environment that can handle custom reward functions, custom debug output, etc.

An implementation of VAEGAN (variational autoencoder + generative adversarial network).

Vae For Image Generation ⭐ 75

Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR10 datasets

Mmd Variational Autoencoder ⭐ 71

CALC2.0: Combining Appearance, Semantic and Geometric Information for Robust and Efficient Visual Loop Closure

Contiguous Succotash ⭐ 70

Recurrent Variational Autoencoder with Dilated Convolutions that generates sequential data implemented in pytorch

Collaborativevae ⭐ 69

Variational Autoencoder with Arbitrary Conditioning

Gumbel_softmax_vae ⭐ 67

PyTorch implementation of a Variational Autoencoder with Gumbel-Softmax Distribution

Implementation_variational Auto Encoder ⭐ 67

Simple implementation of Variational Autoencoder

An unofficial toy implementation for NVAE 《A Deep Hierarchical Variational Autoencoder》

Resnetvae ⭐ 66

Variational AutoEncoder + ResNet Transfer Learning

Vae_tensorflow ⭐ 64

Variational autoencoder in Tensorflow

D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019

Unsuperviseddeeplearning Pytorch ⭐ 63

This repository tries to provide unsupervised deep learning models with Pytorch

Vae Gumbel Softmax ⭐ 60

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

Pytorch implementation of stochastically quantized variational autoencoder (SQ-VAE)

code for Syntax-Directed Variational Autoencoder that generates programs and molecues

Variational Recurrent Autoencoder ⭐ 55

Implementation of the VRAE

Music Sketchnet ⭐ 55

ISMIR 2020 Paper repo: Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm

Tf Var Attention ⭐ 55

Tensorflow Implementation of Variational Attention for Sequence to Sequence Models (COLING 2018)

Vae_householder_flow ⭐ 53

Code for the paper "Improving Variational Auto-Encoders using Householder Flow" (https://arxiv.org/abs/1611.09630)

Multimodal Vae Public ⭐ 52

A PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)

STCN: Stochastic Temporal Convolutional Networks

Vae_tacotron2 ⭐ 51

VAE Tacotron 2, an alternative of GST Tacotron

Li_emnlp_2017 ⭐ 51

Deep Recurrent Generative Decoder for Abstractive Text Summarization in DyNet

Openvae_continuallearning ⭐ 49

Open-source code for our paper: Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

Artificialintelligenceengines ⭐ 48

Computer code collated for use with Artificial Intelligence Engines book by JV Stone

Variationaldeepsemantichashing ⭐ 48

The original implementation of the models and experiments of Variational Deep Semantic Hashing paper (SIGIR 2017)

Class Incremental Learning ⭐ 48

PyTorch implementation of a VAE-based generative classifier, as well as other class-incremental learning methods that do not store data (DGR, BI-R, EWC, SI, CWR, CWR+, AR1, the "labels trick", SLDA).

Vae Concrete ⭐ 46

Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution

Scipy2015 ⭐ 44

Talk for SciPy2015 "Deep Learning: Tips From The Road"

Vae_protein_function ⭐ 44

Protein function prediction using a variational autoencoder

MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations

Source Filter Vae ⭐ 42

Learning and controlling the source-filter representation of speech with a variational autoencoder

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

Invariant representation learning from imaging and spectral data

Wae Rnf Lm ⭐ 40

Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399

Vae_gumble_softmax ⭐ 38

pytorch implementation of VAE-Gumble-Softmax

Precision Recall Distributions ⭐ 38

Assessing Generative Models via Precision and Recall (official repository)

Vae Tensorflow ⭐ 37

(beta-)VAE Tensorflow

Minimal_vae ⭐ 36

A minimal implementation of an Variational Auto-Encoder

Midi Vae ⭐ 36

Cvaecaposr ⭐ 36

Code for the Paper: "Conditional Variational Capsule Network for Open Set Recognition", Y. Guo, G. Camporese, W. Yang, A. Sperduti, L. Ballan, ICCV, 2021.

Playing_with_vae ⭐ 34

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Tt Vae Gan ⭐ 34

Timbre transfer with variational autoencoding and cycle-consistent adversarial networks. Able to transfer the timbre of an audio source to that of another.

Generative_continual_learning ⭐ 33

Deepmusicvstyle ⭐ 33

Code repo for ICME 2020 paper "Style-Conditioned Music Generation". VAE model that allows style-conditioned music generation.

Mixed-curvature Variational Autoencoders (ICLR 2020)

Shot Vae ⭐ 33

The implementation of the SHOT-VAE model in paper "SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations"

Gaussian Process Prior Variational Autoencoder

codes for Variational Autoencoder for Semi-supervised Text Classification

Variational autoencoder for single cell RNA-seq datasets

Numpy Nn Model ⭐ 32

Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.

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