94 Open source projects that are alternatives of or similar to Scvi Tools

Variational autoencoder for Lego minifig faces

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Experiments with Adversarial Autoencoders using Keras

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

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

Variational autoencoder, denoising autoencoder and other variations of autoencoders implementation in keras

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Pytorch implementation of Hyperspherical Variational Auto-Encoders

PyTorch implementation of normalizing flow models

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

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

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

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

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

Text Variational Autoencoder inspired by the paper 'Generating Sentences from a Continuous Space' Bowman et al. https://arxiv.org/abs/1511.06349

Variational Neural Machine Translation System

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Variational autoencoders for collaborative filtering

Assessing Generative Models via Precision and Recall (official repository)

Learning about Haskell with Variational Autoencoders

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

An Introduction to Deep Generative Modeling: Examples

No description or website provided.

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

Implementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection'

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

VAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.

Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch

Generative 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..

CVAE_XGate model in paper "Xu, Dusek, Konstas, Rieser. Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity"

Code for our paper -- Hyperprior Induced Unsupervised Disentanglement of Latent Representations (AAAI 2019)

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

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

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

Lagrangian VAE

Invariant representation learning from imaging and spectral data

TextBox is an open-source library for building text generation system.

Torch Implemention of ECCV'16 paper: Attribute2Image

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

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A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

If 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!

We got a stew going!

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

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).

Using 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)

AE and VAE Playground in PyTorch

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

Collection of generative models in Tensorflow

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

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

Stochastic Adversarial Video Prediction

music generation with a classifying variational autoencoder (VAE) and LSTM

Variational autoencoder for anomaly detection (in PyTorch).

Tensorflow implementation of variational auto-encoder for MNIST

Experiments for understanding disentanglement in VAE latent representations

Tensorflow Implementation of Knowledge-Guided CVAE for dialog generation ACL 2017. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU

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

Shared Latent Space VAE's