114 Open source projects that are alternatives of or similar to Twostagevae

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🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib

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Inspired 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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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.

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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.

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PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

PyTorch implementation of VQ-VAE-2 from "Generating Diverse High-Fidelity Images with VQ-VAE-2"

여러가지 유명한 신경망 모델들을 제공합니다. (DCGAN, VAE, Resnet 등등)

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

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

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PyTorch study

dcgan combined with vae in pytorch!

Implementation of the paper - Automatic chemical design using a data-driven continuous representation of molecules

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

Tensorflow implementation of adversarial auto-encoder for MNIST

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI

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DeepGTT: Learning Travel Time Distributions with Deep Generative Model

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

Code accompanying ISMIR'19 paper titled "Learning to Traverse Latent Spaces for Musical Score Inpaintning"

EfficientMORL (ICML'21)

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Playing with MNIST. Machine Learning. Generative Models.

Keras implementations of three language models: character-level RNN, word-level RNN and Sentence VAE (Bowman, Vilnis et al 2016).

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Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.

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VPoser: Variational Human Pose Prior

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

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

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