227 Open source projects that are alternatives of or similar to Advanced_Models

Repository for implementation of generative models with Tensorflow 1.x

GANs Implementations in Keras

Simple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

dcgan combined with vae in pytorch!

MXNet Implementation of DCGAN, Conditional GAN, pix2pix

A collection of deep learning models (PyTorch implemtation)

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"

Implementation of Conditional Generative Adversarial Networks in PyTorch

Collection of generative models in Tensorflow

DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络（GAN,Generative Adversarial Network）图像生成的理论与实践研究。

でぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet

Deep Learning sample programs using PyTorch in C++

PyTorch Impl. of Prediction Optimizer (to stabilize GAN training)

Implementation of a Neural Network that can detect whether a video is in-game or not

Create an AI that chats like you

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

Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).

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

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

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

A implementation of DCGAN (Deep Convolutional Generative Adversarial Networks) for CIFAR10 image

No description or website provided.

Simple Implementation of many GAN models with PyTorch.

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Tensorflow implementation of adversarial auto-encoder for MNIST

A DCGAN that generate Cat pictures 🐱‍💻

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

PyTorch study

This project is a semi-supervised approach to detect emotions on faces in-the-wild using GAN

EfficientMORL (ICML'21)

Improving MMD-GAN training with repulsive loss function

Implementation of Resnet-50 with and without CBAM in PyTorch v1.8. Implementation tested on Intel Image Classification dataset from https://www.kaggle.com/puneet6060/intel-image-classification.

Playing with MNIST. Machine Learning. Generative Models.

A basic and simple tool for code auto completion

GPT-2 Telegram Chat bot

Chainer implementation of the paper Robust Conditional Generative Adversarial Networks

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

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

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

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

DCGAN image generator 🖼️.

Implementation of some different variants of GANs by tensorflow, Train the GAN in Google Cloud Colab, DCGAN, WGAN, WGAN-GP, LSGAN, SNGAN, RSGAN, RaSGAN, BEGAN, ACGAN, PGGAN, pix2pix, BigGAN

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

Image completion using deep convolutional generative adversarial nets in tensorflow

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Tensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.

Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN

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

DCGAN implementation by TensorFlow

Atom client for Tabnine - Code Faster with the All-Language AI Assistant for Code Completion, autocomplete JavaScript, Python, TypeScript, PHP, Go, Java, node.js, Ruby, C/C++, HTML/CSS, C#, Rust, SQL, Bash, Kotlin, React, Swift, Scala, Sass, Perl, Objective C, Node JS, Matlab, Haskell, Dart, Angular. https://atom.io/packages/tabnine

Deepstory turns a text/generated text into a video where the character is animated to speak your story using his/her voice.

Resources and Implementations of Generative Adversarial Nets which are focusing on how to stabilize training process and generate high quality images: DCGAN, WGAN, EBGAN, BEGAN, etc.

DCGAN face generator 🧑.

Semantic Image Inpainting

PyTorch implementation of GANs (Generative Adversarial Networks). DCGAN, Pix2Pix, CycleGAN, SRGAN

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

Invariant representation learning from imaging and spectral data

Assessing Generative Models via Precision and Recall (official repository)