209 Open source projects that are alternatives of or similar to vae-pytorch

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

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

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

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

Experiments with Adversarial Autoencoders using Keras

Next RecSys Library

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

Focal Frequency Loss for Generative Models

Tensorflow implementation of variational auto-encoder for MNIST

Learning about Haskell with Variational Autoencoders

Training and evaluating a variational autoencoder for pan-cancer gene expression data

Tensorflow implementation of conditional variational auto-encoder for MNIST

Shared Latent Space VAE's

Dual CNN Models for Unsupervised Monocular Depth Estimation

Noise removal from images using Convolutional autoencoder

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

Unsupervised (Self-Supervised) Clustering of Seismic Signals Using Deep Convolutional Autoencoders

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

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

Real time face landmarking using decision trees and NN autoencoders

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

A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

Hands-on in-person workshop for Deep Learning with TensorFlow

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

Variational autoencoder for anomaly detection (in PyTorch).

This is my attempt to reproduce and extend the results in the paper "An Introduction to Deep Learning for the Physical Layer" by Tim O'Shea and Jakob Hoydis

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Torch Implemention of ECCV'16 paper: Attribute2Image

Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

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.

The implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation"

Global NIPS Paper Implementation Challenge of "Hiding Images in Plain Sight: Deep Steganography"

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

Neural network library written in C and Javascript

Variational autoencoder for Lego minifig faces

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

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

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

Invariant representation learning from imaging and spectral data

Colorizing B&W Photos with Neural Networks

Image retrieval program made in Tensorflow supporting VGG16, VGG19, InceptionV3 and InceptionV4 pretrained networks and own trained Convolutional autoencoder.

Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"

Tensorflow implementation of adversarial auto-encoder for MNIST

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

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Autoencoder trained on ImageNet Using Torch 7

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

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

Convolutional AutoEncoder application on MRI images

This is the official implementation for the paper 'AutoEncoder by Forest'

Easy Reduced Basis method

Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)

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!

Tensorflow 2.0 implementation of Adversarial Autoencoders

This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion

Assessing Generative Models via Precision and Recall (official repository)

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