590 Open source projects that are alternatives of or similar to classifying-vae-lstm

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

Tensorflow implementation of variational auto-encoder for MNIST

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

PyTorch implementation of "Auto-Encoding Variational Bayes"

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

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

Collection of generative models in Tensorflow

Machine learning, in numpy

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

No description or website provided.

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

Experiments for understanding disentanglement in VAE latent representations

A CNN Variational Autoencoder (CNN-VAE) implemented in PyTorch

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

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

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

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

Invariant representation learning from imaging and spectral data

A Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).

Tensorflow implementation of conditional variational auto-encoder for MNIST

Stochastic Adversarial Video Prediction

Official implementation of the paper "Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders" (CVPR 2019)

Assessing Generative Models via Precision and Recall (official repository)

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Pytorch implementation of Hyperspherical Variational Auto-Encoders

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.

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

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

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

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

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

Protein function prediction using a variational autoencoder

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

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

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

Lagrangian VAE

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

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

Variational Neural Machine Translation System

Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.

VirNet: A deep attention model for viral reads identification

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

Tensorflow Implementation of Densely Connected Bidirectional LSTM with Applications to Sentence Classification

Repository for the experiments described in the paper named "DeepSentiPers: Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus"

Implementation of a paper "Polyphonic Music Generation with Sequence Generative Adversarial Networks" in TensorFlow

Sequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.

PyTorch implementation of a 2D-LSTM Seq2Seq Model for NMT.

Video lstm auto encoder built with pytorch. https://arxiv.org/pdf/1502.04681.pdf

An open-source sleep stage classification Python package

A combination of VAE's and Diffusion Models for efficient, controllable and high-fidelity generation from low-dimensional latents

Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

No description or website provided.

The project uses state of the art deep learning on collected data for automatic analysis of emotions.

Samples for TensorFlow binding for .NET by Lost Tech

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

No description or website provided.

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

Pytorch implementation of HTR on IAM dataset (word or line level + CTC loss)

CPU and GPU implementations of some 2D RNN layers