402 Open source projects that are alternatives of or similar to Variational Recurrent Autoencoder Tensorflow

brain.js is a GPU accelerated library for Neural Networks written in JavaScript.

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

HDLTex: Hierarchical Deep Learning for Text Classification

PyTorch Implementation of "A Hierarchical Latent Structure for Variational Conversation Modeling" (NAACL 2018 Oral)

Kalman Variational Auto-Encoder

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks (ICLR 2018)

Layer-wise Relevance Propagation (LRP) for LSTMs

Deep Learning sample programs using PyTorch in C++

Unofficial PyTorch Implementation of SUM-GAN from "Unsupervised Video Summarization with Adversarial LSTM Networks" (CVPR 2017)

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

Python library for Reservoir Computing using Echo State Networks

Variational Auto-Encoders in a Sequential Setting.

R interface to the keras library

The code for the MaD TwinNet. Demo page:

This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.

Code for the paper: Benhenda, M. 2017. ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.

Optimus: the first large-scale pre-trained VAE language model

A Collection of Variational Autoencoders (VAE) in PyTorch.

Handwriting Synthesis with RNNs ✏️

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

Blend beats using machine learning to create music in a fun new way.

Multitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587

Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)

videos, lectures, blogs for Deep Learning

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

Tensorflow implementation of the HarvardNLP paper - What You Get Is What You See: A Visual Markup Decompiler (https://arxiv.org/pdf/1609.04938v1.pdf)

Deep learning codes and projects using Python

Spying using Smartwatch and Deep Learning

[CVPR 2017] Generation and reconstruction of 3D shapes via modeling multi-view depth maps or silhouettes

Text Classification Algorithms: A Survey

Minimalist implementation of VQ-VAE in Pytorch

Quantize weights and activations in Recurrent Neural Networks.

Focal Frequency Loss for Generative Models

Biologically-realistic recurrent convolutional neural networks

Neural machine translator for English2German translation.

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Code for EMNLP18 paper "Spherical Latent Spaces for Stable Variational Autoencoders"

A Tensorfflow implementation of Attend, Infer, Repeat

Simple implementation of Variational Autoencoder

Learning the Enigma with Recurrent Neural Networks

SimpleDNN is a machine learning lightweight open-source library written in Kotlin designed to support relevant neural network architectures in natural language processing tasks

Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

News summarization using sequence to sequence model with attention in TensorFlow.

A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.

Some of the ML and DL related reading materials, research papers that I've read

Notebooks about Bayesian methods for machine learning

A bidirectional LSTM with attention for multiclass/multilabel text classification.

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

Implementation of Simple Recurrent Unit in Keras

Singing Voice Separation via Recurrent Inference and Skip-Filtering Connections - PyTorch Implementation. Demo:

Pytorch implementation of Block Neural Autoregressive Flow

Variational Autoencoder trained by Feature Perceputal Loss

Quasi-recurrent Neural Networks for Keras

Plain Stock Close-Price Prediction via Graves LSTM RNNs

[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks

PyTorch implementation of VQ-VAE by Aäron van den Oord et al.

keras project that parses and analyze english resumes

SRU is a recurrent unit that can run over 10 times faster than cuDNN LSTM, without loss of accuracy tested on many tasks.