692 Open source projects that are alternatives of or similar to Smrt

Tensorflow implementation of conditional variational auto-encoder for MNIST

Tensorflow implementation of variational auto-encoder for MNIST

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

Next RecSys Library

Focal Frequency Loss for Generative Models

Deep Learning sample programs using PyTorch in C++

A Tensorfflow implementation of Attend, Infer, Repeat

Assessing Generative Models via Precision and Recall (official repository)

Implementation of a convolutional Variational-Autoencoder model in pytorch.

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

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.

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

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

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

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

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

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

Invariant representation learning from imaging and spectral data

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

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

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

Pytorch implementation of Hyperspherical Variational Auto-Encoders

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

Collection of generative models in Tensorflow

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

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

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

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

Stochastic Adversarial Video Prediction

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

State Representation Learning (SRL) zoo with PyTorch - Part of S-RL Toolbox

Advanced Deep Learning with Keras, published by Packt

Machine learning, in numpy

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

No description or website provided.

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

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

Pytorch implementation of Block Neural Autoregressive Flow

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

Tensorflow implementation of adversarial auto-encoder for MNIST

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

PyTorch implementation of "Auto-Encoding Variational Bayes"

Protein function prediction using a variational autoencoder

Experiments with Adversarial Autoencoders using Keras

Learning about Haskell with Variational Autoencoders

music generation with a classifying variational autoencoder (VAE) and LSTM

AE and VAE Playground in PyTorch

Experiments for understanding disentanglement in VAE latent representations

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

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

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

TensorFlow and Deep Learning Tutorials

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

Shared Latent Space VAE's

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

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

Pharmaceutical Modeling and Simulation for Nonlinear Mixed Effects (NLME), Quantiative Systems Pharmacology (QsP), Physiologically-Based Pharmacokinetics (PBPK) models mixed with machine learning

PyTorch implementation of the Factorized TDNN (TDNN-F) from "Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks" and Kaldi