712 Open source projects that are alternatives of or similar to precision-recall-distributions

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

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

No description or website provided.

Collection of generative models in Tensorflow

Stochastic Adversarial Video Prediction

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

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

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

Protein function prediction using a variational autoencoder

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

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

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

Invariant representation learning from imaging and spectral data

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

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

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.

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

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

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

Tensorflow implementation of conditional variational auto-encoder for MNIST

Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.

PyTorch study

No description or website provided.

A toolbox for differentially private data generation

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

TextBox is an open-source library for building text generation system.

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

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

Tensorflow implementation of adversarial auto-encoder for MNIST

Repository for implementation of generative models with Tensorflow 1.x

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Ladder Variational Autoencoders (LVAE) 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.

Pytorch implementation of Hyperspherical Variational Auto-Encoders

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

Tensorflow implementation of variational auto-encoder for MNIST

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

PyTorch implementation of "Auto-Encoding Variational Bayes"

Experiments for understanding disentanglement in VAE latent representations

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

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

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!

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

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

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

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

Lagrangian VAE

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

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

Focal Frequency Loss for Generative Models

Deep generative models implemented with TensorFlow 2.0: eg. Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Deep Boltzmann Machine (DBM), Convolutional Variational Auto-Encoder (CVAE), Convolutional Generative Adversarial Network (CGAN)

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

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

PySODEvalToolkit: A Python-based Evaluation Toolbox for Salient Object Detection and Camouflaged Object Detection

Useful python NLP tools (evaluation, GUI interface, tokenization)

A Simple Math and Pseudo C# Expression Evaluator in One C# File. Can also execute small C# like scripts

EfficientMORL (ICML'21)

ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite