231 Open source projects that are alternatives of or similar to Kvae

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

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..

Understanding normalizing flows

Using neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)

Tensorflow implementation of conditional variational auto-encoder for MNIST

Learning about Haskell with Variational Autoencoders

PyTorch implementation of normalizing flow models

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

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

We got a stew going!

Lagrangian VAE

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

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Boltzmann Machines in TensorFlow with examples

Next RecSys Library

Deep Recurrent Generative Decoder for Abstractive Text Summarization in DyNet

Some Python Implementations of the Kalman Filter

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).

The original implementation of the models and experiments of Variational Deep Semantic Hashing paper (SIGIR 2017)

Lecture notes on Bayesian deep learning

Tensorflow implementation of variational auto-encoder for MNIST

Python Kalman filters vectorized as Single Instruction, Multiple Data

Modular Probabilistic Programming on MXNet

Variational Autoencoder with Recurrent Neural Network based on Google DeepMind's "DRAW: A Recurrent Neural Network For Image Generation"

数学知识点滴积累 矩阵 数值优化 神经网络反向传播 图优化 概率论 随机过程 卡尔曼滤波 粒子滤波 数学函数拟合

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

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

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

solution of exercises of the book "probabilistic robotics"

Protein function prediction using a variational autoencoder

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

Multiple Object Tracker, Based on Hungarian algorithm + Kalman filter.

Robotics Toolbox for MATLAB

This package includes basic tools for time series analysis, compatible with incomplete data.

Deep probabilistic analysis of single-cell omics data

Loosely coupled integration of GNSS and IMU

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Seminars DeepBayes Summer School 2018

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)

Collection of generative models in Tensorflow

GPstuff - Gaussian process models for Bayesian analysis

Experiments for understanding disentanglement in VAE latent representations

Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019

Variational autoencoders for collaborative filtering

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

Mad Location Manager is a library for GPS and Accelerometer data "fusion" with Kalman filter

Udacity Self-Driving Car Engineer Nanodegree. Project: Extended Kalman Filters

Collection of notebooks about quantitative finance, with interactive python code.

An in-depth step-by-step tutorial for implementing sensor fusion with robot_localization! 🛰

Codera Quant is a Java framework for algorithmic trading strategies development, execution and backtesting via Interactive Brokers TWS API or other brokers API

Simple implementation of Variational Autoencoder

A VAE written entirely in Numpy/Cupy

Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)

Javascript based Kalman filter for 1D data

Deep universal probabilistic programming with Python and PyTorch

Tensorflow Implementation of Knowledge-Guided CVAE for dialog generation ACL 2017. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU

Adversarial Imitation Via Variational Inverse Reinforcement Learning

Lightweight Python library for adding real-time 2D object tracking to any detector.