#Variational-inference
Showing 21 of 21 repositories tagged #variational-inference, ranked by stars
SoftVC VITS Singing Voice Conversion
Bayesian Modeling and Probabilistic Programming in Python
Deep universal probabilistic programming with Python and PyTorch
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Gaussian processes in TensorFlow
Awesome resources on normalizing flows.
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
PyTorch implementation of normalizing flow models
Boltzmann Machines in TensorFlow with examples
A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
Kalman Variational Auto-Encoder
PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations
🍓 Build and train energy-based and diffusion models in PyTorch ⚡.
IVON optimizer for neural networks based on variational learning.
Bayesian dessert for Lasagne
Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
A collection of Methods and Models for various architectures of Artificial Neural Networks
An experiment in VAE-based artistic style transfer by embedding fiddling.