Bayesian Modeling and Probabilistic Programming in Python
#计算机科学#Deep universal probabilistic programming with Python and PyTorch
#计算机科学#Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
#计算机科学#Gaussian processes in TensorFlow
#Awesome#Awesome resources on normalizing flows.
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
#学习与技能提升#Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
#计算机科学#Seminars DeepBayes Summer School 2018
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
PyTorch implementation of normalizing flow models
#计算机科学#Boltzmann Machines in TensorFlow with examples
#Awesome#A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
[NeurIPS 2022] Denoising Diffusion Restoration Models -- Official Code Repository
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Statistical Rethinking (2nd ed.) with NumPyro
#自然语言处理#DGMs for NLP. A roadmap.
#计算机科学#Julia package for automated Bayesian inference on a factor graph with reactive message passing
Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important ...