Pinned Repositories
Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
BayesianNeuralNets
Bayesian neural networks in PyTorch
bayesianNN
Implementing a bayesian neural network in TensorFlow
BDA-exercises
My solutions to exercises from avehtari Baesyan Data Analysis course
BDA_course_Aalto
Bayesian Data Analysis course at Aalto
BDA_R_demos
Bayesian Data Analysis demos for R
blitz-bayesian-deep-learning
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
BMR
Bayesian Macroeconometrics in R
bnn
Bayesian Neural Network in PyTorch
bvar
Toolkit for the estimation of hierarchical Bayesian vector autoregressions. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015). Allows for the computation of impulse responses and forecasts and provides functionality for assessing results.
vie2bgd's Repositories
vie2bgd/Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
vie2bgd/BayesianNeuralNets
Bayesian neural networks in PyTorch
vie2bgd/bayesianNN
Implementing a bayesian neural network in TensorFlow
vie2bgd/BDA-exercises
My solutions to exercises from avehtari Baesyan Data Analysis course
vie2bgd/BDA_course_Aalto
Bayesian Data Analysis course at Aalto
vie2bgd/BDA_R_demos
Bayesian Data Analysis demos for R
vie2bgd/blitz-bayesian-deep-learning
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
vie2bgd/BMR
Bayesian Macroeconometrics in R
vie2bgd/bnn
Bayesian Neural Network in PyTorch
vie2bgd/bvar
Toolkit for the estimation of hierarchical Bayesian vector autoregressions. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015). Allows for the computation of impulse responses and forecasts and provides functionality for assessing results.
vie2bgd/bvarrKK
Translation Of Koop And Korobilis BVAR Matlab Code Into R
vie2bgd/bvars
R package for Bayesian Vector Autoregression
vie2bgd/bvartools
Functions for Bayesian inference of vector autoregressive models
vie2bgd/DeepTimeSeriesModel
A paper list for Time series modelling, including prediciton and anomaly detection
vie2bgd/DUN
Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
vie2bgd/gaussian_processes
vie2bgd/Master-Thesis-BayesianCNN
Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
vie2bgd/ocbnn-public
General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
vie2bgd/probflow
A Python package for building Bayesian models with TensorFlow or PyTorch
vie2bgd/PyTorch-BayesianCNN
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
vie2bgd/quantregForest
R package - Quantile Regression Forests, a tree-based ensemble method for estimation of conditional quantiles (Meinshausen, 2006).
vie2bgd/Turing.jl
Bayesian inference with probabilistic programming.
vie2bgd/uncertainty-toolbox
A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization