Bayesian inference with probabilistic programming.

Studies on Bayesian Neural Networks with application cases

A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors paper presented @ICLR2024

Code accompanying ICLR 2024 paper "Function-space Parameterization of Neural Networks for Sequential Learning"

This repository contains code and resources for my thesis project on uncertainty estimation in computed tomography (CT) scan modeling. Explore Bayesian and deterministic neural network architectures for CT analysis and compare their effectiveness in quantifying uncertainty.

Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning

Bayesian Neural Network in PyTorch

Optimized Bayesian Neural Network C library for integer only inference in embedded RISC-V Cores

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

PyTorch implementation of Sparse Function-space Representation of Neural Networks

Awesome resources on normalizing flows.

On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks

Gaussian Processes for Experimental Sciences

General-purpose library for fitting models to data with correlated Gaussian-distributed noise

This repository contains our work for the validation project of the course Bayesian Machine Learning, 2023/2024, ENS Paris-Saclay, Master MVA. It consists in a thorough study of the paper "Challenges in Markov chain Monte Carlo for Bayesian neural networks" by Theodore Papamarkou et al.

Open Source Photometric classification https://supernnova.readthedocs.io

Repo for my thesis research development at UC Riverside: "Classifying Galaxy Morphologies Using Bayesian Neural Networks for LSST"

Official TensorFlow implementation of Uncertainty Estimation in Deep Bayesian Survival Models (BHI 2023)

my blog

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch