Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"

The official code repo for the paper "Mixture of Stochastic Experts for Modeling Aleatoric Uncertainty in Segmentation". (ICLR 2023)

On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians

Official repository for the paper "ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography" in MICCAI 2023 Conference

"A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?" (CVPR 2024)

Work as part of ANL summer 2020 research on uncertainity quanitification methods in graph neural networks

Energy production forecasting ⚡ with PoC of Bayesian Neural Network 🎲

Code for the ICASSP'19 submission "Modelling Sample Informativeness for Deep Affective Computing".

Generalized Automatic Pipeline for inspecting and fixing uncertainties in your data

Experiments with lossy Bayesian inference.