Paper: Computer model calibration as a method for design
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Updated
Jan 21, 2021 - TeX
Paper: Computer model calibration as a method for design
MCMC for Uncertainty Quantification
Research on Entity Matching Problem
Code for the paper "Stochastic analysis of the electromagnetic induction effect on a neuron's action potential dynamics"
Uncertainty quantification fo ML - collection of scripts, tutorials and templates
Bayesian neural networks in PyTorch
Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery
Official code of the ICML24 paper: "Winner-takes-all learners are geometry-aware conditional density estimators"
Uncertainty Quantification Management System
Code for Connection between Uncertainty Quantification and Gaussian Prior Parameters
Uncertainty Quantification in python using Monte-Carlo simulation
Uncertainty Quantification for Physical and Biological Models
Reproducible experiments conducted in the paper 'Uncertainty Quantification in Anomaly Detection with Cross-Conformal p-Values'.
A Julia package for the computation of hard, theoretically guaranteed bounds on the moments of jump-diffusion processes with polynomial data
Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery
An infrastructure resilience web application to integrate graph neural networks (GNNs) for GIS visualization.
The Matlab tool for Prediction Uncertainty Analysis (PUA) integrates Profile Likelihood analysis with Bayesian sampling.
Showcasing the computation of the concentration-information bounds for the bias of an observable.
Code for ''Understanding and Exploring the Network with Stochastic Architectures''
Repository for the paper "Inferring Structural Parameters of Low-Surface-Brightness-Galaxies with Uncertainty Quantification using Bayesian Neural Networks", accepted in the 2022 ICML workshop on "Machine Learning for Astrophysics"
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