Uncertainty Quantification Machine Learning

Quantifying the Uncertainty in Model Predictions

Neural networks are infamous for making wrong predictions with high confidence. Ideally, when a model encounters difficult ...

Mojtaba Farmanbar - Uncertainty quantification: How much can you trust your machine learning model?

www.pydata.org

Easy introduction to gaussian process regression (uncertainty models)

Gaussian process regression (GPR) is a probabilistic approach to making predictions. GPRs are easy to implement, flexible, and ...

Introduction to Uncertainty Quantification for Deep Learning

A quick 20 min introduction to various UQ methods for Deep

What is Uncertainty Quantification (UQ)?

A brief overview of

Uncertainty Quantification & Machine Learning

2025 ML Academy & Artiste Distinguished Lecture.

Uncertainty Quantification in Machine Learning: Measuring Confidence in Predictions

In this SEI Podcast, Dr. Eric Heim, a senior

Uncertainty Quantification and Deep Learning ǀ Elise Jennings, Argonne National Laboratory

Presented at the Argonne Training Program on Extreme-Scale Computing 2019. Slides for this presentation are available here: ...

Uncertainty quantification in machine learning and nonlinear least squares regression models

This is a quick video brief on a new paper published by Ni Zhan and myself on

AIC: Uncertainty Quantification in Machine Learning: From Aleatoric to Epistemic

Speaker: Professor Eyke Hüllermeier (LMU) Titel:

Uncertainty (Aleatoric vs Epistemic) | Machine Learning

Machine

Uncertainty Quantification (1): Enter Conformal Predictors

... we explore the concept of

Lalitha Venkataramanan: "Uncertainty Quantification in Machine Learning" | IACS Seminar

Presented by Lalitha Venkataramanan, Scientific Advisor at Schlumberger. Abstract: Deep

Bayesian Mathematics | Probabilistic Programming & Uncertainty Quantification in AI | Lecture No 29

Welcome to The

Using machine learning & uncertainty quantification to tackle data in high-res disaster simulations

NYU CUSP's Research Seminar Series features leading voices in the growing field of urban informatics. Check out upcoming ...

Mini Tutorial 6: An Introduction to Uncertainty Quantification for Modeling & Simulation

Predictions from modeling and simulation (M&S) are increasingly relied upon to inform critical decision making in a variety of ...

Uncertainty Quantification for Large Language Models (LLMs)

This paper takes a fully probabilistic approach by modeling the joint distribution over questions and inputs, defining

Arka Daw - Uncertainty Quantification with Physics-informed Machine Learning

As applications in deep