Quantifying The Uncertainty In Model Predictions

Neural networks are infamous for making wrong

Calibration has emerged as a standard approach to

Predictions

This paper takes a fully probabilistic approach by

Gaussian process regression (GPR) is a probabilistic approach to making

BGC Webinar – July 28, 2020 Title:

We introduce the problem of conformal

Title:

In this SEI Podcast, Dr. Eric Heim, a senior machine learning research scientist at the Software Engineering Institute at Carnegie ...

Channel's GitHub page hosting Jupyter Notebook: https://github.com/mtorabirad/MLBoost In this video, we explore the concept of ...

This video tutorial on conformal

https://arxiv.org/abs/2203.07472 A short video on what the above paper discusses: -

Introduction to the class and marginal mean consistency.

A quick 20 min introduction to various UQ methods for Deep Learning:- - Why is UQ required for Deep Learning - Bayesian NN ...

One of the main goals of statistics is to help make

Machine/Deep learning

Published at ICRA 2023 arxiv version: https://arxiv.org/abs/2305.20044.

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

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