activity
20122023
most citedReliable Neural Networks for Regression Uncertainty Estimation

22 citations · 105 across the 15 of their papers we have counts for

collaborators

15 papers

physics.data-an2023

Inferential Moments of Uncertain Multivariable Systems

Kevin Vanslette

This article expands the framework of Bayesian inference and provides direct probabilistic methods for approaching inference tasks that are typically handled with information theor…

cs.LG2021★ 22 cited

Reliable Neural Networks for Regression Uncertainty Estimation

Tony Tohme, Kevin Vanslette, Kamal Youcef-Toumi

While deep neural networks are highly performant and successful in a wide range of real-world problems, estimating their predictive uncertainty remains a challenging task. To addre…

stat.ME2019★ 21 cited

A Generalized Bayesian Approach to Model Calibration

Tony Tohme, Kevin Vanslette, Kamal Youcef-Toumi

In model development, model calibration and validation play complementary roles toward learning reliable models. In this article, we expand the Bayesian Validation Metric framework…

stat.CO2019

Vectorized Uncertainty Propagation and Input Probability Sensitivity Analysis

Kevin Vanslette, Arwa Alanqari, Zeyad Al-awwad +1

In this article we construct a theoretical and computational process for assessing Input Probability Sensitivity Analysis (IPSA) using a Graphics Processing Unit (GPU) enabled tech…

stat.ME2019★ 11 cited

A General Model Validation and Testing Tool

Kevin Vanslette, Tony Tohme, Kamal Youcef-Toumi

We construct and propose the "Bayesian Validation Metric" (BVM) as a general model validation and testing tool. We find the BVM to be capable of representing all of the standard va…

math.ST2019★ 3 cited

Why Simple Quadrature is just as good as Monte Carlo

Kevin Vanslette, Abdullatif Al Alsheikh, Kamal Youcef-Toumi

We motive and calculate Newton--Cotes quadrature integration variance and compare it directly with Monte Carlo (MC) integration variance. We find an equivalence between determinist…

cs.IT2019★ 3 cited

The Design of Global Correlation Quantifiers and Continuous Notions of Statistical Sufficiency

Nicholas Carrara, Kevin Vanslette

Using first principles from inference, we design a set of functionals for the purposes of \textit{ranking} joint probability distributions with respect to their correlations. Start…

quant-ph2018★ 4 cited

The Inferential Design of Entropy and its Application to Quantum Measurements

Kevin Vanslette

This thesis synthesizes probability and entropic inference with Quantum Mechanics (QM) and quantum measurement [1-6]. It is shown that the standard and quantum relative entropies a…

quant-ph2017★ 1 cited

A Multiple Observer Probability Analysis for Bell Scenarios in Special Relativity

Kevin Vanslette

Here we present a Multiple Observer Probability Analysis (MOPA) for the purpose of clarifying topics in experimental Bell scenarios. Because Bell scenarios are interested in quantu…

quant-ph2017

The Quantum Bayes Rule and Generalizations from the Quantum Maximum Entropy Method

Kevin Vanslette

The recent article "Entropic Updating of Probability and Density Matrices" [1] derives and demonstrates the inferential origins of both the standard and quantum relative entropies…

quant-ph2017★ 19 cited

Entropic Updating of Probability and Density Matrices

Kevin Vanslette

We find that the standard relative entropy and the Umegaki entropy are designed for the purpose of inferentially updating probability and density matrices respectively. From the sa…

quant-ph2017★ 1 cited

Entropic Dynamics: A hybrid-contextual theory of Quantum Mechanics

Kevin Vanslette

The Bell-KS theorem and the more recent -epistemic \emph{no-go} theorems of QM are discussed in the context of Entropic Dynamics. In doing so we find that the Bell-KS theorem al…

quant-ph2017★ 19 cited

Quantum Measurement and Weak Values in Entropic Dynamics

Kevin Vanslette, Ariel Caticha

The problem of measurement in quantum mechanics is studied within the Entropic Dynamics framework. We discuss von Neumann and Weak measurements, wavefunction collapse, and Weak Val…

quant-ph2016★ 1 cited

How Kirkwood and Probability Distributions Differ: A Coxian Perspective

Kevin Vanslette

Kolmogorov's first axiom of probability is probability takes values between 0 and 1; however, in Cox's derivation of probability having a maximum value of unity is arbitrary since…

physics.gen-ph2012

Theoretical Study of Variable Measurement Uncertainty and Infinite Unobservable Entropy

Kevin Vanslette

This paper examines the statistical mechanical and thermodynamical consequences of variable phase-space volume element . Varying lea…