activity
20182022
most citedKalman Filter Tuning with Bayesian Optimization

10 citations · 17 across the 5 of their papers we have counts for

collaborators

7 papers

cs.AI20224 cited

A Factor-Based Framework for Decision-Making Competency Self-Assessment

Brett W. Israelsen, Nisar Ahmed

We summarize our efforts to date in developing a framework for generating succinct human-understandable competency self-assessments in terms of machine self confidence, i.e. a robo…

eess.SY2021

Time Dependence in Kalman Filter Tuning

Zhaozhong Chen, Christoffer Heckman, Simon Julier +1

In this paper, we propose an approach to address the problems with ambiguity in tuning the process and observation noises for a discrete-time linear Kalman filter. Conventional app…

cs.LG20202 cited

Explaining Conditions for Reinforcement Learning Behaviors from Real and Imagined Data

Aastha Acharya, Rebecca Russell, Nisar R. Ahmed

The deployment of reinforcement learning (RL) in the real world comes with challenges in calibrating user trust and expectations. As a step toward developing RL systems that are ab…

cs.LG2020

In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems

Michael L. Iuzzolino, Tetsumichi Umada, Nisar R. Ahmed +1

We investigate how different active learning (AL) query policies coupled with classification uncertainty visualizations affect analyst trust in automated classification systems. A…

eess.SY201910 cited

Kalman Filter Tuning with Bayesian Optimization

Zhaozhong Chen, Nisar Ahmed, Simon Julier +1

Many state estimation algorithms must be tuned given the state space process and observation models, the process and observation noise parameters must be chosen. Conventional tunin…

eess.SP20191 cited

Decentralized Gaussian Mixture Fusion through Unified Quotient Approximations

Nisar R. Ahmed

This work examines the problem of using finite Gaussian mixtures (GM) probability density functions in recursive Bayesian peer-to-peer decentralized data fusion (DDF). It is shown…