4 citations · 5 across the 9 of their papers we have counts for
10 papers
Metrics for Bayesian Optimal Experiment Design under Model Misspecification
Tommie A. Catanach, Niladri Das
The conventional approach to Bayesian decision-theoretic experiment design involves searching over possible experiments to select a design that maximizes the expected value of a sp…
Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions
Niladri Das, Jed A. Duersch, Thomas A. Catanach
In this paper, we address the problem of convergence of sequential variational inference filter (VIF) through the application of a robust variational objective and Hinf-norm based…
Optimal Sensor Precision for Multi-Rate Sensing for Bounded Estimation Error
Niladri Das, Raktim Bhattacharya
We address the problem of determining optimal sensor precisions for estimating the states of linear time-varying discrete-time stochastic dynamical systems, with guaranteed bounds…
Modeling and Optimal Control of Hybrid UAVs with Wind Disturbance
Sunsoo Kim, Niladri Das, Raktim Bhattacharya
This paper addresses modeling and control of a six-degree-of-freedom unmanned aerial vehicle capable of vertical take-off and landing in the presence of wind disturbances. We desig…
Utility and Privacy in Object Tracking from Video Stream using Kalman Filter
Niladri Das, Raktim Bhattacharya
Tracking objects in Computer Vision is a hard problem. Privacy and utility concerns adds an extra layer of complexity over this problem. In this work we consider the problem of mai…
Combining Visible and Infrared Spectrum Imagery using Machine Learning for Small Unmanned Aerial System Detection
Vinicius G. Goecks, Grayson Woods, John Valasek
Advances in machine learning and deep neural networks for object detection, coupled with lower cost and power requirements of cameras, led to promising vision-based solutions for s…