89 citations · 112 across the 19 of their papers we have counts for
5 papers · 1 filter
Resource-Efficient Distributed Recursive Gaussian Processes
Josephine King, Ali Emre Balci, Raj Thilak Rajan
Gaussian processes (GPs) provide a flexible framework for learning unknown functions from noisy measurements while quantifying predictive uncertainty, making them well suited for e…
Distributed Target Tracking using Radar Networks
Shao-Hsuan Hung, Raj Thilak Rajan
Distributed target tracking is essential for scalable and robust sensing systems, as it enables multiple radar nodes to cooperatively estimate a target state without relying on a c…
Consensus-based Recursive Multi-Output Gaussian Process
Yogesh Prasanna Kumar Rao, Tamas Keviczky, Raj Thilak Rajan
Multi-output Gaussian Processes provide principled uncertainty-aware learning of vector-valued fields but are difficult to deploy in large-scale, distributed, and streaming setting…
Multicluster Design and Control of Large-Scale Affine Formations
Zhonggang Li, Geert Leus, Raj Thilak Rajan
Conventional affine formation control (AFC) empowers a network of agents with flexible but collective motions - a potential which has not yet been exploited for large-scale swarms.…
A Covariance Matching Approach to Graph Topology Identification
Yongsheng Han, Raj Thilak Rajan, Geert Leus
Graph topology identification (GTI) is a central challenge in networked systems, where the underlying structure is often hidden, yet nodal data are available. Conventional solution…