JEC

Embracing random variability for more robust designs

In engineering design, the traditional “deterministic” modelling approach assumes fixed values for loads, material properties ...
Microsoft

Roadmap to fault tolerant quantum computation using topological qubit arrays

We describe a concrete device roadmap towards a fault-tolerant quantum computing architecture based on noise-resilient, topologically protected Majorana-based qubits. Our roadmap encompasses four ...
IEEE

Distributed Least Mean Square Estimation With Communication Noises Over Random Graphs

Abstract: For the online distributed estimation problem of time-varying parameters, we study a linear regression model with measurement noises over time-varying random graphs. We propose a distributed ...
Frontiers

SSEL: spike-based structural entropic learning for spiking graph neural networks

1 School of Electrical Automation and Information Engineering, Tianjin University, Tianjin, China 2 National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, National Engineering ...
IEEE

Distributed Graph Learning From Smooth Data: A Bayesian Framework

Abstract: The emerging field of graph learning, which aims to learn reasonable graph structures from data, plays a vital role in Graph Signal Processing (GSP) and finds applications in various data ...