Deep learning through evolution: A hybrid approach to scheduling in a dynamic environment
Deep learning through evolution: A hybrid approach to scheduling in a dynamic environment
Co-Design of Embeddable Diagnostics using Reduced-Order Models**The paper has been supported by SFI grants 12/RC/2289 and 13/RC/2094
A Coinductive Equational Characterisation of Trace Inclusion for Regular Processes
Collaborative Economies: From Sharing to Caring
Comparing Switching and Mixing Model-Predictive Controllers for Robust Fault-Tolerant Control
Competition-Based Crowdsourcing Software Development: A Multi-Method Study from a Customer Perspective
ComProSe: Shaping Future Public Safety Communities with ProSe-Based UAVs
Configuring Dynamic Heterogeneous Wireless Communications Networks Using a Customised Genetic Algorithm
Connecting Multistakeholder Analysis across Connected Health Solutions
Context-dependent reconfiguration of autonomous vehicles in mixed traffic