Learning Latent Wireless Dynamics From Channel State Information
In this work, we propose a novel data-driven ml technique to model and predict the dynamics of the wireless propagation environment in […]
Lessons From 3 Longitudinal Sensor-Based Human Behavior Assessment Field Studies and an Approach to Support Stakeholder Management: Content Analysis
Background: Pervasive technologies are used to investigate various phenomena outside the laboratory setting, providing valuable insights into real-world human behavior and interaction […]
A Multi-Task Oriented Semantic Communication Framework for Autonomous Vehicles
Task-oriented semantic communication is an emerging technology that transmits only the relevant semantics of a message instead of the whole message to […]
Revisiting Edge AI: Opportunities and Challenges
Edge artificial intelligence (AI) is an innovative computing paradigm that aims to shift the training and inference of machine learning models to […]
Waveform Learning under Phase Noise Impairment for Sub-THz Communications
The large untapped spectrum in sub-THz allows for ultra-high throughput communication to realize many seemingly impossible applications in 6G. Phase noise (PN) […]
RIS Phase Optimization via Generative Flow Networks
This letter introduces a new Machine Learning (ML) technique to learn phase shifting patterns for Reconfigurable Intelligent Surfaces (RISs). We leverage the […]
Non-contact multimodal indoor human monitoring systems: A survey
Indoor human monitoring systems are integral in various applications. They leverage a wide range of sensors, including cameras, radio devices, and inertial […]
RIS Phase Optimization via Generative Flow Networks
This letter introduces a new Machine Learning (ML) technique to learn phase shifting patterns for Reconfigurable Intelligent Surfaces (RISs). We leverage the […]
Non-contact multimodal indoor human monitoring systems: A survey
Indoor human monitoring systems are integral in various applications. They leverage a wide range of sensors, including cameras, radio devices, and inertial […]
Coupling machine learning and physical modelling for predicting runoff at catchment scale
In this paper, we present an approach that combines data-driven and physical modelling for predicting the runoff occurrence and volume at catchment […]