Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis
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This work presents the application of a probabilistic approach to an already existing deep learning model for weather and climate prediction. Probabilistic deep learning allows to capture and address the uncertainties related to the data given as input and ...
Increasing demand for new infrastructure and ageing of existing infrastructure has made management of infrastructure a key challenge of this century. Replacement of all ageing civil infrastructure is economically and environmentally unsustainable. Civil in ...
For many developed countries, the asset management of aging infrastructure continues to present challenges and risks. Around the world, built-environment assets such as bridges, require functional changes and future-proofing in order to accommodate new and ...
Building utilization can be enhanced by tracking occupants. Non-intrusive tracking of occupants using floor-vibration measurements is beneficial for many smart-building applications such as energy consumption, security enhancement, and care-giving. Also, u ...
The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...
In this paper, we explore various approaches for semi-
supervised learning in an end-to-end automatic speech recog-
nition (ASR) framework. The first step in our approach in-
volves training a seed model on the limited amount of labelled
data. Additional u ...
Model-based data interpretation has the potential to increase knowledge of structural behavior and support asset management. Models are usually conservative and contain many parameters and sources of systematic uncertainty, which need to be taken into acco ...
From the moment we wake up in the morning to the day's ebb when we settle in to sleep, we are bound to the task of decision-making. Some of these decisions barely register in our consciousness, if at all, while others, less shy, take a more prominent place ...
Model-based data-interpretation techniques are increasingly used to improve the knowledge of complex system behavior. Physics-based models that are identified using measurement data are generally used for extrapolation to predict system behavior under othe ...
In wireless sensor networks, various applications involve learning one or multiple functions of the measurements observed by sensors, rather than the measurements themselves. This paper focuses on the class of type-threshold functions, e.g., the maximum an ...
Institute of Electrical and Electronics Engineers2015