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A tailored Graph Neural Network architecture with Differential Privacy guarantees for both training and inference.
Current solutions to legal translation are based on machine learning techniques. Such techniques are based on statistics and always exhibit a margin of error. In addition, machine learning, which is based on data and algorithms, is by definition unethical...
In the domains of aeronautics, automotive, energy, manufacturing and retail, Munich Innovation Hub for Applied AI proposes novel solutions to counter the complexity and dependability challenges resulting from distributed accountability, the need for more ...
Descriptive and predictive analytics for manufacturing legacy and operational data related to maintenance, delivering insights on critical manufacturing operations.
Dezyne is a programming language and a set of tools to specify, validate, verify, simulate, document, and implement concurrent control software for embedded and cyber-physical systems.
Data preprocessing, Feature Engineering, Model Development, Evaluation & Selection for Predictive Maintenance in Manufacturing.
Federated training of Graph Neural Networks (GNNs) with Local Differential Privacy
A data set of 1.8 billion measurements from a mechanical wrist with three axes that can hold tools, for example, for spray painting in combination with a pump. The data set spans six months in 1-second intervals.
A data set of 380 million measurements from a hydraulic pump that can be mounted on an industrial robot, for example, to pump liquid paint for spray painting. The data set spans two months in 1-second intervals.
This repository contains the base components necessary to bootstrap your own Constraint Object-Oriented Logic Action Programming as a Service (COOLAPS) application docker container.