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Found 3 papers, 2 papers with code
Data Augmentation on Graphs: A Technical Survey
In recent years, graph representation learning has achieved remarkable success while suffering from low-quality data problems.
Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition
To address this issue, in this work, we proposed a Behaviour Pattern Disentanglement (BPD) framework, which can disentangle the behavior patterns from the irrelevant noises such as personal styles or environmental noises, etc.
Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey
Machine Learning (ML) and Internet of Things (IoT) are complementary advances: ML techniques unlock complete potentials of IoT with intelligence, and IoT applications increasingly feed data collected by sensors into ML models, thereby employing results to improve their business processes and services.
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