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Found 5 papers, 1 papers with code
What Makes a Good Dataset for Symbol Description Reading?
The usage of mathematical formulas as concise representations of a document's key ideas is common practice.
A monitoring framework for deployed machine learning models with supply chain examples
We use our implementation to study drift in model features, predictions, and performance on three real data sets.
Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks
The transition away from carbon-based energy sources poses several challenges for the operation of electricity distribution systems.
Scalable Deployment of AI Time-series Models for IoT
A knowledge-based approach to managing model and time-series data allows the use of general semantic concepts for expressing feature engineering tasks.
Castor: Contextual IoT Time Series Data and Model Management at Scale
The main features of Castor are: (1) an efficient pipeline for ingesting IoT time series data in real time; (2) a scalable, hybrid data management service for both time series and contextual data; (3) a versatile semantic model for contextual information which can be easily adopted to different application domains; (4) an abstract framework for developing and storing predictive models in R or Python; (5) deployment services which automatically train and/or score predictive models upon user-defined conditions.
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