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Found 4 papers, 2 papers with code
Automated Dynamic Bayesian Networks for Predicting Acute Kidney Injury Before Onset
In this paper, we introduce Ranking Approaches for Unknown Structures (RAUS), an automated framework to systematically inform variable ordering and learn networks end-to-end.
Machine Learning Integrated with Model Predictive Control for Imitative Optimal Control of Compression Ignition Engines
One solution is the use of machine learning (ML) and model predictive control (MPC) to minimize emissions and fuel consumption, without adding substantial computational cost to the engine controller.
Deep Learning based Model Predictive Control for Compression Ignition Engines
Machine learning (ML) and a nonlinear model predictive controller (NMPC) are used in this paper to minimize the emissions and fuel consumption of a compression ignition engine.
The Myths of Our Time: Fake News
While the purpose of most fake news is misinformation and political propaganda, our team sees it as a new type of myth that is created by people in the age of internet identities and artificial intelligence.
