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Found 2 papers, 1 papers with code
Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization
In this article, we systematically examine the technique of adding noise to the ML model input during training to promote stability and improve prediction accuracy.
Parallel Machine Learning for Forecasting the Dynamics of Complex Networks
Forecasting the dynamics of large complex networks from previous time-series data is important in a wide range of contexts.
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