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Found 3 papers, 2 papers with code
Discovering ordinary differential equations that govern time-series
Natural laws are often described through differential equations yet finding a differential equation that describes the governing law underlying observed data is a challenging and still mostly manual task.
Curiously Effective Features for Image Quality Prediction
The performance of visual quality prediction models is commonly assumed to be closely tied to their ability to capture perceptually relevant image aspects.
Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals
Interpretability of deep neural networks is a recently emerging area of machine learning research targeting a better understanding of how models perform feature selection and derive their classification decisions.
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