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Found 4 papers, 2 papers with code
A probabilistic estimation of remaining useful life from censored time-to-event data
Our work encourages the inclusion of censored data in predictive maintenance models and highlights the unique advantages that survival analysis offers when it comes to probabilistic RUL estimation and early fault detection.
A lite parametric model for the Hemodynamic Response Function
When working with task-related fMRI data, one of the most crucial parts of the data analysis consists of determining a proper estimate of the BOLD response.
Unsupervised learning of the brain connectivity dynamic using residual D-net
In this paper, we propose a novel unsupervised learning method to learn the brain dynamics using a deep learning architecture named residual D-net.
Information Assisted Dictionary Learning for fMRI data analysis
The new method allows the incorporation of a priori knowledge associated both with the experimental design as well as with available brain Atlases.
