IEEE

Structured Sparse Regularization-Based Deep Fuzzy Networks for RNA N6-Methyladenosine Sites Prediction

Abstract: In many biological processes, N6-methyladenosine (m6A) plays a critical role. Experimental methods for identifying m6A sites have proven to be costly, and existing computational methods ...
AZoCleantech on MSN

New framework for predicting TAIs in hydrogen combustion

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...
Opinion
Learn With Jay on MSNOpinion

Deep learning regularization: Prevent overfitting effectively explained

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...
IEEE

Cyclic Regularization of Input Convex Neural Networks for Robust Voltage Regulation

Abstract: Traditional centralized voltage regulation in distribution grids is typically formulated using the DistFlow model, which requires complete system knowledge, including topology and line ...