Abstract: As PV systems become more integrated into power grids, challenges arise in optimizing power flow and maintaining stability amid fluctuating load conditions. Variations in solar energy output ...

The Layer-wise Relevance Propagation (LRP) algorithm explains a classifer's prediction specific to a given data point by attributing relevance scores to important components of the input by using the ...

Python has grown in popularity over the years to become one of the most popular programming languages for machine learning (ML) and artificial intelligence (AI) tasks. It has replaced many of the ...

We demonstrate that a neural network automatically solves, explains, and generates university-level problems from the largest Massachusetts Institute of Technology (MIT) mathematics courses at a human ...

We present a theory of neural circuits’ design and function, inspired by the random connectivity of real neural circuits and the mathematical power of random projections. Specifically, we introduce a ...

Deep learning neural networks are especially potent at dealing with structured data, such as images and volumes. Both modified LiviaNET and HyperDense-Net performed well at a prior competition ...

Wesfeiler-Lehman Neural Machine (WLNM) is a subgraph-based link prediction method leveraging deep learning to automatically learn graph structure features for link ...

Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed ...