This important study demonstrates the significance of incorporating biological constraints in training neural networks to develop models that make accurate predictions under novel conditions. By ...

Bohai Bay Basin, River Facies, Reservoir Description, Genetic Inversion, Natural Gamma Share and Cite: Wang, S.-P., Yang, W.

The melting point (MP) of a chemical is an important physicochemical property that characterizes the transition from a solid to a liquid state. The MP is a key parameter in molecular design and ...

This repository is the open source code for my latest work: "Through-the-Wall Radar Human Activity Recognition WITHOUT Using Neural Networks", submitted to arXiv. Fig. 1. Current works in this field ...

Data-driven deep learning techniques have made notable advancements in modeling electromagnetic scattering problems. However, its accuracy on the testing dataset can be heavily reduced when data ...

Predictive processing is an influential framework in neuroscience that posits the brain as a prediction machine—constantly generating and updating internal ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

In the cerebral cortex, numerous neurons exchange information through junctions known as synapses. The strength of each ...

The brains of humans and other primates are known to execute various sophisticated functions, one of which is the ...