Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to ...

Neural Texture Compression (NTC) is a new technique that improves texture quality while reducing VRAM usage. It relies on a specialized neural network trained to compress ...

In this paper we present a simple model for reading neural population signals for the two attributes of a stimulus. We use Poisson distribution to describe the encoding process of neural populations ...

Abstract: In this article, a neural-network ... over sensor networks. For the discussed plant, the unknown nonlinear dynamics are approximated by resorting to NNs and the communication among ...

Four convolutional neural network (CNN) models were trained for perceptionbased classification tasks (the occurrence of Aristotle illusion vs. Reverse illusion, the occurrence vs. absence of Reverse ...

"We wanted to demonstrate that this neural network based variational approach can also be applied to complex condensed matter systems, proven challenging for traditional numerical methods." ...