Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, ...

Using large-scale training data with high complexity is necessary for these deep learning methods. This paper uses a spatiotemporal-inspired Deep Neural Network (DNN) to detect video anomalies. Rather ...

Abstract: Deep spiking neural networks (DSNNs), such as spiking transformers, have demonstrated comparable performance to artificial neural networks (ANNs). With higher spike input sparsity and the ...

The main difference ... Machine Learning Operation The Pulsar’s SNN efficiency is about two orders of magnitude better than implementing a similar model in a conventional, digital DNN.

A growing share of Americans say there are important differences between the Republican and Democratic parties, according to a new CNN/SSRS poll. The May survey, released on Sunday, shows 81 ...

To address these issues, our work considers the spatio-temporal property inherent in SNNs, and proposes a novel distillation framework for deep SNNs that optimizes performance across full-range ...