A PyTorch implementation of the DeFoG model for training and sampling discrete graph flows. (Please update to the latest commit. Recent fixes have been applied.) Working with directed graphs? Consider ...

When you're setting out to get a new gaming PC or laptop, you've probably noticed there are quite a few models out there without an Nvidia or AMD graphics chip. These devices usually come with an ...

Abstract: The fractional Fourier transform on graph (GFrFT) is an extension of discrete fractional Fourier transform (DFrFT) based on graph signal processing (GSP). In this paper, we discuss the shift ...

Brain-computer interfaces (BCIs) are advanced and innovative systems that enable direct communication between humans and external devices by utilizing data encoded in the brain activity (Shi et al., ...

ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...

Graphs and data visualizations are all around us—charting our steps, our election results, our favorite sports teams’ stats, and trends across our world. But too often, people glance at a graph ...

School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China Advanced Sensor Research Institution, Northeast Electric Power University, Jilin 132012, China School of ...

A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...

Abstract: Graph Neural Networks (GNNs) have been gaining more attention due to their excellent performance in modeling various graph-structured data. However, most of the current GNNs only consider ...