IEEE

Revisiting Deformable Convolution on Graphs: Large-range Modeling and Robustness

Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...
Scientific Research Publishing

Convolution Rather Than Monte Carlo Simulation to Price a Barrier Option ()

Repeated convolution and truncation of a truncated fat-tailed distribution, instead of Monte Carlo simulation, for pricing a discrete, simple barrier option is presented. The parameters for the ...
Crowdfund Insider

Circle Introduces Graph-based Approach to Blockchain Fraud Prevention, Launches Circle Payments Network (CPN)

Circle, the issuer of USD Coin (USDC), is making significant strides to enhance the security and efficiency of global financial transactions. Two recent developments—the introduction of a graph-based ...
C&EN

A Self-Developed Fire Early Warning System Based on Gas Detection and Graph Convolution Calculation Method

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

Machine Learning Prediction of Optical Properties of Coumarin Derivatives Using Gaussian-Weighted Graph Convolution and Subgraph Modular Input

Department of Chemistry and Research Institute for Natural Science, Korea University, Seoul 02841, Korea ...
Hosted on MSN

Coronet Instructional Films: Mastering Graphing - Bar, Line, & Circle Graphs

This educational film teaches viewers how to construct mathematical line graphs to solve algebraic problems. It begins by reviewing statistical graphs and then explains the relationship between ...