This is a PyTorch implementation of graph-adaptive activation functions for Graph Neural Networks (GNNs). For any questions or suggestions, please e-mail Bianca Iancu at [email protected] or ...

Abstract: Much of the early domain-specific success with graph analytics has been with algorithms whose results are based on global graph structure. An example of such an algorithm is betweenness ...

A major use in defining functions is for using them to define further functions. This would be useful for visualising, explaining and manipulating composite functions, a major concept in mathematics ...

Abstract: This paper presents the first construction of strongly regular graphs and association schemes from weakly regular plateaued functions over the finite fields of odd characteristic. Indeed, we ...

Graphs of exponential functions and logarithmic functions provide a visual insight into their properties, such as growth, decay, and the inverse relationship between them. Graphs of exponential ...

Graph database vendor Neo4j Inc. is teaming up with Snowflake Inc. to make a library of Neo4j’s graph analytics functions available in the Snowflake cloud. The deal announced today allows users to ...

In this paper, we study the symmetric and the generating functions for odd and even terms of the second-order linear recurrence sequences. we introduce a operator in order to derive a new family of ...