Tag: Graph

Graph Neural Networks (GNNs) represent one of the most captivating and rapidly evolving architectures within the deep learning landscape. As deep learning models designed to process data structured as graphs, GNNs bring remarkable versatility and powerful learning capabilities. Among the var...

With remote work being fully-embraced due to Covid 2020 and the continuing rise of the Gig economy, creating organizational cognizance thru the eyes of the individual contributor is more critical than ever. “What am I doing, why and how?” are the tip-of-the-spear answers individual co...

It started in 2017 by Jannis, Brandon, and Yaniv. They were annoyed by the lack of easy-to-use tools to make APIs (Application Programming Interfaces) on Ethereum. These APIs are really important for allowing different computer programs to talk to each other. What an indexing protocol is. Think o...

For a retailer, road transportation to deliver stores represents a major part of the logistics costs. Companies often conduct route planning optimization studies to reduce these costs and improve the efficiency of their network. It requires collaboration between continuous ...

In my last installment (Part I), I introduced you to a bit about the process of analyzing an archaeological site with data science. I talked about the frustratingly complex nature of “Old Things in Space” and how the network of artifacts and locations constitute a bipartite graph. As ...

Artificial intelligence has taken the world by storm. Every week, new models, tools, and applications emerge that promise to push the boundaries of human endeavor. The availability of open-source tools that enable users to train and employ complex machine learning models in a modest number of lines ...

Now we read the tsv format into a dataframe. The predicate is the category that the node is assigned too. For example, RingsInDrugs, is the most common ring systems in Drugs and it belongs to the Medicinal Chemistry category in our graph. df = pd.read_csv( 'global_chem.tsv', ...

This post is based on recent works with Cristian Bodnar, Xiaowen Dong, Ben Chamberlain, Davide Eynard, Fabrizio Frasca, Francesco Di Giovanni, Maria Gorinova, Pietro Liò, Giulia Luise, Sid Mishra, Guido Montúfar, Emanuele Rossi, Konstantin Rusch, Nina Otter, James Rowbottom, Jake Toppi...

Additive manufacturing is a promising method for developing metamaterials: while the material (resin, polymer etc.) printed by the machine is typically of one type (with a predetermined stiffness etc.), we can achieve varying properties and compressive behaviours by changing the geometry of the prin...

The applicability of graph theory in the context of web2.0 is obvious, with websites like Facebook (undirected graph of friendships) and Twitter (directed graph of followings) built around them. Another obvious application is in computer networks. The field of operations research, which started with...

Many molecular hunters prefer ligand based similarity searching methods as a virtual screening tool , to identify those structures that are most likely to bind to a drug target, typically a protein receptor or enzyme or search for similar structures by pharmacophoric properties , 3D shape , scaffold...