Researchers in Japan have developed quantum multi-programming auto mode, a function that automatically runs quantum programs from different users in parallel. Launched on the Center for Quantum ...

Abstract: We extend the concept of graph isomorphisms to multilayer networks with any number of “aspects” (i.e., types of layering). In developing this generalization, we identify multiple types of ...

Abstract: In graph theory, a tree is one of the more popular families of graphs with a wide range of applications in computer science as well as many other related fields. While there are several ...

tl;dr: We provably improve GNN expressivity by enhancing message passing with substructure encodings. Our method allows incorporating domain specific prior knowledge and can be used as a drop-in ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Accurately modeling chemical reactions in molecular dynamics simulations requires ...

Over the past few years, graph neural networks and graph transformers have been successfully used to analyze graph-structured data, mainly focusing on node classification and link prediction tasks.

Drug discovery is a challenging process with a huge molecular space to be explored and numerous pharmacological properties to be appropriately considered. Among various drug design protocols, fragment ...

If you’re conducting a census of all the plants growing in a specific region, rather than tally every single plant, you might decide to organize them by species. Doing this along certain stretches of ...