C&EN

Δ-Learning of High-Fidelity Electronic Structure Using Graph Neural Networks with Modified Node-Level Features

Department of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina 29208, United States ...
C&EN

A Multi-Stage Graph Neural Network–Physics-Informed Neural Network (GNN–PINN) Framework for Thermodynamic Property Prediction

Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon 22212, Republic of Korea ...
usace.army.mil

The Multi-Domain Effects Platoon: A Brigade-Level Solution for Multidomain Operations

An electronic warfare (EW) team in a hide site deep in the woods notices a suspected enemy frequency. At the same time, an aerial EW platform using the same equipment finds the same signal. With both ...
GitHub

DISABLED test_graph_partition_cpu_tensor_symints (__main__.CudaGraphTreeTests)

This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs. Over the past 3 hours, it has been determined flaky in 10 workflow(s) with 20 failures ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
IEEE

Constraint-Based Sub-Graph Partitioning for Multi-Cellular Biological Networks

Abstract: Synthetic consortia represent an emerging research area in synthetic biology, promising to solve various industrial challenges through the metabolic diversity, division of labor, and spatial ...
IEEE

An Effective Multi-level Immune Algorithm for Graph Bipartitionin

Abstract: An important application of graph partitioning is data clustering using a graph model--- the pairwise similarities between all data objects form a weighted graph adjacency matrix that ...