GitHub

Missing-Modality-Aware Graph Neural Network for Cancer Classification

MAGNET is implemented in Python 3.10 and is supported on both Linux and Windows. It should work on any operating system that supports Python. The implementation has been tested on both GPU and CPU ...
Nasdaq

Argo Living Soils Corp. Announces Research and Development Agreement with Graphene Leaders Canada Inc. to Advance Graphene Concrete Solutions

Vancouver, British Columbia--(Newsfile Corp. - May 5, 2025) - Argo Living Soils Corp. (CSE: ARGO) (OTCQB: ARLSF) (FSE: 94Y0) ("Argo" or the "Company") is pleased to announce it has entered into a ...
C&EN

Discovery of Spin-Crossover Materials with Equivariant Graph Neural Networks and Relevance-Based Classification

Department of Physics, University of Florida, Gainesville, Florida 32611, United States Center for Molecular Magnetic Quantum Materials, Gainesville, Florida 32611, United States Center for Molecular ...
Scientific Research Publishing

IUSS Working Group WRB (2022) World Reference Base for Soil Ressources. In-ternational Soil Classification System for Naming Soils and Creating Legends for Soil Maps. 4th ...

ABSTRACT: Enhancing the value of indigenous food crops such as Egusi melon, which is considered a “lost crop” in many places around the globe, can significantly contribute to food security of millions ...
Scientific Research Publishing

WRB (2022) World Reference Base for Soil Resources. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps. 4th Edition, International ...

TITLE: Determination of Organic Matter and Trace Metals Elements (As, Sb, Cd, Hg, Ni, Pb, Cr, Zn) in the Soils of the Banks of Watercourses in Brazzaville City (Republic of Congo) ...
GitHub

Determine if a graph is chordal bipartite, and if so, find a bisimplicial ordering in a faster algorithm

I know that for chordal graphs, Sage has a function to recognize a perfect elimination ordering. This problem is somewhat similar, identifying chordal bipartite graphs. The following theorem is ...
marktechpost

GraphIC: A Novel Machine Learning Approach that Leverages Graph-based Representations of Reasoning Processes Coupled with Bayesian Networks (BNs) to Select In-Context Examples ...

In-context learning (ICL) enables LLMs to adapt to new tasks by including a few examples directly in the input without updating their parameters. However, selecting appropriate in-context examples ...
IEEE

Generalized Soil Texture Classification Using Systematic Generation of Mixtures Based on USDA Soil Classification Triangle

Abstract: Soil texture classification is pivotal in diverse fields, such as agriculture, environmental science, geology, civil engineering, and land management. Traditional approaches to soil texture ...
IEEE

DisenSemi: Semi-Supervised Graph Classification via Disentangled Representation Learning

Abstract: Graph classification is a critical task in numerous multimedia applications, where graphs are employed to represent diverse types of multimedia data, including images, videos, and social ...