eeworldonline1d
What is the mathematics behind artificial intelligence?
The mathematics behind artificial intelligence (AI) and machine learning (ML) rely on linear algebra, calculus, probability, ...
eLife3d
Synthetic gene circuits that selectively target RAS-driven cancers
This important study demonstrates the potential of synthetic gene circuits to detect and target aberrant RAS activity in cancer cell lines. The circuit design is novel and the evidence supporting the ...
Your guide to SEO forecasting with Google Sheets
Learn three practical forecasting techniques to help predict SEO performance, justify strategies, and measure progress.
C&EN18d
An Automated Approach for Domain-Specific Knowledge Graph Generation─Graph Measures and Characterization
In this paper, we develop a natural language processing (NLP) approach to extract knowledge graphs resulting in a semantically structured network (SSN) that can be queried. After a detailed exposition ...
GitHub18d
Microsoft Graph .NET Core Client Library
Integrate the Microsoft Graph API into your .NET project! The Microsoft Graph .NET Core Client Library contains core classes and interfaces used by Microsoft.Graph Client Library to send native HTTP ...
Frontiers22d
Graph Convolutional Networks for multi-modal robotic martial arts leg pose recognition
Methods: To address these challenges, we propose PoseGCN, a Graph ... model's robustness under varying input conditions. To further enhance the persuasiveness of our model design, we conducted an ...
Medical Xpress25d
Graph machine learning model shows potential for predicting cancer genes
proposed a graph machine learning model, namely TREE, based on the Transformer framework. With this novel Transformer-based architecture, TREE not only identifies the most influential omics data ...
IEEE27d
A Novel Hybrid Model for Credit Risk Assessment of Supply Chain Finance Based on Topological Data Analysis and Graph Neural Network
This study proposes a novel hybrid Topological Data Analysis (TDA) and Graph Neural Network (GNN) to optimize credit risk assessment in SCF. By leveraging BallMapper (BM) topological data analysis ...
C&EN1mon
MVCL-DTI: Predicting Drug–Target Interactions Using a Multiview Contrastive Learning Model on a Heterogeneous Graph
School of Computer Science and Technology, Soochow University, Jiangsu 215006, China Collaborative Innovation Center of Novel Software Technology and Industrialization, Jiangsu 210000, China ...
InfoWorld1mon
The journey towards a knowledge graph for generative AI
and graph traversal. These operations allow for the synthesis of multiple pieces of information, which can then be fed into RAG models to generate richer, more accurate answers to multi-point ...
IEEE1mon
Enhancing Protein Function Prediction through the Fusion of Multi-type Biological Knowledge with Protein Language Model and Graph Neural Network
Abstract: Proteins play crucial roles in diverse biological functions ... trained protein language model to extract evolution information. Moreover, DeepFMB generates PPI-related features and ...
VentureBeat1mon
Diffbot’s AI model doesn’t guess — it knows, thanks to a trillion-fact knowledge graph
The new model, a fine-tuned version of Meta’s LLama 3.3, is the first open-source implementation of a system known as graph retrieval-augmented generation, or GraphRAG. Unlike conventional AI ...