HackerNoon

The Race to Build AI’s Context Layer Is Really About Meaning

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Computer scientists develop a new AI tool that rivals AlphaFold 3 in mapping RNA

The same family of artificial intelligence that powers today's image generators is now being aimed at one of biology's ...
Tech Xplore

Geospatial upgrade gives TabPFN sharper local predictions on datasets up to 70,000 rows

A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make ...
GitHub

Advanced and complementary data structures for modern .NET.

TsPytham.DotNet.AdvancedCollections provides production-ready data structures that are not included in System.Collections, designed with clean APIs, modern C# features, and performance in mind. This ...
GitHub

CCST：Cell clustering for spatial transcriptomics data with graph neural network

Taking advantages of two recent technical development, spatial transcriptomics and graph neural network, we thus introduce CCST, Cell Clustering for Spatial Transcriptomics data with graph neural ...
IEEE

Depth Estimation From Light Field Using Graph-Based Structure-Aware Analysis

Abstract: Existing light field depth map estimation approaches only utilize partial angular views in occlusion areas and local spatial dependencies in the optimization. This paper proposes a novel two ...
IEEE

GCFC: Graph Convolutional Fusion CNN Network for Cross-Domain Zero-Shot Extraction of Winter Wheat Map

Abstract: Accurate extraction of winter wheat and its planted area holds significance for agricultural research and government real-time food monitoring. Traditional machine learning methods often ...
Scientific Research Publishing

Multi-Head Attention Spatial-Temporal Graph Neural Networks for Traffic Forecasting ()

Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit ...