AI-powered knowledge graph links heart images to genes and drug predictions

Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already ...
GitHub

Official repository for the paper "Learning Latent Graph Structures and Their Uncertainty" (ICML 2025)

This repository contains a refactoring of the code used in the paper "Learning Latent Graph Structures and Their Uncertainty" (ICML 2025). The code is designed to be modular and easy to use, allowing ...
GitHub

Code Structure Analyzer (CSA)

This tool has been developed using both LM Studio and Ollama as LLM providers. The idea behind using a local LLM, like Google's Gemma-3 1B, is data privacy and low cost. In addition, with a good LLM a ...
IEEE

Scalable Fuzzy Clustering With Collaborative Structure Learning and Preservation

Abstract: To partition samples into distinct clusters, Fuzzy C-Means (FCM) calculates the membership degrees of samples to cluster centers and provides soft labels, gaining significant attention in ...
Forbes

Using Agents To Intelligently Traverse Graph-Based Data Structures

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...
Ars Technica

Syntax hacking: Researchers discover sentence structure can bypass AI safety rules

Researchers from MIT, Northeastern University, and Meta recently released a paper suggesting that large language models (LLMs) similar to those that power ChatGPT may sometimes prioritize sentence ...
IEEE

Enhancing Graph Structure Learning via Motif-Driven Hypergraph Construction

Abstract: Graph neural networks (GNNs), as a cutting-edge technology in deep learning, perform particularly well in various tasks that process graph structure data. However, their foundation on ...