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 ...

Abstract: In recent years, deep learning on protein structures has attracted widespread attention, as structures determine proteins' function. A series of structure-based protein property prediction ...

Abstract: This paper presents a novel approach to graph learning, GL-AR, which leverages estimated autoregressive coefficients to recover undirected graph structures from time-series graph signals ...

Trimble introduced the 2025 version of Tekla Structures, its structural building information modeling (BIM) software. The new version introduces AI-enabled tools to improve productivity and more ...

Greek dramas, the heart of ancient theater, have long been hailed for their sophisticated structures, profound philosophical insights, and emotional depth. They were crafted to not only entertain but ...

The Periodic Table (PT) serves as the fundamental basis of chemistry, often commencing classroom discussions led by chemistry teachers. Mastery of its structure empowers students to anticipate ...

The application of deep learning algorithms in protein structure prediction has greatly influenced drug discovery and development. Accurate protein structures are crucial for understanding biological ...

Proteins are the essential component behind nearly all biological processes, from catalyzing reactions to transmitting signals within cells. While advances like AlphaFold have transformed our ability ...

This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...