Abstract: Due to the complex sea clutter environment and target features, the conventional statistical theory-based methods cannot achieve high performance in maritime target detection tasks.

This repository for the paper 📘: A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation. The README file here maintains a list of ...

Abstract: Adversarial attacks can fool powerful graph neural networks by subtly modifying input data's graph topology or node attributes. Attackers usually regard the whole graph or local subgraphs as ...

Development version: This branch contains the code for the upcoming 1.0 release. For the code of the current stable 0.9 release, check out the 0.9.x branch. The upcoming 1.0 release will be the way ...

Amazon has developed a new networking topology that's up to a third faster and up to 40 percent more energy efficient than traditional hierarchical network designs. The novel architecture, called ...

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

Decades ago, Paul Erdős used randomness to illuminate the vast and weird world of networks. Now mathematicians are making his ...

For nearly 30 years, a landmark study shaped how scientists understood the relationship between brain and body size in ...

Roese's predictions: stronger AI governance, better data management, agentic AI infrastructure, resilient AI factories, and sovereign AI strategies.

Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...

The CIL MT Syllabus 2026 consists of two papers, with a total of 660 vacancies for Management Trainee. The Paper 1 covers ...