India, July 3 -- Every time you apply for a loan or credit card, the lender checks your credit report. That check leaves a ...

The subthalamic nucleus contains subpopulations with different contributions to deliberative decision-making based on noisy evidence and reward-driven preferences.

For decades, the story of urban growth has seemed almost self-writing: big cities get bigger, pull in talent and jobs, and ...

Cornell Tech researchers found that a 13-word Reddit comment can cause ChatGPT and Gemini to recommend fake products, fraudulent services, and nonexistent businesses. A new analysis published Monday c ...

The purpose of swarm is to provide a novel clustering algorithm that handles massive sets of amplicons. Results of traditional clustering algorithms are strongly input-order dependent, and rely on an ...

Under the terms of the Death in Custody Reporting Act, the Justice Department is required to collect information about everyone who dies in prisons and jails across the United States. The intention ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Graph convolutional network (GCN) has been successfully applied to many graph-based applications; however, training a large-scale GCN remains challenging. Current SGD-based algorithms suffer from ...

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Abstract: Deep spectral clustering is a popular and efficient algorithm in unsupervised learning. However, deep spectral clustering methods are organized into three separate steps: affinity matrix ...