Abstract: Graph neural networks (GNNs) with unsupervised learning can provide high-quality approximate solutions to large-scale combinatorial optimization problems (COPs) with efficient time ...

computational-qr treats a QR code not merely as a URL shortener but as a computational artifact: a self-contained, portable unit of logic, data, and visualisation. Concept What it means in this ...

ABSTRACT: Bipolar disorder (BD) is closely intertwined with abnormalities in sleep and circadian regulation, yet current clinical management typically applies heuristic rules rather than optimizing ...

I make short, to-the-point online math tutorials. I struggled with math growing up and have been able to use those experiences to help students improve in math through practical applications and tips.

I make short, to-the-point online math tutorials. I struggled with math growing up and have been able to use those experiences to help students improve in math through practical applications and tips.

Researchers at Meta FAIR and the University of Edinburgh have developed a new technique that can predict the correctness of a large language model's (LLM) reasoning and even intervene to fix its ...

Abstract: We propose to learn the time-varying stochastic computational resource usage of software as a graph-structured Schrödinger bridge problem (SBP). In general, learning the computational ...

The Uncertainty-Aware Fourier Ptychography (UA-FP) framework marks a transformative milestone in computational imaging, revolutionizing the way we address system uncertainties. This innovative ...

Language-based agentic systems represent a breakthrough in artificial intelligence, allowing for the automation of tasks such as question-answering, programming, and advanced problem-solving. These ...