Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...
Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...
The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...
A deceptively simple question underlies many global environmental policies: where, exactly, are the world’s forests? A new study suggests the answer depends heavily on which map one consults—and that ...
Two researchers advocate for new AI-based measures not because they offer measurement free from error, but rather because they avoid specific problematic forms of error linked to overreliance on ...
Brazilian researchers have developed a methodology that uses remote sensing to map the impact of frost on corn crops. This reduces exposure to climate risks and uncertainty regarding agricultural ...
Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
Tool uses remote sensing to reduce uncertainties regarding agricultural losses, contributing to public policy.
Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.
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