Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
Ensemble integrating three architectures achieved area under the curve of 0.9208, outperforming individual models ...
Researchers have developed a powerful machine learning framework that can accurately predict and optimize biochar production from algae, offering a ...
This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...
Artificial intelligence is reshaping cybersecurity, but much of that progress has focused on cloud and enterprise ...
According to A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges, published in Sensors, AI-based predictive maintenance systems ...
AI autoscaling promises a self-driving cloud, but if you don’t secure the model, attackers can game it into burning cash or ...
Duke Student Government senators met Wednesday to approve over $150,000 in Student Organization Finance Committee and ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Modern Engineering Marvels on MSN
Dead Sea Scrolls rewrote biblical history. Did AI just push them further back?
But what has a jar in a desert cave to do with machine learning? A Bedouin shepherd who sought one of the limestone hills ...
The greatest risk in financial AI isn't that machines will make mistakes. It's that institutions will believe they understand those machines when they don't.
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