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AI-powered strategy streamlines protein engineering by integrating structural and evolutionary constraints
A team of researchers has developed a method that could transform the field of protein engineering. The new approach, called ...
Scientific Research Publishing1d
Machine Learning-Based Outlier Detection in Long-Term Climate Data: Evidence from Burkina Faso’s Synoptic Network ()
Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...
Tech Xplore2d
AI cloud infrastructure gets faster and greener: NPU core improves inference performance by over 60%
The latest generative AI models such as OpenAI's ChatGPT-4 and Google's Gemini 2.5 require not only high memory bandwidth but also large memory capacity. This is why generative AI cloud operating ...
IEEE6d
A Malware Detection Approach Using Autoencoder in Deep Learning
Today, in the field of malware detection, the expanding limitations of traditional detection methods and the increasing accuracy of detection methods designed on the basis of artificial intelligence ...
C&EN28d
Noise-Consistent Hypergraph Autoencoder Based on Contrastive Learning for Cancer ceRNA Association Prediction in Complex Biological Regulatory Networks - ACS Publications
Competitive endogenous RNA (ceRNA) regulatory networks (CENA) have advanced our understanding of noncoding RNAs’ roles in complex diseases, providing a theoretical basis for disease mechanisms.
Nature29d
Meet the engineer using deep learning to restore Renaissance art - Nature
TECHNOLOGY FEATURE 11 June 2025 Meet the engineer using deep learning to restore Renaissance art As a student, Alex Kachkine can only afford damaged art in need of repair.
IEEE29d
Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery - IEEE Xplore
As a breakthrough in the field of machine fault diagnosis, deep learning has great potential to extract more abstract and discriminative features automatically without much prior knowledge compared ...