A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...
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A team of New York University computer scientists has created a neural network that can explain how it reaches its predictions. The work reveals what accounts for the functionality of neural networks ...
AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding. However, there have been limitations for the world of scientific ...
A team of computer scientists has created a neural network that can explain how it reaches its predictions. The work reveals what accounts for the functionality of neural networks--the engines that ...
Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...
A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...
A Husqvarna researcher developed a fast, interpretable PV hotspot-detection method using IR thermography and Lab* color-space features instead of heavy neural networks, achieving up to 95.2% accuracy ...
A binary classification problem is one where the goal is to predict the value of a variable where there are exactly two discrete possibilities. For example, you might want to predict the sex of a ...
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