Fast AI for satellite learns to quantify uncertainty

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Machine learning reveals hidden landscape of robust information storage

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...
IEEE

Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...
IEEE

Gradient-Aware Loss Function for Improved Learning in Speech Enhancement

Abstract: Conventional loss functions for gradient descent are designed mainly to assess output quality, with limited attention to gradient behavior. This study identifies the gradient inconsistency ...
EdNC

Perspective | Reframing ‘learning loss’ to reveal the true value of teachers

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