The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

To his credit, Kasy is a realist here. He doesn’t presume that any of these proposals will be easy to implement. Or that it will happen overnight, or even in the near future. The troubling question at ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...

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 ...

Abstract: Reducing energy consumption has become a pressing need for modern machine learning, which has achieved many of its most impressive results by scaling to larger and more energy-consumptive ...

ABSTRACT: Attrition is a common challenge in statistical analysis for longitudinal or multi-stage cross-sectional studies. While strategies to reduce attrition should ideally be implemented during the ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

State Key Laboratory of Water Pollution Control and Green Resource Recycling, Key Laboratory of Yangtze River Water Environment of Ministry of Education, Shanghai Institute of Pollution Control and ...

Abstract: With the rise of e-commerce, personalized recommendation algorithms have received much attention in recent years. Meanwhile, multimodal recommendation algorithms have become the next ...