Mixture-of-Experts (MoE) models are revolutionizing the way we scale AI. By activating only a subset of a model’s components ...

Humans learn by breaking through and plateauing, persisting and resting, and, occasionally, experiencing the blissful flow state. Mastering a skill can take decades, but the learning process unfolds ...

School of Chemical Engineering and Technology, National Engineering Research Center of Distillation Technology, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin ...

To address the challenges, we propose a spectral-spatial representation learning (SSRL) framework based on HSI ... that the proposed algorithm outperforms state-of-art methods in classification ...

Machine learning can be used for bug detection by analyzing code and historical bug data to help predict and identify potential issues early. ML models can help development teams diagnose bugs and ...

One study compared the classification prediction between machine learning algorithms and humans, including experienced psychiatrists, and found that machine learning algorithms performed better than ...

Simultaneously, we integrated machine learning algorithms to analyze complex omics data, a process that proved to be swifter and more efficient than conventional manual methods, while also enhancing ...

School of Mechanical and Equipment Engineering, Hebei University of Engineering, 19 Taiji Road, Congtai District, HanDan 056038, P. R. China ...

A novel deep learning classification model, the dual-input feature fusion network (DIFFN), is proposed to use two types of grayscale images as network inputs to complete flow pattern identification.