Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …

The well-known ancient Chinese philosopher Lao Tzu (老子) or Laozi (6th∼ 4th century BC
during the Spring and Autumn period) started his classic Tao Teh Ching《 道德经》 or Dao De …

The popularity of machine learning (ML), deep learning (DL) and artificial intelligence (AI)
has risen sharply in recent years. Despite this spike in popularity, the inner workings of ML …

Deep Learning (DL) has been described as one of the key subfields of Artificial Intelligence
(AI) that is transforming weed detection for site-specific weed management (SSWM). In the …

Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly
emerging efficient machine learning techniques which offer promising solutions for …

Abstract Over the years, Machine Learning models have been successfully employed on
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …

Abstract The Internet of Things (IoT) has become a very popular area of research due to its
large-scale implementation and challenges. However, security is the key concern while …

This paper introduces SpecInfer, a system that accelerates generative large language model
(LLM) serving with tree-based speculative inference and verification. The key idea behind …

The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …