Diffusion Probabilistic Model (DPM) has recently become one of the hottest topics in computer
vision. Its image generation applications, such as Imagen, Latent Diffusion Models, and …

Deep neural networks have been well-known for their superb handling of various machine
learning and artificial intelligence tasks. However, due to their over-parameterized black-box …

Pretrained language models have shown promise in analysing nucleotide sequences, yet a
versatile model excelling across diverse tasks with a single pretrained weight set remains …

In recent years, data and computing resources are typically distributed in the devices of end
users, various regions or organizations. Because of laws or regulations, the distributed data …

Combining Large Language Models (LLMs) with search engine services marks a significant
shift in the field of services computing, opening up new possibilities to enhance how we …

Advanced machine learning models have recently achieved high predictive accuracy for
weather and climate prediction. However, these complex models often lack inherent …

This paper proposes a novel participant selection framework, named CrowdRecruiter, for
mobile crowdsensing. CrowdRecruiter operates on top of energy-efficient Piggyback …

Drug discovery often relies on the successful prediction of protein-ligand binding affinity.
Recent advances have shown great promise in applying graph neural networks (GNNs) for …

While deep learning (DL) is data-hungry and usually relies on extensive labeled data to
deliver good performance, Active Learning (AL) reduces labeling costs by selecting a small …

… Xiong are the corresponding authors. Please contact them via qingzwang@outlook.com
and haoyi.xiong.fr@ieee.org. Fei Wu and Ning Ding are with the Department of Physical Edu…