Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …

This review discussed the dilemma of small data faced by materials machine learning. First,
we analyzed the limitations brought by small data. Then, the workflow of materials machine …

Deep long-tailed learning, one of the most challenging problems in visual recognition, aims
to train well-performing deep models from a large number of images that follow a long-tailed …

Species distribution modeling (SDM) is widely used in ecology and conservation. Currently,
the most available data for SDM are species presence‐only records (available through …

Artificial intelligence (AI) has an astonishing potential in assisting clinical decision making
and revolutionizing the field of health care. A major open challenge that AI will need to …

In this paper, we propose Parametric Contrastive Learning (PaCo) to tackle long-tailed
recognition. Based on theoretical analysis, we observe supervised contrastive loss tends to …

With the development of Internet of Things (IoT), 5 G, and cloud computing technologies, the
amount of data from manufacturing systems has been increasing rapidly. With massive …

The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …

Network intrusion detection systems (NIDSs) play an important role in computer network
security. There are several detection mechanisms where anomaly-based automated …

Abstract Multi-Label Classification (MLC) is an extension of the standard single-label
classification where each data instance is associated with several labels simultaneously …