The rapid and accurate in silico prediction of protein-ligand binding free energies or binding
affinities has the potential to transform drug discovery. In recent years, there has been a …

As an essential approach in many Internet of Things (IoT) applications, multiview learning
synthesizes multiple features to achieve more comprehensive descriptions of data items …

Stock ranking is a significant and challenging problem. In recent years, the use of multi-view
data, such as price and tweet, for stock ranking has gained considerable attention in the …

In vision-based action recognition, spatio-temporal features from different modalities are
used for recognizing activities. Temporal modeling is a long challenge of action recognition …

Automatic medical image analysis (eg, medical image classification) is widely used in the
early diagnosis of various diseases. The computer-aided diagnosis (CAD) systems enable …

Gesture recognition has attracted considerable attention owing to its great potential in
applications. Although the great progress has been made recently in multi-modal learning …

Hand gestures are a well-known and intuitive method of human-computer interaction. The
majority of the research has concentrated on hand gesture recognition from the RGB …

Gesture recognition defines an important information channel in human-computer
interaction. Intuitively, combining inputs from multiple modalities improves the recognition …

Molecular representation learning is the first yet vital step in combining deep learning and
molecular science. To push the boundaries of molecular representation learning, we present …

Multi-view learning is effective in improving data classification accuracy through integrating
information from multiple sources. To guarantee the reliability of multi-view classification, the …