Class-incremental multi-label stream classification (class-incremental MLSC) requires learning algorithms to adapt to concept drifts, perform single-pass online learning, and handle emerging new ...

In addition, we introduce an adaptive mechanism to control the level of supervision during learning, crucial for balancing prediction quality with effective use of unlabeled data. To validate ...

Materials design stands to be one of the most promising applications of quantum computing. However, the presence of noise in near-term quantum devices restricts quantum simulations of materials to ...