Topics
The topics of interest for submission include, but are not limited to:
Fundamental Theories of Granular-Ball Computing
Granular ball representation modeling and generation optimization mechanisms
Neuropsychological cognitive mechanisms and performance analysis of granular-ball computing
Mathematical theories of granular-ball computing
Granular-ball ranking
Etc.
Supervised Granular Ball Learning
Optimization of supervised granular ball generation
Granular ball abductive learning
Granular ball rough sets
Granular ball fuzzy sets
Granular ball concept cognition
Granular ball classifiers
A principle of justifiable granularity for granular balls
Granular ball support vector machine
Granular ball neighborhood relations
Granular ball multi-label learning
Granular ball continual and open learning
Granular ball sampling
Granular ball cloud models
Granular ball kernel learning
Granular ball regression
Granular ball fault detection
Etc.
Unsupervised Granular Ball Learning
Optimization of unsupervised granular ball generation
Granular ball clustering methods
Granular ball kernel learning
A principle of justifiable granularity for granular balls
Granular ball anomaly and outlier detection and other unsupervised granular ball learning methods.
Granular Ball Image Representation and Visual Computing
Granular ball image representation and its applications to image classification, image retrieval, and object recognition; granular ball image-text retrieval
Granular ball superpixel learning
Granular ball image data augmentation
Applications of granular balls in multimodal reasoning, compression, and retrieval augmentation
Granular ball image-text alignment, cross-modal matching, and semantic modeling
Granular ball multimodal large models
Granular ball visual coding and decoding
Granular ball 3D modeling
Granular ball point cloud computing
Granular ball style alignment
Etc.
Granular Ball Deep Learning
Robust deep learning based on latent-space granular-ballization, together with its applications to granular-ball-based image classification, granular ball reinforcement learning, granular ball natural language processing, granular ball temporal analysis, granular ball object detection, granular ball domain generalization crowd counting, and other end-to-end granular ball deep learning solutions.
Granular Ball Graph Learning
Supervised and unsupervised granular-ball graph representation
Granular ball graph coarsening
Granular ball graph node classification
Granular ball graph classification
Granular ball graph clustering
Granular ball graph contrastive learning
Granular ball graph link prediction
Granular ball graph rewriting
Granular ball graph augmentation
Large-scale granular ball graph learning
Interpretable granular ball graph learning
and other graph learning methods based on granular-ball computing.
Granular Ball Computing Theories in Other Related Fields
Granular ball semantic communications
Granular ball three-way decision
Quantum granular ball machine learning
Granular ball swarm intelligence
Granular ball evolutionary computation
Granular ball blockchain
Granular ball federated learning
Granular ball privacy-preserving computing
Granular ball spatial intelligence
Granular ball world models
Granular ball databases
Granular ball signal processing
Granular ball edge computing
Granular-ball computing for science
and interdisciplinary studies combining granular-ball computing with other related fields.
Fundamental Theories of Granular-Ball Computing
Granular ball representation modeling and generation optimization mechanisms
Neuropsychological cognitive mechanisms and performance analysis of granular-ball computing
Mathematical theories of granular-ball computing
Granular-ball ranking
Etc.