Knowledge Science with Learning and AI -- Joint Feature Selection and Classifier Parameter Optimization: A Bio-inspired Approach -- Automatic Gaussian Bandwidth Selection for Kernel Principal Component Analysis -- Boosting LightWeight Depth Estimation Via Knowledge Distillation -- Graph Neural Network with Neighborhood Reconnection -- Critical Node Privacy Protection Based on Random Pruning of Critical Trees -- DSEAformer: Forecasting by De-stationary Autocorrelation with Edgebound -- Multitask-based Cluster Transmission for Few-Shot Text Classification -- Hyperplane Knowledge Graph Embedding with Path Neighborhoods and Mapping Properties -- RTAD-TP: Real- Time Anomaly Detection Algorithm for Univariate Time Series Data Based on Two- Parameter Estimation -- Multi-Sampling Item Response Ranking Neural Cognitive Diagnosis with Bilinear Feature Interaction -- A Sparse Matrix Optimization Method for Graph Neural Networks Training -- Dual-dimensional Refinement of Knowledge Graph Embedding Representation -- Contextual Information Augmented Few-Shot Relation Extraction -- Dynamic and Static Feature-aware Microservices Decomposition via Graph Neural Networks -- An Enhanced Fitness-distance Balance Slime Mould Algorithm and Its Application in Feature Selection -- Low Redundancy Learning for Unsupervised Multi-view Feature Selection -- Dynamic Feed-Forward LSTM -- Black-box Adversarial Attack on Graph Neural Networks Based on Node Domain Knowledge -- Role and Relationship-Aware Representation Learning for Complex Coupled Dynamic Heterogeneous Networks -- Twin Graph Attention Network with Evolution Pattern Learner for Few-Shot Temporal Knowledge Graph Completion -- Subspace Clustering with Feature Grouping for Categorical Data -- Learning Graph Neural Networks on Feature-Missing Graphs -- Dealing with Over-reliance on Background Graph for Few-shot Knowledge Graph Completion -- Kernel-based feature extraction for time series clustering -- Cluster Robust Inference for embedding-based Knowledge Graph Completion -- Community-enhanced Contrastive Siamese networks for Graph Representation Learning -- Distant Supervision Relation Extraction with Improved PCNN and Multi-level Attention -- Enhancing Adversarial Robustness via Anomaly-aware Adversarial Training -- An Improved Cross-Validated Adversarial Validation Method -- EACCNet: Enhanced Auto-Cross Correlation Network for Few-Shot Classification -- Joint Label-Structure Estimation from Multifaceted Graph Data -- Dual Channel Knowledge Graph Embedding with Ontology Guided Data Augmentation -- Multi-Dimensional Graph Rule Learner -- MixUNet: A Hybrid Retinal Vessels Segmentation Model Combining The Latest CNN and MLPs -- Robust Few-shot Graph Anomaly Detection via Graph Coarsening -- An Evaluation Metric for Prediction Stability with Imprecise Data -- ReducingThe Teacher-Student Gap Via Elastic Student.