Artificial Neural Networks and Machine Learning - ICANN 2023

Anomaly Detection in Directed Dynamic Graphs via RDGCN and LSTAN.- Anomaly-Based Insider Threat Detection via Hierarchical Information Fusion.- CSEDesc: CyberSecurity Event Detection with Event Description.- GanNeXt: A New Convolutional GAN for Anomaly Detection.- K-Fold Cross-Valuation for Machine Learning Using Shapley Value.- Malicious Domain Detection Based on Self-supervised HGNNs with Contrastive Learning.- Time Series Anomaly Detection with Reconstruction-Based State-Space Models.- ReDualSVG: Refined Scalable Vector Graphics Generation.- Rethinking Feature Context in Learning Image-guided Depth Completion.- Semantic and Frequency Representation Mining for Face Manipulation Detection.- Single image dehazing network based on serial feature attention.- SS-Net: 3D Spatial-Spectral Network for Cerebrovascular Segmentation in TOF-MRA.- STAN: Spatio-Temporal Alignment Network for No-Reference Video Quality Assessment.- Style Expansion without Forgetting for Handwritten Character Recognition.- TransVQ-VAE: Generating Diverse Images using Hierarchical Representation Learning.- UG-Net: Unsupervised-Guided Network for Biomedical Image Segmentation and Classification.- Unsupervised Shape Enhancement and Factorization Machine Network for 3D Face Reconstruction.- Visible-Infrared Person Re-Identification via Modality Augmentation and Center Constraints.- Water Conservancy Remote Sensing Image Classification Based on Target-Scene Deep Semantic Enhancement.- A Partitioned Detection Architecture for Oriented Objects.- A Personalized Federated Multi-Task Learning Scheme for Encrypted Traffic Classification.- Addressing delays in Reinforcement Learning via Delayed Adversarial Imitation Learning.- An Evaluation of Self-Supervised Learning for Portfolio Diversification.- An exploitation-enhanced Bayesian optimization algorithm for high-dimensional expensive