Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2024; 33rd International C Michael Wand,Kristína Malinovská,Igor V. Tetko Conferenc

Inflamed

Key Substructure-Driven Backdoor Attacks on?Graph Neural Networkscker-chosen target class key substructures, modifying few critical edges and nodes. Our approach across real datasets spanning diverse domains highlights its efficiency. The proposed methodology establishes a pioneering direction for refining backdoor attack techniques on GNNs.

無可爭辯

Missing Data Imputation via?Neighbor Data Feature-Enriched Neural Ordinary Differential Equationsetwork is then employed to learn adjacent information of neighboring variables. The temporal information is captured by applying a gate recurrent unit module, thereby obtaining a spatiotemporal prior. The decoder introduces an ordinary differential equation module to generate a series of continuous

尊嚴(yán)

間諜活動

STGNA: Spatial-Temporal Graph Convolutional Networks with Node Level Attention for Shortwave Communiatial-temporal patterns of shortwave communications parameters, yielding to enhanced forecasting accuracy. Comprehensive experiments on a targeted dataset demonstrate that our approach significantly outperforms other baselines in forecasting accuracy.

innate

Virtual Nodes based Heterogeneous Graph Convolutional Neural Network for Efficient Long-Range Informormation aggregation with only 4 layers. Additionally, we demonstrate that VN-HGCN can serve as a versatile framework that can be seamlessly applied to other HGNN models, showcasing its generalizability. Empirical evaluations validate the effectiveness of VN-HGCN, and extensive experiments conducted

febrile

enchant

An Enhanced Prompt-Based LLM Reasoning Scheme via?Knowledge Graph-Integrated Collaboration of the reasoning results. Experimental results show that our scheme significantly progressed across multiple datasets, notably achieving an improvement of over 10% on the QALD10 dataset compared to both the best baseline and the fine-tuned state-of-the-art (SOTA) models.

ATP861

Affirm

HACK