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Artificial Neural Networks and Machine Learning – ICANN 2024 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part V /

The ten-volume set LNCS 15016-15025 constitutes the refereed proceedings of the 33rd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2024, held in Lugano, Switzerland, during September 17–20, 2024. The 294 full papers and 16 short papers included in these proceedin...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Outros autores: Wand, Michael (Editor), Malinovská, Kristína (Editor), Schmidhuber, Jürgen (Editor), Tetko, Igor V. (Editor)
Formato: Electrónico eBook
Idioma:inglés
Publicado: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edición:1st ed. 2024.
Series:Lecture Notes in Computer Science, 15020
Subjects:
Artificial intelligence.
Computers.
Application software.
Computer networks .
Artificial Intelligence.
Computing Milieux.
Computer and Information Systems Applications.
Computer Communication Networks.
Acceso en liña:https://doi.org/10.1007/978-3-031-72344-5
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Table of Contents:
  • -- Graph Neural Networks.
  • 3D Lattice Deformation Prediction with Hierarchical Graph Attention Networks.
  • Beyond Homophily: Attributed Graph Anomaly Detection via Heterophily-aware Contrastive Learning Network.
  • Boosting Attributed Graph Anomaly Detection via Negative Sample Awareness.
  • CauchyGCN: Preserving Local Smoothness in Graph Convolutional Networks via a Cauchy-Based Message-Passing Scheme and Clustering Analysis.
  • ComMGAE: Community Aware Masked Graph AutoEncoder.
  • CTQW-GraphSAGE: Trainabel Continuous-Time Quantum Walk On Graph.
  • Edged Weisfeiler-Lehman algorithm.
  • Enhancing Fraud Detection via GNNs with Synthetic Fraud Node Generation and Integrated Structural Features.
  • Graph-Guided Multi-View Text Classification: Advanced Solutions for Fast Inference.
  • Invariant Graph Contrastive Learning for Mitigating Neighborhood Bias in Graph Neural Network based Recommender Systems.
  • Key Substructure-Driven Backdoor Attacks on Graph Neural Networks.
  • Missing Data Imputation via Neighbor Data Feature-enriched Neural Ordinary Differential Equations.
  • Multi-graph Fusion and Virtual Node Enhanced Graph Neural Networks.
  • STGNA: Spatial-Temporal Graph Convolutional Networks with Node Level Attention for Shortwave Communications Parameters Forecasting.
  • Virtual Nodes based Heterogeneous Graph Convolutional Neural Network for Efficient Long-Range Information Aggregation.
  • Large Language Models.
  • A Three-Phases-LORA Finetuned Hybrid LLM Integrated with Strong Prior Module in the Eduation Context.
  • An Enhanced Prompt-Based LLM Reasoning Scheme via Knowledge Graph-Integrated Collaboration.
  • Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models.
  • BiosERC: Integrating Biography Speakers Supported by LLMs for ERC Tasks.
  • CSAFT: Continuous Semantic Augmentation Fine-Tuning for Legal Large Language Models.
  • FashionGPT: A Large Vision-Language Model for Enhancing Fashion Understanding.
  • Generative Chain-of-Thought for Zero-shot Cognitive Reasoning.
  • Generic Joke Generation with Moral Constraints.
  • Large Language Model Ranker with Graph Reasoning for Zero-Shot Recommendation.
  • REM: A Ranking-based Automatic Evaluation Method for LLMs.
  • Semantics-Preserved Distortion for Personal Privacy Protection in Information Management.
  • Towards Minimal Edits in Automated Program Repair: A Hybrid Framework Integrating Graph Neural Networks and Large Language Models.
  • Unveiling Vulnerabilities in Large Vision-Language Models: The SAVJ Jailbreak Approach.

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