Bio-Ceramic Website Management
Managed and enhanced website content, boosting user satisfaction and traffic.
Managed and enhanced website content, boosting user satisfaction and traffic.
Enhancing functionality and user experience in a project with nearly 3k stars.
A Python-based script for automating VPN connections.
Enhanced and optimized software architecture for document management and retrieval.
A comprehensive guide to mastering Large Language Models (LLMs) through hands-on projects.
A step-by-step guide to mastering LangChain through hands-on projects.
Optimized push notification services and improved codebase quality metrics.
A lightweight e-commerce platform designed to mirror Amazon’s functionality.
A step-by-step guide to mastering PyTorch, covering tensors, neural networks, and GPU utilization.
An in-depth exploration of Python, covering hot topics, useful libraries, and advanced programming concepts.
A Progressive Web App (PWA) for product identification and prize distribution.
Published in The 13th International Conference on Complex Networks and their Applications, 2024
In this work, we propose a novel framework that leverages dual reconstruction and contrastive learning to identify anomalies in attributed networks, addressing both structural and attribute-level outliers. Our experiments on benchmark datasets demonstrate significant performance improvements compared to existing methods.
Recommended citation: Zade, H.R., Zare, H., Ghassemi Parsa, M., Davardoust, H., Bagheri, M.S. (2025). DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction. In: Cherifi, H., Donduran, M., Rocha, L.M., Cherifi, C., Varol, O. (eds) Complex Networks & Their Applications XIII. COMPLEX NETWORKS 2024 2024. Studies in Computational Intelligence, vol 1189. Springer, Cham. https://doi.org/10.1007/978-3-031-82435-7_1
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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