Oral Presentations

• Summarizing Dynamic Graphs using MDL, Divyam Saran and Jilles Vreeken
• General Generator for Attributed Graphs with Community Structure, Seiji Maekawa, Jianpeng Zhang, George Fletcher and Makoto Onizuka
• Discovering Robustly Connected Subgraphs with Simple Descriptions, Janis Kalofolias, Mario Boley and Jilles Vreeken
• Link Prediction via Community Detection in Bipartite Multi-Layer Graphs, Maksim Koptelov, Albrecht Zimmermann and Bruno Cremilleux

Poster Presentations

• Dual-Primal Graph Convolutional Networks, Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann and Michael Bronstein
• Proximity Preserving Nonnegative Matrix Factorization, Yuya Ogawa, Koh Takeuchi, Yuya Sasaki and Makoto Onizuka
• Which way? Direction-Aware Attributed Graph Embedding, Zekarias Kefato, Nasrullah Sheikh and Alberto Montresor
• On the Necessity of Graph Kernel Baselines, Till Hendrik Schulz and Pascal Welke
• Clustering graphs using random trees, Kevin Dalleau, Miguel Couceiro and Malika Smail-Tabbone
• A Similarity-Driven Sequential Model for Predicting Medical Treatment Initiation via Graph Laplacian, Tong Wu, Yue Wang, Yunlong Wang, Cao Xiao, Emily Zhao, Lucas Glass and Jimeng Sun
• Mixed-Order Spectral Clustering for Networks, Yan Ge, Haiping Lu and Pan Peng
• Client Network: An Interactive Model for Predicting New Clients, Massimiliano Mattetti, Akihiro Kishimoto, Adi Botea, Elizabeth M. Daly, Inge Vejsbjerg, Bei Chen and Oznur Alkan
• Graph Embeddings for Enrichment of Historical Data, Jurian Baas, Mehdi Dastani and Ad Feelders
• What can structural characteristics of networks tell us about the quality of link predictions?, Maksim Koptelov and Albrecht Zimmermann
• Multi-layered Graph Representation Learning with Edge Restructured Pooling, Atsushi Miyamoto, Koji Fukuda and Yicheng Du