Schedule of the Seminar:

Introduction to Graph Neural Networks (Fady Yacoub, October 13, 2025)

Graph Neural Networks for Node Classification (Jan Andrzejewski, October 13, 2025)

Graph Neural Networks: Scalability (Adrian Walczak, October 20, 2025)

Interpretability in Graph Neural Networks (Kacper Chmielewski, November 3, 2025)

Graph Neural Networks: Link Prediction (Igor Jakus, October 27, 2025)

Graph Neural Networks: Graph Classification (Wiktor Małysa, November 3, 2025)

Graph Neural Networks: Graph Matching (Vikrant Rajput, November 17, 2025)

Graph Neural Networks in Modern Recommender Systems (Jose Aguilar Olmo, November 24, 2025)

Spatial Graph Autoencoders (Bartosz Brzoza, November 24, 2025)

2nd Round of Papers (some possible topics):

Semi-Supervised Classification with Graph Convolutional Networks [PDF]

Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision [PDF]

Graph Random Neural Network for Semi-Supervised Learning on Graphs [PDF]

E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classification [PDF]

A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions (selected topics) [PDF]

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection (selected topics) [PDF]

Gated Graph Sequence Neural Networks [PDF]

Link Prediction Based on Graph Neural Networks [PDF]

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting [PDF]

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting [PDF]

Graph U-Nets [PDF]

Predictive temporal embedding of dynamic graphs [PDF]

T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction [PDF]