Post #624

Fresh picks from ArXiv This week on ArXiv: uncertainty for node classification, GNNs for tabular data, and cryptocurrency graph 🤑 If I forgot to mention your paper, please shoot me a message and I will update the post. GNNs * A Scalable AutoML Approach Based on Graph Neural Networks * Optimizing Sparse Matrix Multiplications for Graph Neural Networks * Graph Embedding with Hierarchical Attentive Membership WSDM 2022 * Unbiased Graph Embedding with Biased Graph Observations * Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification with Stephan Günnemann * Robustness of Graph Neural Networks at Scale with Stephan Günnemann * VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization * Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods * Nested Graph Neural Networks with Pan Li * Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features * Tackling Oversmoothing of GNNs with Contrastive Learning * On the Power of Edge Independent Graph Models * On Provable Benefits of Depth in Training Graph Convolutional Networks * UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation CIKM'2021 * Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs WSDM 2022 * How to transfer algorithmic reasoning knowledge to learn new algorithms? with Petar Velickovic and Jian Tang Software * retworkx: A High-Performance Graph Library for Python * NeuroComb: Improving SAT Solving with Graph Neural Networks * Graph? Yes! Which one? Help! Datasets * Towards a Taxonomy of Graph Learning Datasets * Cryptocurrencies Activity as a Complex Network: Analysis of Transactions Graphs