Post #860

GraphML News (August 31st) - When GNNs help, randomized transformers, and new papers August is a dry month in terms of news, but soon we’ll start to see upcoming ICLR submissions! 🔨 Meanwhile, have a look at the Measuring and Exploiting Network Usable Information blogpost by Meng-Chieh Lee (based off the spotlight ICLR 2024 paper) that touches upon the question asked every day in industrial labs - will GNNs outperform MLPs on my data? Are there any hints or data characteristics (well, apart from the homophily ratio) that could indicate which model would be better without training one? The authors introduce the notion of Network Usable Information (NUI) as a function of structural embeddings, node features, and neighbors’ features and find some correlations between the new score and performance on node classification and link prediction. We submitted a position paper to ICML’24 studying a similar question but it didn’t get through because reviewers demanded more experiments (in the positions track, yeah). 🎰Learning Randomized Algorithms with Transformers by Google and ETH Zurich - a intriguing blend of theoretical CS, math, and randomized algorithms with expressiveness of transformers. Experiments shows that randomized transformers can solve graph coloring problems on small sizes and explore grid worlds. More weekend reading: 💊Graph Artificial Intelligence in Medicine by Ruth Johnson, Michelle Li, feat Marinka Zitnik - a massive survey on GNNs in clinical applications. Do Graph Neural Networks Work for High Entropy Alloys? by Zhang et al - the answer is yes, but with proper modeling. High-entropy alloys are unordered at the atomic scale but can be represented as sets of graphs (each graph is a local env for an alloy). Practically, adding a set pooling function like DeepSet(GNN(set of graphs)) is what we are looking for. Expressive Power of Temporal Message Passing by Przemysław Wałega and Michael Rawson - Weisfeiler and Leman Go Temporal! Another fun fact about temporal GNNs: two models named DyG-Mamba (one, two, both add Mamba on top of GNN encoders) were submitted on arxiv with a few days gap.