As part of the meetups for the 2023 learning on graphs (LoG) conference, we'll be hosting an event at Mila! Join us for some presentations on the latest graph research, snacks, and lunch. Register to confirm your attendance below! Here is the tentative agenda (find the latest updates here):
10:00 - 10:15 am - A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs by Xinyu Yuan
10:15 - 10:30 - GraphText: Graph Reasoning in Text Space by Jianan Zhao (https://arxiv.org/abs/2310.01089)
10:30 - 10:45 - MUDiff: Unified Diffusion for Complete Molecule Generation by Chenqing Hua
10:45 - 11:00 - Kùzu: A Graph Database Management System for Graph Data Science by Guodong Jin
11:00 - 11:15 - Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets by Dinghuai Zhang
11:15 - 11:30 - Graph Inductive Biases in Transformers without Message Passing by Liheng Ma
11:30 - 11:45 - Towards a GML-Enabled Knowledge Graph Platform by Hussein Abdullah
11:45 - 12:00 - Temporal Graph Benchmark for Machine Learning on Temporal Graphs by Shenyang Huang
12:00 - 12:15 - Graphium, a library to scale GNNs to infinity by Dominique Beaini (https://graphium-docs.datamol.io/stable/)
12:15 - 12:30 - Graph Positional and Structural Encoder by Semih Cantürk (https://arxiv.org/abs/2307.07107)
12:30 - 12:45 - When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability by Sitao Luan
12:45 - 14:00 - Lunch