3 code implementations • NeurIPS 2021 • Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim
Many widely used datasets for graph machine learning tasks have generally been homophilous, where nodes with similar labels connect to each other.
Ranked #2 on Node Classification on wiki
Graph Learning Node Classification on Non-Homophilic (Heterophilic) Graphs
2 code implementations • 30 Jun 2021 • Abhay Singh, Qian Huang, Sijia Linda Huang, Omkar Bhalerao, Horace He, Ser-Nam Lim, Austin R. Benson
Here, we demonstrate how simply adding a set of edges, which we call a \emph{proposal set}, to the graph as a pre-processing step can improve the performance of several link prediction algorithms.
Ranked #1 on Link Property Prediction on ogbl-ddi
1 code implementation • 19 Sep 2020 • Ayush Mangal, Jitesh Jain, Keerat Kaur Guliani, Omkar Bhalerao
While previous approaches used the past as an indicator of the future, we instead explicitly model the future frequency and recency in a multi-task fashion with prefetching, leveraging the abilities of deep networks to capture futuristic trends and use them for learning eviction and admission.