116 citations · 146 across the 10 of their papers we have counts for
5 papers · 1 filter
PertReason: A Knowledge-Grounded Benchmark and Framework for Cell-State-Conditioned Mechanistic Reasoning of Perturbation Effects
Dongkwan Kim, Yiming Gao, Yining Yang +1
Evaluating machine learning in scientific domains requires separating correct predictions from correct reasons under realistic distribution shifts. We introduce PertReason, a knowl…
Generalizing Weisfeiler-Lehman Kernels to Subgraphs
Dongkwan Kim, Alice Oh
Subgraph representation learning has been effective in solving various real-world problems. However, current graph neural networks (GNNs) produce suboptimal results for subgraph-le…
Models and Benchmarks for Representation Learning of Partially Observed Subgraphs
Dongkwan Kim, Jiho Jin, Jaimeen Ahn +1
Subgraphs are rich substructures in graphs, and their nodes and edges can be partially observed in real-world tasks. Under partial observation, existing node- or subgraph-level mes…
How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Dongkwan Kim, Alice Oh
Attention mechanism in graph neural networks is designed to assign larger weights to important neighbor nodes for better representation. However, what graph attention learns is not…
Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning
Dongkwan Kim, Alice Oh
Subgraph representation learning has emerged as an important problem, but it is by default approached with specialized graph neural networks on a large global graph. These models d…