10 citations · 19 across the 4 of their papers we have counts for
4 papers
Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic Decomposition
Heesoo Jung, Hogun Park
Self-supervised learning (SSL) in graphs has garnered significant attention, particularly in employing Graph Neural Networks (GNNs) with pretext tasks initially designed for other…
CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders
Jongwon Park, Heesoo Jung, Hogun Park
Recent Self-Supervised Learning (SSL) methods encapsulating relational information via masking in Graph Neural Networks (GNNs) have shown promising performance. However, most exist…
Improving Multi-hop Logical Reasoning in Knowledge Graphs with Context-Aware Query Representation Learning
Jeonghoon Kim, Heesoo Jung, Hyeju Jang +1
Multi-hop logical reasoning on knowledge graphs is a pivotal task in natural language processing, with numerous approaches aiming to answer First-Order Logic (FOL) queries. Recent…
Dual Policy Learning for Aggregation Optimization in Graph Neural Network-based Recommender Systems
Heesoo Jung, Sangpil Kim, Hogun Park
Graph Neural Networks (GNNs) provide powerful representations for recommendation tasks. GNN-based recommendation systems capture the complex high-order connectivity between users a…