DaRE: A Cross-Domain Recommender System with Domain-aware Feature Extraction and Review Encoder. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chongkwon Kim (CoRR, 2021)

Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Hyungho Byun; Chong-Kwon Kim (CIKM, 2022)

Review-Based Domain Disentanglement without Duplicate Users or Contexts for Cross-Domain Recommendation. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Hyungho Byun; Chong-Kwon Kim (CIKM, 2022)

DiVa: An Accelerator for Differentially Private Machine Learning. - Beomsik Park; Ranggi Hwang; Dongho Yoon; Yoonhyuk Choi; Minsoo Rhu (MICRO, 2022)

Flip Initial Features: Generalization of Neural Networks for Semi-supervised Node Classification. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chong-Kwon Kim (CoRR, 2022)

Universal Graph Contrastive Learning with a Novel Laplacian Perturbation. - Taewook Ko; Yoonhyuk Choi; Chong-Kwon Kim (UAI, 2023)

Signed Directed Graph Contrastive Learning with Laplacian Augmentation. - Taewook Ko; Yoonhyuk Choi; Chong-Kwon Kim (CoRR, 2023)

Is Signed Message Essential for Graph Neural Networks? - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chong-Kwon Kim (CoRR, 2023)

Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chong-Kwon Kim (CoRR, 2023)

A spectral graph convolution for signed directed graphs via magnetic Laplacian. - Taewook Ko; Yoonhyuk Choi; Chong-Kwon Kim (Neural Networks, 2023)

Improving the Text Convolution Mechanism with Large Language Model for Review-Based Recommendation. - Yoonhyuk Choi; Fahim Tasneema Azad (IEEE Big Data, 2024)

Prioritizing Potential Wetland Areas via Region-to-Region Knowledge Transfer and Adaptive Propagation. - Yoonhyuk Choi; Reepal Shah; John Sabo; Huan Liu 001; K. Selçuk Candan (IEEE Big Data, 2024)

Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning. - Ahmet Kapkiç; Pratanu Mandal; Shu Wan 002; Paras Sheth; Abhinav Gorantla; Yoonhyuk Choi; Huan Liu 001; K. Selçuk Candan (CIKM, 2024)

Precipitation Nowcasting with Graph Neural Network and Gated Recurrent Units. - Soobin Park; Yoonhyuk Choi; Chong-Kwon Kim (ICOIN, 2024)

Review-Based Cross-Domain Recommendation via Hyperbolic Embedding and Hierarchy-Aware Domain Disentanglement. - Yoonhyuk Choi (CoRR, 2024)

Better Not to Propagate: Understanding Edge Uncertainty and Over-smoothing in Signed Graph Neural Networks. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chong-Kwon Kim (CoRR, 2024)

Selective Blocking for Message-Passing Neural Networks on Heterophilic Graphs. - Yoonhyuk Choi; Taewook Ko; Jiho Choi; Chong-Kwon Kim (UAI, 2025)

Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chong-Kwon Kim (WSDM, 2025)

Review-Based Hyperbolic Cross-Domain Recommendation. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chong-Kwon Kim (WSDM, 2025)

Hierarchical Uncertainty-Aware Graph Neural Network. - Yoonhyuk Choi; Chong-Kwon Kim (CoRR, 2025)

SpecSphere: Dual-Pass Spectral-Spatial Graph Neural Networks with Certified Robustness. - Yoonhyuk Choi; Chong-Kwon Kim (CoRR, 2025)

Beyond Message-Passing: Generalization of Graph Neural Networks via Feature Perturbation for Semi-Supervised Node Classification. - Yoonhyuk Choi; Jiho Choi; Taewook Ko; Chong-Kwon Kim (IEEE Trans. Neural Networks Learn. Syst., 2025)