| 2026 | AAAI | Sheaf Graph Neural Networks via PAC-Bayes Spectral Optimization. | Yoonhyuk Choi, Jiho Choi, Taewook Ko, JongWook Kim, Chong-Kwon Kim |
| 2026 | SIGIR | Delay-Aware Sequential Recommendation with Dynamic Graphs and Variate-Temporal Decomposition. | Yoonhyuk Choi |
| 2025 | UAI | Selective Blocking for Message-Passing Neural Networks on Heterophilic Graphs. | Yoonhyuk Choi, Taewook Ko, Jiho Choi, Chong-Kwon Kim |
| 2025 | WSDM | Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation. | Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-Kwon Kim |
| 2025 | WSDM | Review-Based Hyperbolic Cross-Domain Recommendation. | Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-Kwon Kim |
| 2024 | CIKM | Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning. | Ahmet Kapki, Pratanu Mandal, Shu Wan, Paras Sheth, Abhinav Gorantla, Yoonhyuk Choi, Huan Liu, K. Seluk Candan |
| 2023 | UAI | Universal Graph Contrastive Learning with a Novel Laplacian Perturbation. | Taewook Ko, Yoonhyuk Choi, Chong-Kwon Kim |
| 2022 | CIKM | Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification. | Yoonhyuk Choi, Jiho Choi, Taewook Ko, Hyungho Byun, Chong-Kwon Kim |
| 2022 | CIKM | Review-Based Domain Disentanglement without Duplicate Users or Contexts for Cross-Domain Recommendation. | Yoonhyuk Choi, Jiho Choi, Taewook Ko, Hyungho Byun, Chong-Kwon Kim |
| 2022 | MICRO | DiVa: An Accelerator for Differentially Private Machine Learning. | Beomsik Park, Ranggi Hwang, Dongho Yoon, Yoonhyuk Choi, Minsoo Rhu |