Yoonhyuk Choi

According to our database, Yoonhyuk Choi authored at least 15 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Prioritizing Potential Wetland Areas via Region-to-Region Knowledge Transfer and Adaptive Propagation.

Yoonhyuk Choi, Reepal Shah, John Sabo, K. Selcuk Candan, Huan Liu

CoRR, 2024

Review-Based Cross-Domain Recommendation via Hyperbolic Embedding and Hierarchy-Aware Domain Disentanglement.

Yoonhyuk Choi

CoRR, 2024

Precipitation Nowcasting with Graph Neural Network and Gated Recurrent Units.

Soobin Park, Yoonhyuk Choi, Chong-Kwon Kim

Proceedings of the International Conference on Information Networking, 2024

Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning.

Ahmet Kapkiç, Pratanu Mandal, Shu Wan, Paras Sheth, Abhinav Gorantla, Yoonhyuk Choi, Huan Liu, K. Selçuk Candan

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

A spectral graph convolution for signed directed graphs via magnetic Laplacian.

Taewook Ko, Yoonhyuk Choi, Chong-Kwon Kim

Neural Networks, July, 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

Is Signed Message Essential for Graph Neural Networks?

Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-Kwon Kim

CoRR, 2023

Signed Directed Graph Contrastive Learning with Laplacian Augmentation.

Taewook Ko, Yoonhyuk Choi, Chong-Kwon Kim

CoRR, 2023

Universal Graph Contrastive Learning with a Novel Laplacian Perturbation.

Taewook Ko, Yoonhyuk Choi, Chong-Kwon Kim

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

Flip Initial Features: Generalization of Neural Networks for Semi-supervised Node Classification.

Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-Kwon Kim

CoRR, 2022

DiVa: An Accelerator for Differentially Private Machine Learning.

Beomsik Park, Ranggi Hwang, Dongho Yoon, Yoonhyuk Choi, Minsoo Rhu

Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 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

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification.

Yoonhyuk Choi, Jiho Choi, Taewook Ko, Hyungho Byun, Chong-Kwon Kim

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

DaRE: A Cross-Domain Recommender System with Domain-aware Feature Extraction and Review Encoder.

Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chongkwon Kim

CoRR, 2021