| Towards Deep Attention in Graph Neural Networks: Problems and Remedies SY Lee, F Bu, J Yoo, K Shin ICML 2023 (arXiv 2306.02376), 2023 | 33 | 2023 |
| RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark F Berto, C Hua, J Park, L Luttmann, Y Ma, F Bu, J Wang, H Ye, M Kim, ... arXiv:2306.17100, 2023 | 26* | 2023 |
| A Survey on Hypergraph Mining: Patterns, Tools, and Generators G Lee, F Bu, T Eliassi-Rad, K Shin ACM Computing Surveys 2025 (arXiv 2401.08878), 2024 | 20 | 2024 |
| Double Prioritized State Recycled Experience Replay F Bu, DE Chang ICCE-Asia 2020 (arXiv 2007.03961), 2020 | 12 | 2020 |
| How Transitive Are Real-World Group Interactions? - Measurement and Reproduction S Kim, F Bu, M Choe, J Yoo, K Shin KDD 2023 (arXiv 2306.02358), 2023 | 11 | 2023 |
| Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective SY Lee, S Kim, F Bu, J Yoo, J Tang, K Shin ICML 2024 (arXiv 2402.04621), 2024 | 9 | 2024 |
| HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs S Kim, S Kang, F Bu, SY Lee, J Yoo, K Shin ICLR 2024 (arXiv 2404.00638), 2024 | 9 | 2024 |
| Hypercore Decomposition for Non-Fragile Hyperedges: Concepts, Algorithms, Observations, and Applications F Bu, G Lee, K Shin Data Mining and Knowledge Discovery (2023) 37, 2389–2437 (arXiv 2301.08440), 2023 | 9 | 2023 |
| Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs F Bu, DE Chang AAAI 2022 (arXiv 2205.08385), 2022 | 7 | 2022 |
| Robust Graph Clustering via Meta Weighting for Noisy Graphs H Jo, F Bu, K Shin CIKM 2023 (arXiv 2311.00322), 2023 | 6 | 2023 |
| Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes H Kim, J Ko, F Bu, K Shin WWW 2023 (arXiv 2302.05505), 2023 | 6 | 2023 |
| Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More F Bu, H Jo, SY Lee, S Ahn, K Shin ICML 2024 (arXiv:2405.08424), 2024 | 2 | 2024 |
| Interplay between Topology and Edge Weights in Real-World Graphs: Concepts, Patterns, and an Algorithm F Bu, S Kang, K Shin Data Mining and Knowledge Discovery (2023) 37, 2139–2191 (arXiv 2305.09083), 2023 | 2 | 2023 |
| Estimating simplet counts via sampling H Kim, H Moon, F Bu, J Ko, K Shin The VLDB Journal 34 (2), 1-26, 2025 | | 2025 |
| DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation J Lee, H Kim, F Bu, J Ko, K Shin AAAI 2025 (arXiv:2502.01031), 2025 | | 2025 |
| On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications H Jo, H Hwang, F Bu, SY Lee, C Park, K Shin KDD 2025 (arXiv:2501.05015), 2025 | | 2025 |
| Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy S Kim, SY Lee, F Bu, S Kang, K Kim, J Yoo, K Shin NeurIPS 2024 (arXiv 2410.20366), 2024 | | 2024 |
| Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms F Bu, R Yang, P Bogdan, K Shin arXiv:2405.16726, 2024 | | 2024 |
| On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms F Bu, K Shin KDD 2023 (arXiv 2306.06368), 2023 | | 2023 |
| A Novel Optimization Algorithm with Orthogonality for Deep Neural Networks Inspired by Feedback Integrators F Bu KAIST Master's Thesis, 2021 | | 2021 |
Kijung ShinAssociate Professor, KAISTDirección de correo verificada de kaist.ac.kr