Double Prioritized State Recycled Experience Replay. - Fanchen Bu; Dong Eui Chang (CoRR, 2020)

Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs. - Fanchen Bu; Dong Eui Chang (AAAI, 2022)

Robust Graph Clustering via Meta Weighting for Noisy Graphs. - Hyeonsoo Jo; Fanchen Bu; Kijung Shin (CIKM, 2023)

Towards Deep Attention in Graph Neural Networks: Problems and Remedies. - Soo Yong Lee; Fanchen Bu; Jaemin Yoo; Kijung Shin (ICML, 2023)

On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. - Fanchen Bu; Kijung Shin (KDD, 2023)

How Transitive Are Real-World Group Interactions? - Measurement and Reproduction. - Sunwoo Kim 006; Fanchen Bu; Minyoung Choe; Jaemin Yoo; Kijung Shin (KDD, 2023)

Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes. - Hyunju Kim; Jihoon Ko; Fanchen Bu; Kijung Shin (WWW, 2023)

Interplay between topology and edge weights in real-world graphs: concepts, patterns, and an algorithm. - Fanchen Bu; Shinhwan Kang; Kijung Shin (Data Min. Knowl. Discov., 2023)

Hypercore decomposition for non-fragile hyperedges: concepts, algorithms, observations, and applications. - Fanchen Bu; Geon Lee; Kijung Shin (Data Min. Knowl. Discov., 2023)

HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs. - Sunwoo Kim 006; Shinhwan Kang; Fanchen Bu; Soo Yong Lee; Jaemin Yoo; Kijung Shin (ICLR, 2024)

Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More. - Fanchen Bu; Hyeonsoo Jo; Soo Yong Lee; Sungsoo Ahn; Kijung Shin (ICML, 2024)

Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective. - Soo Yong Lee; Sunwoo Kim 006; Fanchen Bu; Jaemin Yoo; Jiliang Tang; Kijung Shin (ICML, 2024)

Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy. - Sunwoo Kim 006; Soo Yong Lee; Fanchen Bu; Shinhwan Kang; Kyungho Kim; Jaemin Yoo; Kijung Shin (NeurIPS, 2024)

Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms. - Fanchen Bu; Ruochen Yang; Paul Bogdan; Kijung Shin (CoRR, 2024)

DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation. - Junghun Lee; Hyunju Kim; Fanchen Bu; Jihoon Ko; Kijung Shin (AAAI, 2025)

On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications. - Hyeonsoo Jo; Hyunjin Hwang; Fanchen Bu; Soo Yong Lee; Chanyoung Park 001; Kijung Shin (KDD (1), 2025)

TiGer: Self-supervised Purification for Time-Evolving Graphs. - Hyeonsoo Jo; Jongha Lee; Fanchen Bu; Kijung Shin (PAKDD (2), 2025)

Estimating simplet counts via sampling. - Hyunju Kim; Heechan Moon; Fanchen Bu; Jihoon Ko; Kijung Shin (VLDB J., 2025)

Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification. - Langzhang Liang; Fanchen Bu; Zixing Song; Zenglin Xu; Shirui Pan; Kijung Shin (CoRR, 2025)

On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis. - Fanchen Bu; Kijung Shin (CoRR, 2025)

PyTorch-based Geometric Learning with Non-CUDA Processing Units: Experiences from Intel Gaudi-v2 HPUs. - Fanchen Bu; Kijung Shin (CoRR, 2025)

A Survey on Hypergraph Mining: Patterns, Tools, and Generators. - Geon Lee; Fanchen Bu; Tina Eliassi-Rad; Kijung Shin (ACM Comput. Surv., 2025)