Wang, Yusu

40 publications

ICML 2025 De-Coupled NeuroGF for Shortest Path Distance Approximations on Large Terrain Graphs Samantha Chen, Pankaj K Agarwal, Yusu Wang

NeurIPS 2025 Differentiable Extensions with Rounding Guarantees for Combinatorial Optimization over Permutations Robert R Nerem, Zhishang Luo, Akbar Rafiey, Yusu Wang

NeurIPS 2025 Effective Neural Approximations for Geometric Optimization Problems Samantha Chen, Oren Ciolli, Anastasios Sidiropoulos, Yusu Wang

ICML 2025 Elucidating Flow Matching ODE Dynamics via Data Geometry and Denoisers Zhengchao Wan, Qingsong Wang, Gal Mishne, Yusu Wang

JMLR 2025 Enhancing Graph Representation Learning with Localized Topological Features Zuoyu Yan, Qi Zhao, Ze Ye, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

NeurIPS 2025 Seeds of Structure: Patch PCA Reveals Universal Compositional Cues in Diffusion Models Qingsong Wang, Zhengchao Wan, Mikhail Belkin, Yusu Wang

ICML 2024 Comparing Graph Transformers via Positional Encodings Mitchell Black, Zhengchao Wan, Gal Mishne, Amir Nayyeri, Yusu Wang

AISTATS 2024 DE-HNN: An Effective Neural Model for Circuit Netlist Representation Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Michaël Defferrard, Elahe Rezaei, Ryan M. Carey, Rhett Davis, Rajeev Jain, Yusu Wang

ALT 2024 Distances for Markov Chains, and Their Differentiation Tristan Brugère, Zhengchao Wan, Yusu Wang

AAAI 2024 Learning Ultrametric Trees for Optimal Transport Regression Samantha Chen, Puoya Tabaghi, Yusu Wang

AAAI 2024 NN-Steiner: A Mixed Neural-Algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem Andrew B. Kahng, Robert R. Nerem, Yusu Wang, Chien-Yi Yang

AISTATS 2024 On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers Cai Zhou, Rose Yu, Yusu Wang

ICML 2024 Position: Topological Deep Learning Is the New Frontier for Relational Learning Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T Schaub, Petar Veličković, Bei Wang, Yusu Wang, Guowei Wei, Ghada Zamzmi

ALT 2024 Universal Representation of Permutation-Invariant Functions on Vectors and Tensors Puoya Tabaghi, Yusu Wang

LoG 2023 Cycle Invariant Positional Encoding for Graph Representation Learning Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen, Yusu Wang

AISTATS 2023 Implicit Graphon Neural Representation Xinyue Xia, Gal Mishne, Yusu Wang

NeurIPS 2023 Neural Approximation of Wasserstein Distance via a Universal Architecture for Symmetric and Factorwise Group Invariant Functions Samantha Chen, Yusu Wang

ICML 2023 On the Connection Between MPNN and Graph Transformer Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang

ICML 2023 The Numerical Stability of Hyperbolic Representation Learning Gal Mishne, Zhengchao Wan, Yusu Wang, Sheng Yang

ICMLW 2023 The Weisfeiler-Lehman Distance: Reinterpretation and Connection with GNNs Samantha Chen, Sunhyuk Lim, Facundo Memoli, Zhengchao Wan, Yusu Wang

ICML 2023 Understanding Oversquashing in GNNs Through the Lens of Effective Resistance Mitchell Black, Zhengchao Wan, Amir Nayyeri, Yusu Wang

ICML 2022 Convergence of Invariant Graph Networks Chen Cai, Yusu Wang

ICML 2022 Generative Coarse-Graining of Molecular Conformations Wujie Wang, Minkai Xu, Chen Cai, Benjamin K Miller, Tess Smidt, Yusu Wang, Jian Tang, Rafael Gomez-Bombarelli

ICLRW 2022 Neural Approximation of Extended Persistent Homology on Graphs Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

NeurIPS 2022 Neural Approximation of Graph Topological Features Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

ICML 2022 Weisfeiler-Lehman Meets Gromov-Wasserstein Samantha Chen, Sunhyuk Lim, Facundo Memoli, Zhengchao Wan, Yusu Wang

ICLR 2021 Graph Coarsening with Neural Networks Chen Cai, Dingkang Wang, Yusu Wang

NeurIPS 2021 NN-Baker: A Neural-Network Infused Algorithmic Framework for Optimization Problems on Geometric Intersection Graphs Evan McCarty, Qi Zhao, Anastasios Sidiropoulos, Yusu Wang

ICLR 2021 Topology-Aware Segmentation Using Discrete Morse Theory Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen

AISTATS 2020 Persistence Enhanced Graph Neural Network Qi Zhao, Ze Ye, Chao Chen, Yusu Wang

AISTATS 2019 A Topological Regularizer for Classifiers via Persistent Homology Chao Chen, Xiuyan Ni, Qinxun Bai, Yusu Wang

IJCAI 2019 Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction Xudong Zhang, Pengxiang Wu, Changhe Yuan, Yusu Wang, Dimitris N. Metaxas, Chao Chen

NeurIPS 2019 Learning Metrics for Persistence-Based Summaries and Applications for Graph Classification Qi Zhao, Yusu Wang

ALT 2018 Unperturbed: Spectral Analysis Beyond Davis-Kahan Justin Eldridge, Mikhail Belkin, Yusu Wang

ICML 2017 Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen

NeurIPS 2016 Graphons, Mergeons, and so on! Justin Eldridge, Mikhail Belkin, Yusu Wang

COLT 2015 Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clustering Justin Eldridge, Mikhail Belkin, Yusu Wang

NeurIPS 2014 Learning with Fredholm Kernels Qichao Que, Mikhail Belkin, Yusu Wang

COLT 2012 Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries Mikhail Belkin, Qichao Que, Yusu Wang, Xueyuan Zhou

NeurIPS 2011 Data Skeletonization via Reeb Graphs Xiaoyin Ge, Issam I. Safa, Mikhail Belkin, Yusu Wang