InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting. - Haoshu Fang; Jianhua Sun 003; Runzhong Wang; Minghao Gou; Yong-Lu Li 001; Cewu Lu (ICCV, 2019)

Learning Combinatorial Embedding Networks for Deep Graph Matching. - Runzhong Wang; Junchi Yan; Xiaokang Yang 001 (ICCV, 2019)

Learning deep graph matching with channel-independent embedding and Hungarian attention. - Tianshu Yu 001; Runzhong Wang; Junchi Yan; Baoxin Li (ICLR, 2020)

Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning. - Runzhong Wang; Junchi Yan; Xiaokang Yang 001 (NeurIPS, 2020)

Deep Reinforcement Learning of Graph Matching. - Chang Liu 021; Runzhong Wang; Zetian Jiang; Junchi Yan (CoRR, 2020)

Combinatorial Learning of Graph Edit Distance via Dynamic Embedding. - Runzhong Wang; Tianqi Zhang; Tianshu Yu 001; Junchi Yan; Xiaokang Yang 001 (CVPR, 2021)

Deep Latent Graph Matching. - Tianshu Yu 001; Runzhong Wang; Junchi Yan; Baoxin Li (ICML, 2021)

A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs. - Runzhong Wang; Zhigang Hua; Gan Liu; Jiayi Zhang 003; Junchi Yan; Feng Qi 005; Shuang Yang; Jun Zhou 011; Xiaokang Yang 001 (NeurIPS, 2021)

Appearance and Structure Aware Robust Deep Visual Graph Matching: Attack, Defense and Beyond. - Qibing Ren; Qingquan Bao; Runzhong Wang; Junchi Yan (CVPR, 2022)

Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning. - Chang Liu 021; Chenfei Lou; Runzhong Wang; Alan Yuhan Xi; Li Shen 008; Junchi Yan (ICML, 2022)

Mind Your Solver! On Adversarial Attack and Defense for Combinatorial Optimization. - Han Lu; Zenan Li; Runzhong Wang; Qibing Ren; Junchi Yan; Xiaokang Yang 001 (CoRR, 2022)

Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem With Extension to Hypergraph and Multiple-Graph Matching. - Runzhong Wang; Junchi Yan; Xiaokang Yang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Deep Learning of Partial Graph Matching via Differentiable Top-K. - Runzhong Wang; Ziao Guo; Shaofei Jiang; Xiaokang Yang 001; Junchi Yan (CVPR, 2023)

MHSCNET: A Multimodal Hierarchical Shot-Aware Convolutional Network for Video Summarization. - Wujiang Xu; Runzhong Wang; Xiaobo Guo; Shaoshuai Li; Qiongxu Ma; Yunan Zhao; Sheng Guo 005; Zhenfeng Zhu; Junchi Yan (ICASSP, 2023)

Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching. - Chang Liu 021; Zetian Jiang; Runzhong Wang; Lingxiao Huang; Pinyan Lu; Junchi Yan (ICLR, 2023)

ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs. - Han Lu; Zenan Li; Runzhong Wang; Qibing Ren; Xijun Li; Mingxuan Yuan; Jia Zeng; Xiaokang Yang 001; Junchi Yan (ICLR, 2023)

Towards One-shot Neural Combinatorial Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case. - Runzhong Wang; Li Shen 008; Yiting Chen 003; Xiaokang Yang 001; Dacheng Tao; Junchi Yan (ICLR, 2023)

LinSATNet: The Positive Linear Satisfiability Neural Networks. - Runzhong Wang; Yunhao Zhang; Ziao Guo; Tianyi Chen; Xiaokang Yang 001; Junchi Yan (ICML, 2023)

GAL-VNE: Solving the VNE Problem with Global Reinforcement Learning and Local One-Shot Neural Prediction. - Haoyu Geng; Runzhong Wang; Fei Wu 001; Junchi Yan (KDD, 2023)

From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization. - Yang Li 197; Jinpei Guo; Runzhong Wang; Junchi Yan (NeurIPS, 2023)

Rethinking and Benchmarking Predict-then-Optimize Paradigm for Combinatorial Optimization Problems. - Haoyu Geng; Hang Ruan; Runzhong Wang; Yang Li 197; Yang Wang; Lei Chen 031; Junchi Yan (CoRR, 2023)

Combinatorial Learning of Robust Deep Graph Matching: An Embedding Based Approach. - Runzhong Wang; Junchi Yan; Xiaokang Yang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Unsupervised Learning of Graph Matching With Mixture of Modes via Discrepancy Minimization. - Runzhong Wang; Junchi Yan; Xiaokang Yang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

InstaBoost++: Visual Coherence Principles for Unified 2D/3D Instance Level Data Augmentation. - Jianhua Sun 003; Haoshu Fang; Yuxuan Li; Runzhong Wang; Minghao Gou; Cewu Lu (Int. J. Comput. Vis., 2023)

LLMCO4MR: LLMs-Aided Neural Combinatorial Optimization for Ancient Manuscript Restoration from Fragments with Case Studies on Dunhuang. - Yuqing Zhang; Hangqi Li; Shengyu Zhang 001; Runzhong Wang; Baoyi He; Huaiyong Dou; Junchi Yan; Yongquan Zhang; Fei Wu 001 (ECCV (75), 2024)

GMTR: Graph Matching Transformers. - Jinpei Guo; Shaofeng Zhang; Runzhong Wang; Chang Liu 021; Junchi Yan (ICASSP, 2024)

MixSATGEN: Learning Graph Mixing for SAT Instance Generation. - Xinyan Chen; Yang Li 197; Runzhong Wang; Junchi Yan (ICLR, 2024)

Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime. - Haoyu Geng; Hang Ruan; Runzhong Wang; Yang Li 197; Yang Wang; Lei Chen 031; Junchi Yan (NeurIPS, 2024)

Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization. - Yang Li 197; Jinpei Guo; Runzhong Wang; Hongyuan Zha; Junchi Yan (NeurIPS, 2024)

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search. - Kevin Yu; Jihye Roh; Ziang Li; Wenhao Gao 001; Runzhong Wang; Connor W. Coley (NeurIPS, 2024)

Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions. - Wujiang Xu; Qitian Wu; Runzhong Wang; Mingming Ha; Qiongxu Ma; Linxun Chen; Bing Han 023; Junchi Yan (WWW, 2024)

Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural Networks. - Runzhong Wang; Yang Li 197; Junchi Yan; Xiaokang Yang 001 (CoRR, 2024)

Batched Bayesian optimization with correlated candidate uncertainties. - Jenna C. Fromer; Runzhong Wang; Mrunali Manjrekar; Austin Tripp; José Miguel Hernández-Lobato; Connor W. Coley (CoRR, 2024)

Pygmtools: A Python Graph Matching Toolkit. - Runzhong Wang; Ziao Guo; Wenzheng Pan; Jiale Ma; Yikai Zhang; Nan Yang; Qi Liu; Longxuan Wei; Hanxue Zhang; Chang Liu 021; Zetian Jiang; Xiaokang Yang 001; et al. (J. Mach. Learn. Res., 2024)

Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search. - Yang Li 197; Jiale Ma; Wenzheng Pan; Runzhong Wang; Haoyu Geng; Nianzu Yang; Junchi Yan (ICLR, 2025)

Unified and Generalizable Reinforcement Learning for Facility Location Problems on Graphs. - Wenxuan Guo; Runzhong Wang; Yanyan Xu 002; Yaohui Jin (WWW, 2025)

Batched Bayesian Optimization by Maximizing the Probability of Including the Optimum. - Jenna C. Fromer; Runzhong Wang; Mrunali Manjrekar; Austin Tripp; José Miguel Hernández-Lobato; Connor W. Coley (J. Chem. Inf. Model., 2025)

On the Expressive Power of Subgraph Graph Neural Networks for Graphs with Bounded Cycles. - Ziang Chen; Qiao Zhang; Runzhong Wang (CoRR, 2025)

DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra. - Montgomery Bohde; Mrunali Manjrekar; Runzhong Wang; Shuiwang Ji; Connor W. Coley (CoRR, 2025)

Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning. - Runzhong Wang; Rui-Xi Wang; Mrunali Manjrekar; Connor W. Coley (CoRR, 2025)

Optimization of Robotic Liquid Handling as a Capacitated Vehicle Routing Problem. - Guangqi Wu; Runzhong Wang; Connor W. Coley (CoRR, 2025)