Real-time collection and analysis of 3-Kinect v2 skeleton data in a single application. - Serguei A. Mokhov; Miao Song 001; Jonathan Llewellyn; Jie Zhang; Alexander Charette; Ruofan Wu; Shuiying Ge (SIGGRAPH Posters, 2016)

CapelliniSpTRSV: A Thread-Level Synchronization-Free Sparse Triangular Solve on GPUs. - Jiya Su; Feng Zhang 007; Weifeng Liu 002; Bingsheng He; Ruofan Wu; Xiaoyong Du 001; Rujia Wang (ICPP, 2020)

Self-supervised Representation Learning on Dynamic Graphs. - Sheng Tian; Ruofan Wu; Leilei Shi; Liang Zhu; Tao Xiong (CIKM, 2021)

Exploring deep reuse in winograd CNN inference. - Ruofan Wu; Feng Zhang 007; Zhen Zheng; Xiaoyong Du 001; Xipeng Shen (PPoPP, 2021)

Toward Reliable Designs of Data-Driven Reinforcement Learning Tracking Control for Euler-Lagrange Systems. - Zhikai Yao; Jennie Si; Ruofan Wu; Jianyong Yao (CoRR, 2021)

Reinforcement Learning Enabled Automatic Impedance Control of a Robotic Knee Prosthesis to Mimic the Intact Knee Motion in a Co-Adapting Environment. - Ruofan Wu; Minhan Li; Zhikai Yao; Jennie Si; He Huang 002 (CoRR, 2021)

SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing. - Hui Li 061; Xing Fu; Ruofan Wu; Jinyu Xu; Kai Xiao; Xiaofu Chang; Weiqiang Wang; Shuai Chen; Leilei Shi; Tao Xiong; Yuan Qi 001 (CoRR, 2021)

YuenyeungSpTRSV: A Thread-Level and Warp-Level Fusion Synchronization-Free Sparse Triangular Solve. - Feng Zhang 007; Jiya Su; Weifeng Liu 002; Bingsheng He; Ruofan Wu; Xiaoyong Du 001; Rujia Wang (IEEE Trans. Parallel Distributed Syst., 2021)

GRANDE: a neural model over directed multigraphs with application to anti-money laundering. - Ruofan Wu; Boqun Ma; Hong Jin; Wenlong Zhao 013; Weiqiang Wang; Tianyi Zhang (ICDM, 2022)

Design Domain Specific Neural Network via Symbolic Testing. - Hui Li 061; Xing Fu; Ruofan Wu; Jinyu Xu; Kai Xiao; Xiaofu Chang; Weiqiang Wang; Shuai Chen; Leilei Shi; Tao Xiong; Yuan Qi 001 (KDD, 2022)

TREC: Transient Redundancy Elimination-based Convolution. - Jiawei Guan; Feng Zhang 007; Jiesong Liu; Hsin-Hsuan Sung; Ruofan Wu; Xiaoyong Du 001; Xipeng Shen (NeurIPS, 2022)

Human-Robotic Prosthesis as Collaborating Agents for Symmetrical Walking. - Ruofan Wu; Junmin Zhong; Brent Wallace; Xiang Gao 015; He Huang 002; Jennie Si (NeurIPS, 2022)

ROLLER: Fast and Efficient Tensor Compilation for Deep Learning. - Hongyu Zhu 003; Ruofan Wu; Yijia Diao; Shanbin Ke; Haoyu Li; Chen Zhang 001; Jilong Xue; Lingxiao Ma; Yuqing Xia; Wei Cui; Fan Yang 024; Mao Yang; et al. (OSDI, 2022)

DREW: Efficient Winograd CNN Inference with Deep Reuse. - Ruofan Wu; Feng Zhang 007; Jiawei Guan; Zhen Zheng; Xiaoyong Du 001; Xipeng Shen (WWW, 2022)

GUARD: Graph Universal Adversarial Defense. - Jintang Li; Jie Liao; Ruofan Wu; Liang Chen 001; Changhua Meng; Zibin Zheng; Weiqiang Wang (CoRR, 2022)

MaskGAE: Masked Graph Modeling Meets Graph Autoencoders. - Jintang Li; Ruofan Wu; Wangbin Sun; Liang Chen 001; Sheng Tian; Liang Zhu; Changhua Meng; Zibin Zheng; Weiqiang Wang (CoRR, 2022)

sqSGD: Locally Private and Communication Efficient Federated Learning. - Yan Feng; Tao Xiong; Ruofan Wu; LingJuan Lv; Leilei Shi (CoRR, 2022)

Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems. - Junmin Zhong; Ruofan Wu; Jennie Si (CoRR, 2022)

Robotic Knee Tracking Control to Mimic the Intact Human Knee Profile Based on Actor-Critic Reinforcement Learning. - Ruofan Wu; Zhikai Yao; Jennie Si; He Helen Huang (IEEE CAA J. Autom. Sinica, 2022)

Management and Control of Load Clusters for Ancillary Services Using Internet of Electric Loads Based on Cloud-Edge-End Distributed Computing. - Xin Wu; Lan You; Ruofan Wu; Qi Zhang; Kaixin Liang (IEEE Internet Things J., 2022)

A New Robotic Knee Impedance Control Parameter Optimization Method Facilitated by Inverse Reinforcement Learning. - Wentao Liu; Ruofan Wu; Jennie Si; He Huang 002 (IEEE Robotics Autom. Lett., 2022)

Inferring Human-Robot Performance Objectives During Locomotion Using Inverse Reinforcement Learning and Inverse Optimal Control. - Wentao Liu; Junmin Zhong; Ruofan Wu; Bretta L. Fylstra; Jennie Si; He Helen Huang (IEEE Robotics Autom. Lett., 2022)

Reinforcement Learning Impedance Control of a Robotic Prosthesis to Coordinate With Human Intact Knee Motion. - Ruofan Wu; Minhan Li; Zhikai Yao; Wentao Liu; Jennie Si; He Huang 002 (IEEE Robotics Autom. Lett., 2022)

Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. - Jintang Li; Zhouxin Yu; Zulun Zhu; Liang Chen 001; Qi Yu 001; Zibin Zheng; Sheng Tian; Ruofan Wu; Changhua Meng (AAAI, 2023)

RECom: A Compiler Approach to Accelerating Recommendation Model Inference with Massive Embedding Columns. - Zaifeng Pan; Zhen Zheng; Feng Zhang 007; Ruofan Wu; Hao Liang 003; Dalin Wang; Xiafei Qiu; Junjie Bai; Wei Lin 016; Xiaoyong Du 001 (ASPLOS (4), 2023)

A Momentum Loss Reweighting Method for Improving Recall. - Chenzhi Jiang; Yin Jin; Ningtao Wang; Ruofan Wu; Xing Fu; Weiqiang Wang (CIKM, 2023)

GUARD: Graph Universal Adversarial Defense. - Jintang Li; Jie Liao; Ruofan Wu; Liang Chen 001; Zibin Zheng; Jiawang Dan; Changhua Meng; Weiqiang Wang (CIKM, 2023)

Self-supervision meets kernel graph neural models: From architecture to augmentations. - Jiawang Dan; Ruofan Wu; Yunpeng Liu; Baokun Wang; Changhua Meng; Tengfei Liu; Tianyi Zhang; Ningtao Wang; Xing Fu; Qi Li 002; Weiqiang Wang (ICDM (Workshops), 2023)

What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. - Jintang Li; Ruofan Wu; Wangbin Sun; Liang Chen 001; Sheng Tian; Liang Zhu; Changhua Meng; Zibin Zheng; Weiqiang Wang (KDD, 2023)

Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions. - Ruofan Wu; Jiawei Qiao; Mingzhe Wu; Wen Yu 002; Ming Zheng; Tengfei Liu; Tianyi Zhang; Weiqiang Wang (NeurIPS, 2023)

A Long N-step Surrogate Stage Reward for Deep Reinforcement Learning. - Junmin Zhong; Ruofan Wu; Jennie Si (NeurIPS, 2023)

Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding. - Yuke Hu; Wei Liang; Ruofan Wu; Kai Xiao; Weiqiang Wang; Xiaochen Li; Jinfei Liu; Zhan Qin (WWW, 2023)

DEDGAT: Dual Embedding of Directed Graph Attention Networks for Detecting Financial Risk. - Jiafu Wu; Mufeng Yao; Dong Wu; Mingmin Chi; Baokun Wang; Ruofan Wu; Xin Fu; Changhua Meng; Weiqiang Wang (CoRR, 2023)

Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs. - Jintang Li; Sheng Tian; Ruofan Wu; Liang Zhu; Wenlong Zhao 013; Changhua Meng; Liang Chen 001; Zibin Zheng; Hongzhi Yin (CoRR, 2023)

Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning. - Jintang Li; Wangbin Sun; Ruofan Wu; Yuchang Zhu; Liang Chen 001; Zibin Zheng (CoRR, 2023)

FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural Networks. - Qiying Pan; Ruofan Wu; Tengfei Liu; Tianyi Zhang; Yifei Zhu; Weiqiang Wang (CoRR, 2023)

Self-supervision meets kernel graph neural models: From architecture to augmentations. - Jiawang Dan; Ruofan Wu; Yunpeng Liu; Baokun Wang; Changhua Meng; Tengfei Liu; Tianyi Zhang; Ningtao Wang; Xing Fu; Qi Li; Weiqiang Wang (CoRR, 2023)

Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs. - Jintang Li; Zheng Wei; Jiawang Dan; Jing Zhou; Yuchang Zhu; Ruofan Wu; Baokun Wang; Zhang Zhen; Changhua Meng; Hong Jin; Zibin Zheng; Liang Chen 001 (CoRR, 2023)

Privacy-preserving design of graph neural networks with applications to vertical federated learning. - Ruofan Wu; Mingyang Zhang; Lingjuan Lyu; Xiaolong Xu; Xiuquan Hao; Xinyi Fu; Tengfei Liu; Tianyi Zhang; Weiqiang Wang (CoRR, 2023)

Mitigating Estimation Errors by Twin TD-Regularized Actor and Critic for Deep Reinforcement Learning. - Junmin Zhong; Ruofan Wu; Jennie Si (CoRR, 2023)

LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning. - Jintang Li; Jiawang Dan; Ruofan Wu; Jing Zhou; Sheng Tian; Yunfei Liu; Baokun Wang; Changhua Meng; Weiqiang Wang; Yuchang Zhu; Liang Chen 001; Zibin Zheng (CoRR, 2023)

A two-stage CNN method for MRI image segmentation of prostate with lesion. - Zixuan Wang; Ruofan Wu; Yanran Xu; Yi Liu; Ruimei Chai; He Ma (Biomed. Signal Process. Control., 2023)

Expanding the Edge: Enabling Efficient Winograd CNN Inference With Deep Reuse on Edge Device. - Feng Zhang 007; Ruofan Wu; Jiawei Guan; Zhen Zheng; Xiaoguang Guo; Xiao Zhang 001; Xiaoyong Du 001; Xipeng Shen (IEEE Trans. Knowl. Data Eng., 2023)

A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. - Jintang Li; Huizhe Zhang; Ruofan Wu; Zulun Zhu; Baokun Wang; Changhua Meng; Zibin Zheng; Liang Chen 001 (ICLR, 2024)

Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. - Yunfei Liu; Jintang Li; Yuehe Chen; Ruofan Wu; Ericbk Wang; Jing Zhou; Sheng Tian; Shuheng Shen; Xing Fu; Changhua Meng; Weiqiang Wang; Liang Chen 001 (KDD, 2024)

On provable privacy vulnerabilities of graph representations. - Ruofan Wu; Guanhua Fang; Qiying Pan; Mingyang Zhang; Tengfei Liu; Weiqiang Wang; Wenbiao Zhao (CoRR, 2024)

Actor-Critic Reinforcement Learning with Phased Actor. - Ruofan Wu; Junmin Zhong; Jennie Si (CoRR, 2024)

State Space Models on Temporal Graphs: A First-Principles Study. - Jintang Li; Ruofan Wu; Xinzhou Jin; Boqun Ma; Liang Chen 001; Zibin Zheng (CoRR, 2024)

Ultra-imbalanced classification guided by statistical information. - Yin Jin; Ningtao Wang; Ruofan Wu; Pengfei Shi; Xing Fu; Weiqiang Wang (CoRR, 2024)