Deep GDashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. - Jack Lanchantin; Ritambhara Singh; Beilun Wang; Yanjun Qi (CoRR, 2016)

A Theoretical Framework for Robustness of (Deep) Classifiers Under Adversarial Noise. - Beilun Wang; Ji Gao; Yanjun Qi (CoRR, 2016)

A constrained L1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models. - Beilun Wang; Ritambhara Singh; Yanjun Qi (CoRR, 2016)

Kernelized Information-Theoretic Metric Learning for Cancer Diagnosis Using High-Dimensional Molecular Profiling Data. - Feiyu Xiong; Moshe Kam; Leonid Hrebien; Beilun Wang; Yanjun Qi (ACM Trans. Knowl. Discov. Data, 2016)

A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. - Beilun Wang; Ji Gao; Yanjun Qi (AISTATS, 2017)

DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples. - Ji Gao; Beilun Wang; Zeming Lin; Weilin Xu; Yanjun Qi (ICLR (Workshop), 2017)

A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Samples. - Beilun Wang; Ji Gao; Yanjun Qi (ICLR (Workshop), 2017)

GaKCo: A Fast Gapped k-mer String Kernel Using Counting. - Ritambhara Singh; Arshdeep Sekhon; Kamran Kowsari; Jack Lanchantin; Beilun Wang; Yanjun Qi (ECML/PKDD (1), 2017)

Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. - Jack Lanchantin; Ritambhara Singh; Beilun Wang; Yanjun Qi (PSB, 2017)

DeepMask: Masking DNN Models for robustness against adversarial samples. - Ji Gao; Beilun Wang; Yanjun Qi (CoRR, 2017)

A Constrained, Weighted-L1 Minimization Approach for Joint Discovery of Heterogeneous Neural Connectivity Graphs. - Chandan Singh; Beilun Wang; Yanjun Qi (CoRR, 2017)

A constrained $$ ell $$ ℓ 1 minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models. - Beilun Wang; Ritambhara Singh; Yanjun Qi (Mach. Learn., 2017)

Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. - Beilun Wang; Arshdeep Sekhon; Yanjun Qi (AISTATS, 2018)

A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. - Beilun Wang; Arshdeep Sekhon; Yanjun Qi (ICML, 2018)

Sparse and Low-Rank Tensor Regression via Parallel Proximal Method. - Jiaqi Zhang; Beilun Wang (CoRR, 2019)

Fast and Scalable Estimator for Sparse and Unit-Rank Higher-Order Regression Models. - Jiaqi Zhang; Beilun Wang (CoRR, 2019)

An OpenCV-based Framework for Table Information Extraction. - Jiayi Yuan; Hongye Li; Meng Wang; Ruyang Liu; Chuanyou Li; Beilun Wang (ICKG, 2020)

Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables. - Jiaqi Zhang; Meng Wang 009; Qinchi Li; Sen Wang 001; Xiaojun Chang; Beilun Wang (IJCAI, 2020)

How Decisions Are Made in Brains: Unpack "Black Box" of CNN With Ms. Pac-Man Video Game. - Beilun Wang; Rui Ma; Jingyu Kuang; Yan Zhang 100 (IEEE Access, 2020)

Differential Network Learning Beyond Data Samples. - Arshdeep Sekhon; Beilun Wang; Zhe Wang 025; Yanjun Qi (CoRR, 2020)

Cascade and Fusion: A Deep Learning Approach for Camouflaged Object Sensing. - Kaihong Huang; Chunshu Li; Jiaqi Zhang; Beilun Wang (Sensors, 2021)

Scalable Estimator for Multi-task Gaussian Graphical Models Based in an IoT Network. - Beilun Wang; Jiaqi Zhang; Yan Zhang 100; Meng Wang 009; Sen Wang 001 (ACM Trans. Sens. Networks, 2021)

A Difference Standardization Method for Mutual Transfer Learning. - Haoqing Xu; Meng Wang; Beilun Wang (ICML, 2022)

Fast and scalable learning of sparse changes in high-dimensional graphical model structure. - Beilun Wang; Jiaqi Zhang; Haoqing Xu; Te Tao (Neurocomputing, 2022)

TKGAT: Graph attention network for knowledge-enhanced tag-aware recommendation system. - Beilun Wang; Haoqing Xu; Chunshu Li; Yuchen Li 011; Meng Wang (Knowl. Based Syst., 2022)

Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data. - Xiao Tan 005; Yangyang Shen; Meng Wang 009; Beilun Wang (CIKM, 2023)

Applying Robust Gradient Difference Compression to Federated Learning. - Yueyao Chen; Beilun Wang; Tianyi Ma; Cheng Chen (CSCWD, 2023)

A Robust Framework for Fixing The Vulnerability of Compressed Distributed Learning. - Yueyao Chen; Beilun Wang; Yan Zhang 100; Jingyu Kuang (CSCWD, 2023)

A Framework Using Absolute Compression Hard-Threshold for Improving The Robustness of Federated Learning Model. - Yuzhang Wu; Beilun Wang (CSCWD, 2023)

Take CARE: Improving Inherent Robustness of Spiking Neural Networks with Channel-wise Activation Recalibration Module. - Yan Zhang 100; Cheng Chen; Dian Shen; Meng Wang 009; Beilun Wang (ICDM, 2023)

Collaborative Estimating Multiple Gaussian Graphical Models on Resource Constrained Devices in IoT Networks. - Ying Zhan 001; Beilun Wang (SMC, 2023)

Label Information Enhanced Fraud Detection against Low Homophily in Graphs. - Yuchen Wang; Jinghui Zhang; Zhengjie Huang; Weibin Li; Shikun Feng; Ziheng Ma; Yu Sun 029; Dianhai Yu; Fang Dong 001; Jiahui Jin; Beilun Wang; Junzhou Luo (WWW, 2023)

Factor Model-Based Large Covariance Estimation from Streaming Data Using a Knowledge-Based Sketch Matrix. - Xiao Tan 005; Zhaoyang Wang; Hao Qian 003; Jun Zhou 011; Peibo Duan; Dian Shen; Meng Wang 009; Beilun Wang (CIKM, 2024)

A Privacy-Preserving Method for Sequential Recommendation in Vertical Federated Learning. - Yutian Shi; Beilun Wang (CSCWD, 2024)

Hynify: A High-throughput and Unified Accelerator for Multi-Mode Nonparametric Statistics. - Kaihong Huang; Dian Shen; Zhaoyang Wang; Juntao Yang; Beilun Wang (DAC, 2024)

Large Covariance Estimation from Streaming Data with Knowledge-Based Sketch Matrix. - Xiao Tan 005; Zhaoyang Wang; Meng Wang 009; Dian Shen; Weitong Chen 001; Beilun Wang (DASFAA (5), 2024)

Adaptive Group Personalization for Federated Mutual Transfer Learning. - Haoqing Xu; Dian Shen; Meng Wang 009; Beilun Wang (ICML, 2024)

FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings. - Xiao Tan 005; Yiqin Wang; Yangyang Shen; Dian Shen; Meng Wang 009; Peibo Duan; Beilun Wang (NeurIPS, 2024)

Exploiting biochemical data to improve osteosarcoma diagnosis with deep learning. - Shidong Wang; Yangyang Shen; Fanwei Zeng; Meng Wang 009; Bohan Li 001; Dian Shen; Xiaodong Tang; Beilun Wang (Health Inf. Sci. Syst., 2024)

eNetSTL: Towards an In-kernel Library for High-Performance eBPF-based Network Functions. - Bin Yang 027; Dian Shen; Junxue Zhang 001; Hanlin Yang; Lunqi Zhao; Beilun Wang; Guyue Liu; Kai Chen 005 (EuroSys, 2025)

HyperCom: Enabling High Performance and Composable Data Structures for Software Network Functions with eBPF. - Bin Yang 027; Dian Shen; Hanlin Yang; Lunqi Zhao; Jianrui Liu; Jiantao Cheng; Beilun Wang (INFOCOM, 2025)

NoTeNet: Normalized Mutual Information-Driven Tuning-free Dynamic Dependence Network Inference Method for Multimodal Data. - Xiao Tan 005; Yangyang Shen; Yan Zhang 100; Jingwen Shao; Dian Shen; Meng Wang 009; Beilun Wang (WWW, 2025)

Sparse and smooth additive isotonic model in high-dimensional settings. - Jiaqi Zhang; Yiqin Wang; Meng Wang; Beilun Wang (Mach. Learn., 2025)

ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks. - Kai Sun; Peibo Duan; Levin Kuhlmann; Beilun Wang; Bin Zhang 001 (CoRR, 2025)