Bao Wang - RankMe

89 papers A* 17A 1C 1Misc 1Journal 60Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep Learning With Data Privacy via Residual Perturbation. IEEE Trans. Pattern Anal. Mach. Intell. Wenqi Tao, Huaming Ling, Zuoqiang Shi, Bao Wang
2026	J	`jnl`	Improving Flow Matching by Aligning Flow Divergence. CoRR Yuhao Huang, Taos Transue, Shih-Hsin Wang, William M. Feldman, Hong Zhang, Bao Wang
2026	—	`conf`	On Saddle Point Avoidance and Stationary Distribution of Sharpness-Aware Minimization. KDD (1) Tao Sun, Fan Jia, Bao Wang
2026	J	`jnl`	RMFlow: Refined Mean Flow by a Noise-Injection Step for Multimodal Generation. CoRR Yuhao Huang, Shih-Hsin Wang, Andrea L. Bertozzi, Bao Wang
2026	J	`jnl`	Towards Multiscale Graph-based Protein Learning with Geometric Secondary Structural Motifs. CoRR Shih-Hsin Wang, Yuhao Huang, Taos Transue, Justin M. Baker, Jonathan Forstater, Thomas Strohmer, Bao Wang
2025	A*	`conf`	A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules. ICLR Shih-Hsin Wang, Yuhao Huang, Justin M. Baker, Yuan-En Sun, Qi Tang, Bao Wang
2025	A*	`conf`	Improving Flow Matching by Aligning Flow Divergence. ICML Yuhao Huang, Taos Transue, Shih-Hsin Wang, William M. Feldman, Hong Zhang, Bao Wang
2025	A*	`conf`	Investigating the Role of Weight Decay in Enhancing Nonconvex SGD. CVPR Tao Sun, Yuhao Huang, Li Shen, Kele Xu, Bao Wang
2025	J	`jnl`	Plug-and-Play Image Restoration with Flow Matching: A Continuous Viewpoint. CoRR Fan Jia, Yuhao Huang, Shih-Hsin Wang, Cristina Garcia-Cardona, Andrea L. Bertozzi, Bao Wang
2024	A*	`conf`	An Explicit Frame Construction for Normalizing 3D Point Clouds. ICML Justin M. Baker, Shih-Hsin Wang, Tommaso de Fernex, Bao Wang
2024	J	`jnl`	Deep Learning with Data Privacy via Residual Perturbation. CoRR Wenqi Tao, Huaming Ling, Zuoqiang Shi, Bao Wang
2024	A*	`conf`	Efficient Score Matching with Deep Equilibrium Layers. ICLR Yuhao Huang, Qingsong Wang, Akwum Onwunta, Bao Wang
2024	J	`jnl`	Improving Deep Neural Networks' Training for Image Classification With Nonlinear Conjugate Gradient-Style Adaptive Momentum. IEEE Trans. Neural Networks Learn. Syst. Bao Wang, Qiang Ye
2024	J	`jnl`	Learning to Control the Smoothness of Graph Convolutional Network Features. CoRR Shih-Hsin Wang, Justin M. Baker, Cory D. Hauck, Bao Wang
2024	A	`conf`	Monotone Operator Theory-Inspired Message Passing for Learning Long-Range Interaction on Graphs. AISTATS Justin M. Baker, Qingsong Wang, Martin Berzins, Thomas Strohmer, Bao Wang
2024	A*	`conf`	Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks. ICLR Shih-Hsin Wang, Yung-Chang Hsu, Justin M. Baker, Andrea L. Bertozzi, Jack Xin, Bao Wang
2023	J	`jnl`	Accelerated Sparse Recovery via Gradient Descent with Nonlinear Conjugate Gradient Momentum. J. Sci. Comput. Mengqi Hu, Yifei Lou, Bao Wang, Ming Yan, Xiu Yang, Qiang Ye
2023	J	`jnl`	Decentralized Federated Averaging. IEEE Trans. Pattern Anal. Mach. Intell. Tao Sun, Dongsheng Li, Bao Wang
2023	A*	`conf`	Implicit Graph Neural Networks: A Monotone Operator Viewpoint. ICML Justin M. Baker, Qingsong Wang, Cory D. Hauck, Bao Wang
2023	J	`jnl`	Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs. J. Sci. Comput. Justin M. Baker, Elena Cherkaev, Akil Narayan, Bao Wang
2023	A*	`conf`	Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions. ICML Tao Sun, Qingsong Wang, Dongsheng Li, Bao Wang
2023	J	`jnl`	Pairwise Learning with Adaptive Online Gradient Descent. Trans. Mach. Learn. Res. Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang
2022	A*	`conf`	Adaptive Random Walk Gradient Descent for Decentralized Optimization. ICML Tao Sun, Dongsheng Li, Bao Wang
2022	J	`jnl`	Adaptive and Implicit Regularization for Matrix Completion. CoRR Zhemin Li, Tao Sun, Hongxia Wang, Bao Wang
2022	J	`jnl`	Adaptive and Implicit Regularization for Matrix Completion. SIAM J. Imaging Sci. Zhemin Li, Tao Sun, Hongxia Wang, Bao Wang
2022	C	`conf`	Adversarial Attacks on Deep Temporal Point Process. ICMLA Samira Khorshidi, Bao Wang, George O. Mohler
2022	J	`jnl`	Efficient and Reliable Overlay Networks for Decentralized Federated Learning. SIAM J. Appl. Math. Yifan Hua, Kevin S. Miller, Andrea L. Bertozzi, Chen Qian, Bao Wang
2022	A*	`conf`	Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks. NeurIPS Tao Sun, Dongsheng Li, Bao Wang
2022	A*	`conf`	GRAND++: Graph Neural Diffusion with A Source Term. ICLR Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2022	Misc	`conf`	Glassoformer: A Query-Sparse Transformer for Post-Fault Power Grid Voltage Prediction. ICASSP Yunling Zheng, Carson Hu, Guang Lin, Meng Yue, Bao Wang, Jack Xin
2022	J	`jnl`	Learning POD of Complex Dynamics Using Heavy-ball Neural ODEs. CoRR Justin M. Baker, Elena Cherkaev, Akil Narayan, Bao Wang
2022	—	`conf`	Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. MSML Tan Minh Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
2022	J	`jnl`	Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. CoRR Tan M. Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
2022	—	`conf`	Post-Fault Power Grid Voltage Prediction via 1D-CNN with Spatial Coupling. AI4I Carson Hu, Guang Lin, Bao Wang, Meng Yue, Jack Xin
2022	J	`jnl`	Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs. CoRR Justin M. Baker, Hedi Xia, Yiwei Wang, Elena Cherkaev, Akil Narayan, Long Chen, Jack Xin, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2022	J	`jnl`	Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. SIAM J. Imaging Sci. Bao Wang, Tan M. Nguyen, Tao Sun, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2022	J	`jnl`	glassoformer: a query-sparse transformer for post-fault power grid voltage prediction. CoRR Yunling Zheng, Carson Hu, Guang Lin, Meng Yue, Bao Wang, Jack Xin
2021	—	`conf`	An Integrated Approach to Produce Robust Deep Neural Network Models with High Efficiency. LOD Zhijian Li, Bao Wang, Jack Xin
2021	J	`jnl`	Decentralized Federated Averaging. CoRR Tao Sun, Dongsheng Li, Bao Wang
2021	J	`jnl`	Deep Interactive Denoiser (DID) for X-Ray Computed Tomography. IEEE Trans. Medical Imaging Ti Bai, Biling Wang, Dan Nguyen, Bao Wang, Bin Dong, Wenxiang Cong, Mannudeep K. Kalra, Steve B. Jiang
2021	J	`jnl`	Efficient and Reliable Overlay Networks for Decentralized Federated Learning. CoRR Yifan Hua, Kevin Miller, Andrea L. Bertozzi, Chen Qian, Bao Wang
2021	A*	`conf`	FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention. NeurIPS Tan M. Nguyen, Vai Suliafu, Stanley J. Osher, Long Chen, Bao Wang
2021	J	`jnl`	FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention. CoRR Tan M. Nguyen, Vai Suliafu, Stanley J. Osher, Long Chen, Bao Wang
2021	A*	`conf`	Heavy Ball Neural Ordinary Differential Equations. NeurIPS Hedi Xia, Vai Suliafu, Hangjie Ji, Tan M. Nguyen, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2021	J	`jnl`	Heavy Ball Neural Ordinary Differential Equations. CoRR Hedi Xia, Vai Suliafu, Hangjie Ji, Tan M. Nguyen, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2021	J	`jnl`	How Does Momentum Benefit Deep Neural Networks Architecture Design? A Few Case Studies. CoRR Bao Wang, Hedi Xia, Tan M. Nguyen, Stanley J. Osher
2021	J	`jnl`	Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo. SIAM J. Sci. Comput. Bao Wang, Difan Zou, Quanquan Gu, Stanley J. Osher
2021	—	`conf`	Myocardial Ischemia Detection Using Body Surface Potential Mappings and Machine Learning. CinC James N. Brundage, Vai Suliafu, Jake A. Bergquist, Brian Zenger, Lindsay C. Rupp, Bao Wang, Rob S. MacLeod
2021	A*	`conf`	Stability and Generalization of Decentralized Stochastic Gradient Descent. AAAI Tao Sun, Dongsheng Li, Bao Wang
2021	J	`jnl`	Stability and Generalization of the Decentralized Stochastic Gradient Descent. CoRR Tao Sun, Dongsheng Li, Bao Wang
2021	J	`jnl`	Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization. CoRR Tao Sun, Huaming Ling, Zuoqiang Shi, Dongsheng Li, Bao Wang
2020	J	`jnl`	An Integrated Approach to Produce Robust Models with High Efficiency. CoRR Zhijian Li, Bao Wang, Jack Xin
2020	—	`conf`	DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM. MSML Bao Wang, Quanquan Gu, March Boedihardjo, Lingxiao Wang, Farzin Barekat, Stanley J. Osher
2020	J	`jnl`	Deep Interactive Denoiser (DID) for X-Ray Computed Tomography. CoRR Ti Bai, Biling Wang, Dan Nguyen, Bao Wang, Bin Dong, Wenxiang Cong, Mannudeep K. Kalra, Steve B. Jiang
2020	J	`jnl`	EnResNet: ResNets Ensemble via the Feynman-Kac Formalism for Adversarial Defense and Beyond. SIAM J. Math. Data Sci. Bao Wang, Binjie Yuan, Zuoqiang Shi, Stanley J. Osher
2020	J	`jnl`	Exploring Private Federated Learning with Laplacian Smoothing. CoRR Zhicong Liang, Bao Wang, Quanquan Gu, Stanley J. Osher, Yuan Yao
2020	A*	`conf`	MomentumRNN: Integrating Momentum into Recurrent Neural Networks. NeurIPS Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2020	J	`jnl`	MomentumRNN: Integrating Momentum into Recurrent Neural Networks. CoRR Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2020	J	`jnl`	Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. CoRR Bao Wang, Tan M. Nguyen, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2020	—	`conf`	Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets. LOD (2) Thu Dinh, Bao Wang, Andrea L. Bertozzi, Stanley J. Osher, Jack Xin
2020	J	`jnl`	Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets. CoRR Thu Dinh, Bao Wang, Andrea L. Bertozzi, Stanley J. Osher
2019	J	`jnl`	A Deterministic Approach to Avoid Saddle Points. CoRR Lisa Maria Kreusser, Stanley J. Osher, Bao Wang
2019	—	`conf`	A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting. WCGO Zhijian Li, Xiyang Luo, Bao Wang, Andrea L. Bertozzi, Jack Xin
2019	J	`jnl`	A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting. CoRR Zhijian Li, Xiyang Luo, Bao Wang, Andrea L. Bertozzi, Jack Xin
2019	J	`jnl`	DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM. CoRR Bao Wang, Quanquan Gu, March Boedihardjo, Farzin Barekat, Stanley J. Osher
2019	J	`jnl`	Graph Interpolating Activation Improves Both Natural and Robust Accuracies in Data-Efficient Deep Learning. CoRR Bao Wang, Stanley J. Osher
2019	J	`jnl`	Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo. CoRR Bao Wang, Difan Zou, Quanquan Gu, Stanley J. Osher
2019	A*	`conf`	ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies. NeurIPS Bao Wang, Zuoqiang Shi, Stanley J. Osher
2019	—	`conf`	SOS-EW: System for Overdose Spike Early Warning Using Drug Mover's Distance-Based Hawkes Processes. PKDD/ECML Workshops (1) Wen-Hao Chiang, Baichuan Yuan, Hao Li, Bao Wang, Andrea L. Bertozzi, Jeremy G. Carter, Brad Ray, George O. Mohler
2019	J	`jnl`	Stop Memorizing: A Data-Dependent Regularization Framework for Intrinsic Pattern Learning. SIAM J. Math. Data Sci. Wei Zhu, Qiang Qiu, Bao Wang, Jianfeng Lu, Guillermo Sapiro, Ingrid Daubechies
2018	J	`jnl`	Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization. CoRR Bao Wang, Alex Tong Lin, Zuoqiang Shi, Wei Zhu, Penghang Yin, Andrea L. Bertozzi, Stanley J. Osher
2018	J	`jnl`	Breaking the polar-nonpolar division in solvation free energy prediction. J. Comput. Chem. Bao Wang, Chengzhang Wang, Kedi Wu, Guo-Wei Wei
2018	J	`jnl`	Deep Learning with Data Dependent Implicit Activation Function. CoRR Bao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley J. Osher
2018	A*	`conf`	Deep Neural Nets with Interpolating Function as Output Activation. NeurIPS Bao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley J. Osher
2018	J	`jnl`	EnResNet: ResNet Ensemble via the Feynman-Kac Formalism. CoRR Bao Wang, Binjie Yuan, Zuoqiang Shi, Stanley J. Osher
2018	J	`jnl`	Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data. CoRR Bao Wang, Xiyang Luo, Fangbo Zhang, Baichuan Yuan, Andrea L. Bertozzi, P. Jeffrey Brantingham
2018	J	`jnl`	Laplacian Smoothing Gradient Descent. CoRR Stanley J. Osher, Bao Wang, Penghang Yin, Xiyang Luo, Minh Pham, Alex Tong Lin
2018	J	`jnl`	Mathematical Analysis of Adversarial Attacks. CoRR Zehao Dou, Stanley J. Osher, Bao Wang
2018	J	`jnl`	Scientific data interpolation with low dimensional manifold model. J. Comput. Phys. Wei Zhu, Bao Wang, Richard C. Barnard, Cory D. Hauck, Frank Jenko, Stanley J. Osher
2018	J	`jnl`	Stop memorizing: A data-dependent regularization framework for intrinsic pattern learning. CoRR Wei Zhu, Qiang Qiu, Bao Wang, Jianfeng Lu, Guillermo Sapiro, Ingrid Daubechies
2017	J	`jnl`	Accurate, robust, and reliable calculations of Poisson-Boltzmann binding energies. J. Comput. Chem. Duc Duy Nguyen, Bao Wang, Guo-Wei Wei
2017	J	`jnl`	Deep Learning for Real Time Crime Forecasting. CoRR Bao Wang, Duo Zhang, Duanhao Zhang, P. Jeffrey Brantingham, Andrea L. Bertozzi
2017	J	`jnl`	Deep Learning for Real-Time Crime Forecasting and its Ternarization. CoRR Bao Wang, Penghang Yin, Andrea L. Bertozzi, P. Jeffrey Brantingham, Stanley J. Osher, Jack Xin
2017	J	`jnl`	ESES: Software for Eulerian solvent excluded surface. J. Comput. Chem. Beibei Liu, Bao Wang, Rundong Zhao, Yiying Tong, Guo-Wei Wei
2017	J	`jnl`	Feature functional theory - binding predictor (FFT-BP) for the blind prediction of binding free energies. CoRR Bao Wang, Zhixiong Zhao, Duc Duy Nguyen, Guo-Wei Wei
2017	J	`jnl`	Finite volume formulation of the MIB method for elliptic interface problems. J. Comput. Appl. Math. Yin Cao, Bao Wang, Kelin Xia, Guo-Wei Wei
2016	J	`jnl`	Object-oriented persistent homology. J. Comput. Phys. Bao Wang, Guo-Wei Wei
2015	J	`jnl`	Matched interface and boundary method for elasticity interface problems. J. Comput. Appl. Math. Bao Wang, Kelin Xia, Guo-Wei Wei
2015	J	`jnl`	Second order method for solving 3D elasticity equations with complex interfaces. J. Comput. Phys. Bao Wang, Kelin Xia, Guo-Wei Wei