Wenda Zhou - RankMe

25 papers A* 4A 2B 1Journal 17Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Competitive Programming with Large Reasoning Models. CoRR Ahmed El-Kishky, Alexander Wei, Andre Saraiva, Borys Minaiev, Daniel Selsam, David Dohan, Francis Song, Hunter Lightman, Ignasi Clavera Gilaberte, Jakub Pachocki, Jerry Tworek, Lorenz Kuhn, Lukasz Kaiser, Mark Chen, Max Schwarzer, Mostafa Rohaninejad, Nat McAleese, o3 contributors, Oleg Mürk, Rhythm Garg, Rui Shu, Szymon Sidor, Vineet Kosaraju, Wenda Zhou
2024	J	`jnl`	Corrections to "Compressed Sensing in the Presence of Speckle Noise". IEEE Trans. Inf. Theory Wenda Zhou, Shirin Jalali, Arian Maleki
2024	J	`jnl`	Versatile Cataract Fundus Image Restoration Model Utilizing Unpaired Cataract and High-quality Images. CoRR Zheng Gong, Zhuo Deng, Weihao Gao, Wenda Zhou, Yuhang Yang, Hanqing Zhao, Zhiyuan Niu, Lei Shao, Wen-Bin Wei, Lan Ma
2023	J	`jnl`	Retinal photograph-based deep learning system for detection of hyperthyroidism: a multicenter, diagnostic study. J. Big Data Li Dong, Lie Ju, Shiqi Hui, Lihua Luo, Xue Jiang, Zihan Nie, Ruiheng Zhang, Wenda Zhou, Heyan Li, Jost B. Jonas, Xin Wang, Xin Zhao, Chao He, Yuzhong Chen, Zhaohui Wang, Jianxiong Gao, Zongyuan Ge, Wenbin Wei, Dongmei Li
2022	J	`jnl`	Compressed Sensing in the Presence of Speckle Noise. IEEE Trans. Inf. Theory Wenda Zhou, Shirin Jalali, Arian Maleki
2022	J	`jnl`	Deep Learning for Automatic Detection of Recurrent Retinal Detachment after Surgery Using Ultra-Widefield Fundus Images: A Single-Center Study. Adv. Intell. Syst. Wenda Zhou, Li Dong, Kai Zhang, Qian Wang, Lei Shao, Qiong Yang, Yueming Liu, Li-Jian Fang, Xu-Han Shi, Chuan Zhang, Ruiheng Zhang, He-Yan Li, Hao-Tian Wu, Wen-Bin Wei
2022	A*	`conf`	Vitruvion: A Generative Model of Parametric CAD Sketches. ICLR Ari Seff, Wenda Zhou, Nick Richardson, Ryan P. Adams
2021	A*	`conf`	Autobahn: Automorphism-based Graph Neural Nets. NeurIPS Erik H. Thiede, Wenda Zhou, Risi Kondor
2021	J	`jnl`	Autobahn: Automorphism-based Graph Neural Nets. CoRR Erik Henning Thiede, Wenda Zhou, Risi Kondor
2021	J	`jnl`	Compressed sensing in the presence of speckle noise. CoRR Wenda Zhou, Shirin Jalali, Arian Maleki
2021	J	`jnl`	Vitruvion: A Generative Model of Parametric CAD Sketches. CoRR Ari Seff, Wenda Zhou, Nick Richardson, Ryan P. Adams
2020	A	`conf`	Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions. AISTATS Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki
2020	J	`jnl`	Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions. CoRR Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki
2020	J	`jnl`	SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design. CoRR Ari Seff, Yaniv Ovadia, Wenda Zhou, Ryan P. Adams
2019	J	`jnl`	Denoising of structured random processes. CoRR Wenda Zhou, Shirin Jalali
2019	A*	`conf`	Discrete Object Generation with Reversible Inductive Construction. NeurIPS Ari Seff, Wenda Zhou, Farhan N. Damani, Abigail G. Doyle, Ryan P. Adams
2019	J	`jnl`	Discrete Object Generation with Reversible Inductive Construction. CoRR Ari Seff, Wenda Zhou, Farhan N. Damani, Abigail G. Doyle, Ryan P. Adams
2019	A	`conf`	Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data. AISTATS Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz
2019	—	`conf`	Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach. ICLR (Poster) Wenda Zhou, Victor Veitch, Morgane Austern, Ryan P. Adams, Peter Orbanz
2019	B	`conf`	Towards theoretically-founded learning-based denoising. ISIT Wenda Zhou, Shirin Jalali
2018	A*	`conf`	Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions. ICML Shuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, Vahab S. Mirrokni
2018	J	`jnl`	Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions. CoRR Shuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, Vahab S. Mirrokni
2018	J	`jnl`	Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems. CoRR Shuaiwen Wang, Wenda Zhou, Arian Maleki, Haihao Lu, Vahab S. Mirrokni
2018	J	`jnl`	Compressibility and Generalization in Large-Scale Deep Learning. CoRR Wenda Zhou, Victor Veitch, Morgane Austern, Ryan P. Adams, Peter Orbanz
2018	J	`jnl`	Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data. CoRR Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz