Kaiwen Wu - RankMe

35 papers A* 9A 3Journal 18Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Knowledge Gradient for Preference Learning. CoRR Kaiwen Wu, Jacob R. Gardner
2025	J	`jnl`	Estimating the Material Footprint at the National Level from 1993 to 2022 Based on Multi-Feature CNN-BiLSTM. ISPRS Int. J. Geo Inf. LiZhi Miao, Yannan Wang, Kaiwen Wu, Lei Huang, Mei-Po Kwan
2025	J	`jnl`	Mixed Likelihood Variational Gaussian Processes. CoRR Kaiwen Wu, Craig Sanders, Benjamin Letham, Phillip Guan
2025	J	`jnl`	Spatiotemporal hybrid deep learning for estimating and analyzing carbon stocks: a case study in Jiangsu province, China. Int. J. Digit. Earth LiZhi Miao, Jvmin Wang, Kaiwen Wu, Heng Xu, Xiying Sun, Gang Lu, Mei-Po Kwan
2024	J	`jnl`	A Fast, Robust Elliptical Slice Sampling Implementation for Linearly Truncated Multivariate Normal Distributions. CoRR Kaiwen Wu, Jacob R. Gardner
2024	A*	`conf`	Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference. NeurIPS Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob R. Gardner, Geoff Pleiss, John P. Cunningham
2024	J	`jnl`	Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference. CoRR Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob R. Gardner, Geoff Pleiss, John P. Cunningham
2024	A	`conf`	Large-Scale Gaussian Processes via Alternating Projection. AISTATS Kaiwen Wu, Jonathan Wenger, Haydn Thomas Jones, Geoff Pleiss, Jacob R. Gardner
2024	A*	`conf`	Understanding Stochastic Natural Gradient Variational Inference. ICML Kaiwen Wu, Jacob R. Gardner
2024	J	`jnl`	Understanding Stochastic Natural Gradient Variational Inference. CoRR Kaiwen Wu, Jacob R. Gardner
2023	J	`jnl`	Black-Box Variational Inference Converges. CoRR Kyurae Kim, Kaiwen Wu, Jisu Oh, Yi-An Ma, Jacob R. Gardner
2023	—	`conf`	Crop Type Classification Network for Hyperspectral Images Coupled with Agricultural Vegetation Indices. Agro-Geoinformatics Shuai Zhang, Yonghua Jiang, Chengjun Wang, Weiling Liu, Da Li, Kaiwen Wu
2023	A	`conf`	Discovering Many Diverse Solutions with Bayesian Optimization. AISTATS Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner
2023	J	`jnl`	Large-Scale Gaussian Processes via Alternating Projection. CoRR Kaiwen Wu, Jonathan Wenger, Haydn Thomas Jones, Geoff Pleiss, Jacob R. Gardner
2023	—	`conf`	Multi-scale Residual Spatial-Spectral Attention Longan-Litchi Extraction Network for Cultivated Land Non-grain Monitoring. Agro-Geoinformatics Yingshan Xue, Yonghua Jiang, Chengjun Wang, Kaiwen Wu, Xiaoxiao Zhang, Weiling Liu
2023	A*	`conf`	On the Convergence of Black-Box Variational Inference. NeurIPS Kyurae Kim, Jisu Oh, Kaiwen Wu, Yi-An Ma, Jacob R. Gardner
2023	A*	`conf`	Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference. ICML Kyurae Kim, Kaiwen Wu, Jisu Oh, Jacob R. Gardner
2023	J	`jnl`	Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference. CoRR Kyurae Kim, Kaiwen Wu, Jisu Oh, Jacob R. Gardner
2023	—	`conf`	Resident-Based Store Recommendation Model for Community Commercial Planning. ADMA (1) Kaiwen Wu, Yanhu Li, Xiaofeng He
2023	A*	`conf`	The Behavior and Convergence of Local Bayesian Optimization. NeurIPS Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob R. Gardner
2023	J	`jnl`	The Behavior and Convergence of Local Bayesian Optimization. CoRR Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob R. Gardner
2023	A*	`conf`	Variational Gaussian Processes with Decoupled Conditionals. NeurIPS Xinran Zhu, Kaiwen Wu, Natalie Maus, Jacob R. Gardner, David Bindel
2022	J	`jnl`	Discovering Many Diverse Solutions with Bayesian Optimization. CoRR Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner
2022	J	`jnl`	Dynamic adversarial domain adaptation based on multikernel maximum mean discrepancy for breast ultrasound image classification. Expert Syst. Appl. Bo Xu, Kaiwen Wu, Ying Wu, Jie He, Chaoyi Chen
2022	A*	`conf`	Local Bayesian optimization via maximizing probability of descent. NeurIPS Quan Nguyen, Kaiwen Wu, Jacob R. Gardner, Roman Garnett
2022	J	`jnl`	Local Bayesian optimization via maximizing probability of descent. CoRR Quan Nguyen, Kaiwen Wu, Jacob R. Gardner, Roman Garnett
2022	—	`conf`	Research on Ultrasonic Image Segmentation of Thyroid Nodules Based on Improved U-net++. BIC Chaoyi Chen, Bo Xu, Ying Wu, Kaiwen Wu, Cuier Tan
2020	J	`jnl`	Newton-type Methods for Minimax Optimization. CoRR Guojun Zhang, Kaiwen Wu, Pascal Poupart, Yaoliang Yu
2020	A	`conf`	On Minimax Optimality of GANs for Robust Mean Estimation. AISTATS Kaiwen Wu, Gavin Weiguang Ding, Ruitong Huang, Yaoliang Yu
2020	A*	`conf`	Stronger and Faster Wasserstein Adversarial Attacks. ICML Kaiwen Wu, Allen Houze Wang, Yaoliang Yu
2020	J	`jnl`	Stronger and Faster Wasserstein Adversarial Attacks. CoRR Kaiwen Wu, Allen Houze Wang, Yaoliang Yu
2019	A*	`conf`	Distributional Reinforcement Learning for Efficient Exploration. ICML Borislav Mavrin, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu
2019	J	`jnl`	Distributional Reinforcement Learning for Efficient Exploration. CoRR Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu
2019	J	`jnl`	Understanding Adversarial Robustness: The Trade-off between Minimum and Average Margin. CoRR Kaiwen Wu, Yaoliang Yu
2016	—	`conf`	Research and practice of time-sharing device sharing mechanism in remote embedded experiment platform. ICNC-FSKD Kaiwen Wu, Yanmei Jin