Ikuti
Kaiwen Wu
Kaiwen Wu
Email yang diverifikasi di seas.upenn.edu - Beranda
Judul
Dikutip oleh
Dikutip oleh
Tahun
Stronger and faster wasserstein adversarial attacks
K Wu, A Wang, Y Yu
International conference on machine learning, 10377-10387, 2020
352020
Newton-type methods for minimax optimization
G Zhang, K Wu, P Poupart, Y Yu
arXiv preprint arXiv:2006.14592, 2020
302020
Discovering many diverse solutions with Bayesian optimization
N Maus, K Wu, D Eriksson, J Gardner
arXiv preprint arXiv:2210.10953, 2022
252022
On the convergence of black-box variational inference
K Kim, J Oh, K Wu, Y Ma, J Gardner
Advances in Neural Information Processing Systems 36, 44615-44657, 2023
242023
Local Bayesian optimization via maximizing probability of descent
Q Nguyen, K Wu, J Gardner, R Garnett
Advances in neural information processing systems 35, 13190-13202, 2022
242022
On minimax optimality of GANs for robust mean estimation
K Wu, GW Ding, R Huang, Y Yu
International Conference on Artificial Intelligence and Statistics, 4541-4551, 2020
152020
The behavior and convergence of local bayesian optimization
K Wu, K Kim, R Garnett, J Gardner
Advances in neural information processing systems 36, 73497-73523, 2023
132023
Large-scale Gaussian processes via alternating projection
K Wu, J Wenger, HT Jones, G Pleiss, J Gardner
International Conference on Artificial Intelligence and Statistics, 2620-2628, 2024
72024
Practical and matching gradient variance bounds for black-box variational Bayesian inference
K Kim, K Wu, J Oh, JR Gardner
International Conference on Machine Learning, 16853-16876, 2023
62023
Understanding adversarial robustness: The trade-off between minimum and average margin
K Wu, Y Yu
arXiv preprint arXiv:1907.11780, 2019
42019
Variational gaussian processes with decoupled conditionals
X Zhu, K Wu, N Maus, J Gardner, D Bindel
Advances in Neural Information Processing Systems 36, 46191-46211, 2023
22023
Black-box variational inference converges
K Kim, K Wu, J Oh, Y Ma, JR Gardner
arXiv preprint arXiv:2305.15349, 2, 2023
22023
Understanding stochastic natural gradient variational inference
K Wu, JR Gardner
arXiv preprint arXiv:2406.01870, 2024
12024
Mixed Likelihood Variational Gaussian Processes
K Wu, C Sanders, B Letham, P Guan
arXiv preprint arXiv:2503.04138, 2025
2025
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
J Wenger, K Wu, P Hennig, J Gardner, G Pleiss, JP Cunningham
Advances in Neural Information Processing Systems 37, 31316-31349, 2024
2024
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
JP Cunningham, G Pleiss, JR Gardner, P Hennig, K Wu, J Wenger
arXiv, 2024
2024
A Fast, Robust Elliptical Slice Sampling Implementation for Linearly Truncated Multivariate Normal Distributions
K Wu, JR Gardner
arXiv preprint arXiv:2407.10449, 2024
2024
Wasserstein Adversarial Robustness
K Wu
University of Waterloo, 2020
2020
A Fast, Robust Elliptical Slice Sampling Method for Truncated Multivariate Normal Distributions
K Wu, JR Gardner
NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty, 0
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