SHENGYANG SUN
SHENGYANG SUN
在 cs.toronto.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Noisy Natural Gradient as Variational Inference
G Zhang, S Sun, D Duvenaud, R Grosse
International Conference on Machine Learning 2018, 2017
1202017
Functional variational bayesian neural networks
S Sun, G Zhang, J Shi, R Grosse
arXiv preprint arXiv:1903.05779, 2019
1042019
Learning structured weight uncertainty in bayesian neural networks
S Sun, C Chen, L Carin
International Conference on Artificial Intelligence and Statistics 2017 …, 2017
792017
Differentiable Compositional Kernel Learning for Gaussian Processes
S Sun, G Zhang, C Wang, W Zeng, J Li, R Grosse
International Conference on Machine Learning 2018, 2018
462018
A Spectral Approach to Gradient Estimation for Implicit Distributions
J Shi, S Sun, J Zhu
International Conference on Machine Learning 2018, 2018
432018
Kernel implicit variational inference
J Shi, S Sun, J Zhu
International Conference on Learning Representations 2018, 2017
352017
ZhuSuan: A library for Bayesian deep learning
J Shi, J Chen, J Zhu, S Sun, Y Luo, Y Gu, Y Zhou
arXiv preprint arXiv:1709.05870, 2017
322017
Aggregated momentum: Stability through passive damping
J Lucas, S Sun, R Zemel, R Grosse
arXiv preprint arXiv:1804.00325, 2018
302018
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes.
J Yang, S Sun, DM Roy
NeurIPS, 10802-10812, 2019
82019
Towards Characterizing the High-dimensional Bias of Kernel-based Particle Inference Algorithms
J Ba, MA Erdogdu, M Ghassemi, T Suzuki, S Sun, D Wu, T Zhang
12019
Neural Networks as Inter-Domain Inducing Points
S Sun, J Shi, R Grosse
1
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
S Sun, J Shi, AG Wilson, R Grosse
arXiv preprint arXiv:2106.05992, 2021
2021
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
C Wang, S Sun, R Grosse
International Conference on Artificial Intelligence and Statistics, 2476-2484, 2021
2021
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