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SHENGYANG SUN
SHENGYANG SUN
Applied Scientist, NVIDIA
Verified email at nvidia.com - Homepage
Title
Cited by
Cited by
Year
Functional variational Bayesian neural networks
S Sun, G Zhang, J Shi, R Grosse
arXiv preprint arXiv:1903.05779, 2019
2742019
On the spectral efficiency of massive MIMO systems with low-resolution ADCs
J Zhang, L Dai, S Sun, Z Wang
IEEE Communications Letters 20 (5), 842-845, 2016
2742016
Noisy Natural Gradient as Variational Inference
G Zhang, S Sun, D Duvenaud, R Grosse
International Conference on Machine Learning 2018, 2017
2202017
Learning structured weight uncertainty in bayesian neural networks
S Sun, C Chen, L Carin
International Conference on Artificial Intelligence and Statistics 2017 …, 2017
1312017
A Spectral Approach to Gradient Estimation for Implicit Distributions
J Shi, S Sun, J Zhu
International Conference on Machine Learning 2018, 2018
882018
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
862018
Aggregated momentum: Stability through passive damping
J Lucas, S Sun, R Zemel, R Grosse
arXiv preprint arXiv:1804.00325, 2018
732018
Kernel implicit variational inference
J Shi, S Sun, J Zhu
International Conference on Learning Representations 2018, 2017
592017
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
472017
Information-theoretic online memory selection for continual learning
S Sun, D Calandriello, H Hu, A Li, M Titsias
arXiv preprint arXiv:2204.04763, 2022
372022
Fast-rate PAC-Bayes generalization bounds via shifted Rademacher processes
J Yang, S Sun, DM Roy
Advances in Neural Information Processing Systems 32, 2019
352019
Understanding the variance collapse of SVGD in high dimensions
J Ba, MA Erdogdu, M Ghassemi, S Sun, T Suzuki, D Wu, T Zhang
International Conference on Learning Representations, 2021
162021
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
152021
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
Second Symposium on Advances in Approximate Bayesian Inference, 2019
122019
Scalable variational gaussian processes via harmonic kernel decomposition
S Sun, J Shi, AG Wilson, R Grosse
arXiv preprint arXiv:2106.05992, 2021
52021
Neural networks as inter-domain inducing points
S Sun, J Shi, RB Grosse
Third Symposium on Advances in Approximate Bayesian Inference, 2020
42020
Function-Space Bayesian Learning: from Gaussian Processes to Bayesian Deep Learning
S Sun
University of Toronto (Canada), 2022
2022
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Articles 1–17