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Jiaxin Shi
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Cited by
Cited by
Year
Towards better analysis of deep convolutional neural networks
M Liu, J Shi, Z Li, C Li, J Zhu, S Liu
IEEE transactions on visualization and computer graphics 23 (1), 91-100, 2016
4242016
Functional variational bayesian neural networks
S Sun*, G Zhang*, J Shi*, R Grosse
International Conference on Learning Representations, 2019
1752019
Sliced score matching: A scalable approach to density and score estimation
Y Song*, S Garg*, J Shi, S Ermon
Uncertainty in Artificial Intelligence, 574-584, 2020
802020
Plenopatch: Patch-based plenoptic image manipulation
FL Zhang, J Wang, E Shechtman, ZY Zhou, JX Shi, SM Hu
IEEE transactions on visualization and computer graphics 23 (5), 1561-1573, 2016
752016
A spectral approach to gradient estimation for implicit distributions
J Shi, S Sun, J Zhu
International Conference on Machine Learning, 4644-4653, 2018
662018
Message passing Stein variational gradient descent
J Zhuo, C Liu, J Shi, J Zhu, N Chen, B Zhang
International Conference on Machine Learning, 6018-6027, 2018
522018
Kernel implicit variational inference
J Shi*, S Sun*, J Zhu
International Conference on Learning Representations, 2017
462017
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
382017
Sparse orthogonal variational inference for Gaussian processes
J Shi, M Titsias, A Mnih
International Conference on Artificial Intelligence and Statistics, 1932-1942, 2020
322020
Semi-crowdsourced clustering with deep generative models
Y Luo, T Tian, J Shi, J Zhu, B Zhang
Advances in Neural Information Processing Systems 31, 2018
162018
Scalable training of inference networks for gaussian-process models
J Shi, ME Khan, J Zhu
International Conference on Machine Learning, 5758-5768, 2019
152019
Nonparametric score estimators
Y Zhou, J Shi, J Zhu
International Conference on Machine Learning, 11513-11522, 2020
112020
Sampling with Mirrored Stein Operators
J Shi, C Liu, L Mackey
International Conference on Learning Representations, 2021
52021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
S Sun, J Shi, AG Wilson, R Grosse
International Conference on Machine Learning, 2021
22021
Gradient Estimation with Discrete Stein Operators
J Shi, Y Zhou, J Hwang, MK Titsias, L Mackey
arXiv preprint arXiv:2202.09497, 2022
12022
Double control variates for gradient estimation in discrete latent variable models
MK Titsias, J Shi
arXiv preprint arXiv:2111.05300, 2021
12021
Neural Networks as Inter-Domain Inducing Points
S Sun, J Shi, RB Grosse
Third Symposium on Advances in Approximate Bayesian Inference, 2020
12020
Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
M Titsias, J Shi
International Conference on Artificial Intelligence and Statistics, 6134-6151, 2022
2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Z Deng, J Shi, J Zhu
arXiv preprint arXiv:2205.00165, 2022
2022
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Articles 1–19