Xuechen Li
Title
Cited by
Cited by
Year
Isolating sources of disentanglement in variational autoencoders
RTQ Chen, X Li, R Grosse, D Duvenaud
arXiv preprint arXiv:1802.04942, 2018
4532018
Inference Suboptimality in Variational Autoencoders
C Cremer, X Li, D Duvenaud
International Conference on Machine Learning, 2018
1402018
Scalable gradients for stochastic differential equations
X Li, TKL Wong, RTQ Chen, D Duvenaud
International Conference on Artificial Intelligence and Statistics, 3870-3882, 2020
55*2020
Stochastic runge-kutta accelerates langevin monte carlo and beyond
X Li, D Wu, L Mackey, MA Erdogdu
arXiv preprint arXiv:1906.07868, 2019
252019
When Does Preconditioning Help or Hurt Generalization?
S Amari, J Ba, R Grosse, X Li, A Nitanda, T Suzuki, D Wu, J Xu
arXiv preprint arXiv:2006.10732, 2020
52020
Neural sdes as infinite-dimensional gans
P Kidger, J Foster, X Li, H Oberhauser, T Lyons
arXiv preprint arXiv:2102.03657, 2021
22021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
W Xu, RTQ Chen, X Li, D Duvenaud
arXiv preprint arXiv:2102.06559, 2021
2021
The idemetric property: when most distances are (almost) the same
G Barmpalias, N Huang, A Lewis-Pye, A Li, X Li, Y Pan, T Roughgarden
Proceedings of the Royal Society A, 2019
2019
Isolating Sources of Disentanglement in VAEs
RTQ Chen, X Li, R Grosse, D Duvenaud
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Articles 1–9