| Isolating sources of disentanglement in variational autoencoders RTQ Chen, X Li, RB Grosse, DK Duvenaud Advances in neural information processing systems 31, 2018 | 737 | 2018 |
| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 204 | 2021 |
| Inference Suboptimality in Variational Autoencoders C Cremer, X Li, D Duvenaud International Conference on Machine Learning, 2018 | 197 | 2018 |
| Scalable gradients for stochastic differential equations X Li, TKL Wong, RTQ Chen, D Duvenaud International Conference on Artificial Intelligence and Statistics, 3870-3882, 2020 | 134 | 2020 |
| Stochastic runge-kutta accelerates langevin monte carlo and beyond X Li, Y Wu, L Mackey, MA Erdogdu Advances in neural information processing systems 32, 2019 | 37 | 2019 |
| Neural sdes as infinite-dimensional gans P Kidger, J Foster, X Li, TJ Lyons International Conference on Machine Learning, 5453-5463, 2021 | 21* | 2021 |
| 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 | 16 | 2020 |
| Scalable gradients and variational inference for stochastic differential equations X Li, TKL Wong, RTQ Chen, DK Duvenaud Symposium on Advances in Approximate Bayesian Inference, 1-28, 2020 | 15 | 2020 |
| Large language models can be strong differentially private learners X Li, F Tramer, P Liang, T Hashimoto arXiv preprint arXiv:2110.05679, 2021 | 14 | 2021 |
| Infinitely deep bayesian neural networks with stochastic differential equations W Xu, RTQ Chen, X Li, D Duvenaud International Conference on Artificial Intelligence and Statistics, 721-738, 2022 | 10 | 2022 |
| Efficient and accurate gradients for neural sdes P Kidger, J Foster, XC Li, T Lyons Advances in Neural Information Processing Systems 34, 2021 | 4 | 2021 |
| Learning to Extend Program Graphs to Work-in-Progress Code X Li, CJ Maddison, D Tarlow arXiv preprint arXiv:2105.14038, 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 Proceedings of the 32nd International Conference on Neural Information …, 2019 | | 2019 |
