Yingzhen Li 个人学术档案 - 学术资源搜索

引用次数

	总计	2019 年至今
引用	3568	3147
h 指数	20	20
i10 指数	29	26

660

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495

20162017201820192020202120222023202447 122 229 337 523 643 639 649 356

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Richard E TurnerProfessor, University of Cambridge在 cam.ac.uk 的电子邮件经过验证
José Miguel Hernández-LobatoProfessor of Machine Learning, University of Cambridge在 cam.ac.uk 的电子邮件经过验证
Thang D BuiLecturer, Australian National University在 anu.edu.au 的电子邮件经过验证
Daniel Hernández-LobatoAssociate Professor, Universidad Autónoma de Madrid在 uam.es 的电子邮件经过验证
Stephan MandtAssociate Professor, University of California, Irvine在 uci.edu 的电子邮件经过验证
Cuong V. NguyenDurham University在 durham.ac.uk 的电子邮件经过验证
Cheng ZhangPrincipal Researcher, Microsoft Research, Cambridge, UK在 kth.se 的电子邮件经过验证
Andrew Y. K. FoongSenior Researcher, Microsoft Research在 microsoft.com 的电子邮件经过验证
Wenbo GongMicrosoft Research在 microsoft.com 的电子邮件经过验证
Yarin GalAssociate Professor, University of Oxford在 cs.ox.ac.uk 的电子邮件经过验证
Ehsan ShareghiAssistant Professor, Monash University在 monash.edu 的电子邮件经过验证
Mark RowlandResearch Scientist, Google DeepMind在 google.com 的电子邮件经过验证
Qiang LiuAssistant Professor of Computer Science, UT Austin在 cs.utexas.edu 的电子邮件经过验证
Sam DevlinMicrosoft Research Cambridge在 microsoft.com 的电子邮件经过验证
Maximilian IglWaymo Research在 eng.ox.ac.uk 的电子邮件经过验证
Katja HofmannMicrosoft Research在 microsoft.com 的电子邮件经过验证
Kamil CiosekSpotify在 spotify.com 的电子邮件经过验证
Sebastian TschiatschekUniversity of Vienna在 univie.ac.at 的电子邮件经过验证
Nate KushmanResearch Scientist, DeepMind在 kushman.org 的电子邮件经过验证
David R. BurtMassachusetts Institute of Technology在 mit.edu 的电子邮件经过验证

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Yingzhen Li

Imperial College London

在 imperial.ac.uk 的电子邮件经过验证 - 首页

Artificial Intelligence Machine Learning Statistics


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Variational Continual Learning CV Nguyen, Y Li, TD Bui, RE Turner	765	2018
Variational Continual Learning CV Nguyen, Y Li, TD Bui, RE Turner arXiv preprint arXiv:1710.10628, 2017	765	2017
Rényi divergence variational inference Y Li, RE Turner Advances in Neural Information Processing Systems, 1073-1081, 2016	319	2016
Disentangled Sequential Autoencoder L Yingzhen, S Mandt International Conference on Machine Learning, 5656-5665, 2018	302*	2018
Deep gaussian processes for regression using approximate expectation propagation T Bui, D Hernández-Lobato, J Hernandez-Lobato, Y Li, R Turner International Conference on Machine Learning, 1472-1481, 2016	265	2016
Black-box α-divergence minimization JM Hernández-Lobato, Y Li, M Rowland, D Hernández-Lobato, TD Bui, ... International Machine Learning Society, 2016	264	2016
Dropout inference in bayesian neural networks with alpha-divergences Y Li, Y Gal Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017	224	2017
Generalization in reinforcement learning with selective noise injection and information bottleneck M Igl, K Ciosek, Y Li, S Tschiatschek, C Zhang, S Devlin, K Hofmann Advances in Neural Information Processing Systems, 13978-13990, 2019	180	2019
Stochastic expectation propagation Y Li, JM Hernández-Lobato, RE Turner Advances in Neural Information Processing Systems, 2323-2331, 2015	153	2015
On the expressiveness of approximate inference in bayesian neural networks A Foong, D Burt, Y Li, R Turner Advances in Neural Information Processing Systems 33, 2020	124	2020
'In-Between'Uncertainty in Bayesian Neural Networks AYK Foong, Y Li, JM Hernández-Lobato, RE Turner arXiv preprint arXiv:1906.11537, 2019	117	2019
Gradient Estimators for Implicit Models Y Li, RE Turner arXiv preprint arXiv:1705.07107, 2017	103	2017
Are generative classifiers more robust to adversarial attacks? Y Li, J Bradshaw, Y Sharma International Conference on Machine Learning, 3804-3814, 2019	99	2019
Variational implicit processes C Ma, Y Li, JM Hernández-Lobato International Conference on Machine Learning, 4222-4233, 2019	79	2019
A causal view on robustness of neural networks C Zhang, K Zhang, Y Li Advances in Neural Information Processing Systems 33, 289-301, 2020	78	2020
Approximate Inference with Amortised MCMC Y Li, RE Turner, Q Liu arXiv preprint arXiv:1702.08343, 2017	63	2017
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data S Lunz, Y Li, A Fitzgibbon, N Kushman arXiv preprint arXiv:2002.12674, 2020	55	2020
Meta-Learning for Stochastic Gradient MCMC W Gong, Y Li, JM Hernández-Lobato arXiv preprint arXiv:1806.04522, 2018	50	2018
Sliced Kernelized Stein Discrepancy W Gong, Y Li, JM Hernández-Lobato arXiv preprint arXiv:2006.16531, 2020	41	2020
On the importance of the Kullback-Leibler divergence term in variational autoencoders for text generation V Prokhorov, E Shareghi, Y Li, MT Pilehvar, N Collier arXiv preprint arXiv:1909.13668, 2019	40	2019

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