Trevor Campbell 个人学术档案

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Tamara BroderickAssociate Professor of EECS, Massachusetts Institute of Technology在 mit.edu 的电子邮件经过验证
Jonathan P. HowRichard C. Maclaurin Professor of Aerospace Engineering, Massachusetts Institute of Technology在 mit.edu 的电子邮件经过验证
Jonathan HugginsAssistant Professor of Statistics, Boston University在 bu.edu 的电子邮件经过验证
Diana CaiCenter for Computational Mathematics, Flatiron Institute在 flatironinstitute.org 的电子邮件经过验证
Julian StraubResearch Scientist, Reality Labs Research在 csail.mit.edu 的电子邮件经过验证
John W. Fisher IIISenior Research Scientist, Massachusetts Institute of Technology在 csail.mit.edu 的电子邮件经过验证
Zuheng(David) XuPhD student, Department of Statistics, University of British Columnbia在 stat.ubc.ca 的电子邮件经过验证
Mikolaj KasprzakDepartment of Mathematics, University of Luxembourg在 uni.lu 的电子邮件经过验证
Saifuddin SyedUniversity of Oxford在 stats.ox.ac.uk 的电子邮件经过验证
Brian KulisAssociate Professor at Boston University & Amazon Scholar在 bu.edu 的电子邮件经过验证
Reza VaziriProfessor of Civil Engineering, The University of British Columbia在 ubc.ca 的电子邮件经过验证
Ehsan HaghighatHead of Simulations & AI at Eden -- Research Affiliate at MIT在 mit.edu 的电子邮件经过验证
Anoush PoursartipThe University of British Columbia在 ubc.ca 的电子邮件经过验证
Sina Amini NiakiSenior Data Scientist, Amazon在 alumni.ubc.ca 的电子邮件经过验证
Naitong ChenPhD Student, Department of Statistics, University of British Columbia在 stat.ubc.ca 的电子邮件经过验证
Boyan BeronovUniversity of British Columbia在 cs.ubc.ca 的电子邮件经过验证
Xinglong LiUBC在 stat.ubc.ca 的电子邮件经过验证
Miao LiuIBM在 ibm.com 的电子邮件经过验证
Cecilia MascoloUniversity of Cambridge在 cl.cam.ac.uk 的电子邮件经过验证
Thibaut HorelMIT在 mit.edu 的电子邮件经过验证

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Trevor Campbell

Associate Professor, Statistics, UBC

在 stat.ubc.ca 的电子邮件经过验证 - 首页

Machine Learning Statistics Optimization Mathematics


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
Coresets for scalable Bayesian logistic regression J Huggins, T Campbell, T Broderick Advances in neural information processing systems 29, 2016	250	2016
Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture SA Niaki, E Haghighat, T Campbell, A Poursartip, R Vaziri Computer Methods in Applied Mechanics and Engineering 384, 113959, 2021	174	2021
Bayesian coreset construction via greedy iterative geodesic ascent T Campbell, T Broderick International Conference on Machine Learning, 698-706, 2018	143	2018
Automated scalable Bayesian inference via Hilbert coresets T Campbell, T Broderick Journal of Machine Learning Research 20 (15), 1-38, 2019	122	2019
Edge-exchangeable graphs and sparsity D Cai, T Campbell, T Broderick Advances in Neural Information Processing Systems 29, 2016	93	2016
Dynamic clustering via asymptotics of the dependent Dirichlet process mixture T Campbell, M Liu, B Kulis, JP How, L Carin Advances in Neural Information Processing Systems 26, 2013	63	2013
Validated variational inference via practical posterior error bounds J Huggins, M Kasprzak, T Campbell, T Broderick International Conference on Artificial Intelligence and Statistics, 1792-1802, 2020	57*	2020
Efficient global point cloud alignment using Bayesian nonparametric mixtures J Straub, T Campbell, JP How, JW Fisher Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	54	2017
Bayesian nonparametric set construction for robust optimization T Campbell, JP How 2015 American Control Conference (ACC), 4216-4221, 2015	53	2015
Sparse variational inference: Bayesian coresets from scratch T Campbell, B Beronov Advances in Neural Information Processing Systems 32, 2019	41	2019
Streaming, distributed variational inference for Bayesian nonparametrics T Campbell, J Straub, JW Fisher III, JP How Advances in Neural Information Processing Systems 28, 2015	39	2015
Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach JH Huggins, T Campbell, M Kasprzak, T Broderick arXiv preprint arXiv:1809.09505, 2018	38	2018
Small-variance nonparametric clustering on the hypersphere J Straub, T Campbell, JP How, JW Fisher Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015	36	2015
Bayesian pseudocoresets D Manousakas, Z Xu, C Mascolo, T Campbell Advances in Neural Information Processing Systems 33, 14950-14960, 2020	32	2020
Universal boosting variational inference T Campbell, X Li Advances in Neural Information Processing Systems 32, 2019	30	2019
Finite mixture models do not reliably learn the number of components D Cai, T Campbell, T Broderick International Conference on Machine Learning, 1158-1169, 2021	29	2021
Truncated random measures T Campbell, JH Huggins, JP How, T Broderick	28	2019
Exchangeable trait allocations T Campbell, D Cai, T Broderick	27	2018
Parallel tempering on optimized paths S Syed, V Romaniello, T Campbell, A Bouchard-Côté International Conference on Machine Learning, 10033-10042, 2021	23	2021
Data-dependent compression of random features for large-scale kernel approximation R Agrawal, T Campbell, J Huggins, T Broderick The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	23	2019

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