Trevor Campbell

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Tamara BroderickAssociate Professor of EECS, Massachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
Jonathan P. HowRichard C. Maclaurin Professor of Aerospace Engineering, Massachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
Jonathan HugginsAssistant Professor of Statistics, Boston UniversityAdresse e-mail validée de bu.edu
Diana CaiCenter for Computational Mathematics, Flatiron InstituteAdresse e-mail validée de flatironinstitute.org
Julian StraubResearch Scientist, Reality Labs ResearchAdresse e-mail validée de csail.mit.edu
John W. Fisher IIISenior Research Scientist, Massachusetts Institute of TechnologyAdresse e-mail validée de csail.mit.edu
Saifuddin SyedUniversity of OxfordAdresse e-mail validée de stats.ox.ac.uk
Zuheng(David) XuPhD student, Department of Statistics, University of British ColumnbiaAdresse e-mail validée de stat.ubc.ca
Mikolaj KasprzakDepartment of Information Systems, Decision Sciences and Statistics, ESSEC Business SchoolAdresse e-mail validée de essec.edu
Nikola SurjanovicUniversity of British ColumbiaAdresse e-mail validée de stat.ubc.ca
Brian KulisAssociate Professor at Boston University & Amazon ScholarAdresse e-mail validée de bu.edu
Miguel Biron-LattesPhD candidate, University of British ColumbiaAdresse e-mail validée de stat.ubc.ca
Naitong ChenPhD Student, Department of Statistics, University of British ColumbiaAdresse e-mail validée de stat.ubc.ca
Reza VaziriProfessor of Civil Engineering, The University of British ColumbiaAdresse e-mail validée de ubc.ca
Ehsan HaghighatResearch ScientistAdresse e-mail validée de mit.edu
Anoush PoursartipThe University of British ColumbiaAdresse e-mail validée de ubc.ca
Sina Amini NiakiSenior Data Scientist, AmazonAdresse e-mail validée de alumni.ubc.ca
Boyan BeronovUniversity of British ColumbiaAdresse e-mail validée de cs.ubc.ca
Xinglong LiUBCAdresse e-mail validée de stat.ubc.ca
Miao LiuIBMAdresse e-mail validée de ibm.com

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Trevor Campbell

Associate Professor, Statistics, UBC

Adresse e-mail validée de stat.ubc.ca - Page d'accueil

Machine Learning Statistics Optimization Mathematics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Coresets for scalable Bayesian logistic regression J Huggins, T Campbell, T Broderick Advances in neural information processing systems 29, 2016	265	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	210	2021
Bayesian coreset construction via greedy iterative geodesic ascent T Campbell, T Broderick International Conference on Machine Learning, 698-706, 2018	150	2018
Automated scalable Bayesian inference via Hilbert coresets T Campbell, T Broderick Journal of Machine Learning Research 20 (15), 1-38, 2019	132	2019
Edge-exchangeable graphs and sparsity D Cai, T Campbell, T Broderick Advances in Neural Information Processing Systems 29, 2016	97	2016
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	67*	2020
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
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	55	2017
Bayesian nonparametric set construction for robust optimization T Campbell, JP How 2015 American Control Conference (ACC), 4216-4221, 2015	54	2015
Sparse variational inference: Bayesian coresets from scratch T Campbell, B Beronov Advances in Neural Information Processing Systems 32, 2019	46	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	40	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
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	36	2021
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	34	2020
Universal boosting variational inference T Campbell, X Li Advances in Neural Information Processing Systems 32, 2019	32	2019
Truncated random measures T Campbell, JH Huggins, JP How, T Broderick	30	2019
Exchangeable trait allocations T Campbell, D Cai, T Broderick	30	2018
Parallel tempering on optimized paths S Syed, V Romaniello, T Campbell, A Bouchard-Côté International Conference on Machine Learning, 10033-10042, 2021	25	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	24	2019

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