Jonathan Huggins

Cited by

	All	Since 2020
Citations	1170	933
h-index	18	15
i10-index	24	20

220

110

165

20132014201520162017201820192020202120222023202420259 11 15 14 31 58 83 120 203 185 177 220 27

Public access

View all

17 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Tamara BroderickAssociate Professor of EECS, Massachusetts Institute of TechnologyVerified email at mit.edu
Trevor CampbellAssociate Professor, Statistics, UBCVerified email at stat.ubc.ca
Mikolaj KasprzakDepartment of Information Systems, Decision Sciences and Statistics, ESSEC Business SchoolVerified email at essec.edu
Kevin EsveltAssociate Professor, MIT Media LabVerified email at mit.edu
Liam PaninskiColumbia UniversityVerified email at stat.columbia.edu
Michael Riis AndersenAssociate professor, Technical University of DenmarkVerified email at dtu.dk
Aki VehtariProfessor, Aalto UniversityVerified email at aalto.fi
Alun LloydDrexel Professor of Mathematics, North Carolina State UniversityVerified email at ncsu.edu
Jeffrey W MillerHarvard T.H. Chan School of Public HealthVerified email at hsph.harvard.edu
Manushi WelandaweBoston University Mathematics and StatisticsVerified email at bu.edu
Akash Kumar DhakaDoctoral Student, Aalto UniversityVerified email at aalto.fi
Alejandro CatalinaAalto UniversityVerified email at aalto.fi
Ethan AlleyMIT Media LabVerified email at mit.edu
Lester MackeyMicrosoft ResearchVerified email at microsoft.com
Daniel M. RoyResearch Director, Vector Institute; Prof., U. Toronto (Statistics, CS)Verified email at utoronto.ca
Brian L TrippeAssistant Professor of Statistics, Stanford UniversityVerified email at stanford.edu
Eftychios A. PnevmatikakisMeta Reality LabsVerified email at flatironinstitute.org
James ZouStanford UniversityVerified email at stanford.edu
Jonathan P. HowRichard C. Maclaurin Professor of Aerospace Engineering, Massachusetts Institute of TechnologyVerified email at mit.edu
Ardavan SaeediMassachusetts Institute of TechnologyVerified email at mit.edu

Jonathan Huggins

Assistant Professor of Statistics, Boston University

Verified email at bu.edu - Homepage

Machine Learning Data Science Uncertainty Quantification Bayesian Inference


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Coresets for scalable Bayesian logistic regression JH Huggins, T Campbell, T Broderick Advances in Neural Information Processing Systems, 4080-4088, 2016	274	2016
Bidirectional contact tracing could dramatically improve COVID-19 control WJ Bradshaw, EC Alley, JH Huggins, AL Lloyd, KM Esvelt Nature communications 12 (1), 232, 2021	162	2021
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	68*	2020
Challenges and opportunities in high dimensional variational inference AK Dhaka, A Catalina, M Welandawe, MR Andersen, J Huggins, A Vehtari Advances in Neural Information Processing Systems 34, 7787-7798, 2021	54	2021
Random feature Stein discrepancies J Huggins, L Mackey Advances in neural information processing systems 31, 2018	50	2018
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference J Huggins, RP Adams, T Broderick Advances in Neural Information Processing Systems 30, 2017	40	2017
Robust, accurate stochastic optimization for variational inference AK Dhaka, A Catalina, MR Andersen, M Magnusson, J Huggins, A Vehtari Advances in Neural Information Processing Systems 33, 10961-10973, 2020	39	2020
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	39	2018
Robust inference and model criticism using bagged posteriors JH Huggins, JW Miller arXiv preprint arXiv:1912.07104, 2019	36*	2019
Fast Kalman filtering and forward–backward smoothing via a low-rank perturbative approach EA Pnevmatikakis, KR Rad, J Huggins, L Paninski Journal of Computational and Graphical Statistics 23 (2), 316-339, 2014	36	2014
Quantifying the accuracy of approximate diffusions and Markov chains J Huggins, J Zou Artificial Intelligence and Statistics, 382-391, 2017	34	2017
Sequential Monte Carlo as Approximate Sampling: bounds, adaptive resampling via -ESS, and an application to Particle Gibbs JH Huggins, DM Roy Bernoulli 25 (1), 584–622, 2019	33*	2019
The kernel interaction trick: Fast Bayesian discovery of pairwise interactions in high dimensions R Agrawal, B Trippe, J Huggins, T Broderick International Conference on Machine Learning, 141-150, 2019	32	2019
Truncated random measures T Campbell, JH Huggins, JP How, T Broderick	31	2019
Reproducible model selection using bagged posteriors JH Huggins, JW Miller Bayesian analysis 18 (1), 79, 2022	28*	2022
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	25	2019
Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime JH Huggins, L Paninski Journal of Computational Neuroscience 32, 347-366, 2012	20	2012
Scalable Gaussian process inference with finite-data mean and variance guarantees JH Huggins, T Campbell, M Kasprzak, T Broderick The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	19	2019
Fast state-space methods for inferring dendritic synaptic connectivity A Pakman, J Huggins, C Smith, L Paninski Journal of computational neuroscience 36, 415-443, 2014	16	2014
The mutational signature comprehensive analysis toolkit (musicatk) for the discovery, prediction, and exploration of mutational signatures A Chevalier, S Yang, Z Khurshid, N Sahelijo, T Tong, JH Huggins, ... Cancer research 81 (23), 5813-5817, 2021	15	2021

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors