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Jonathan Huggins
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Recent & Upcoming Talks
2023
Reproducible (Bayesian) Statistical Inference
Nov 13, 2023
BAYSM 2023
Robust, structurally-aware inference for mixture models
Aug 8, 2023
JSM 2023
Robust, structurally-aware inference for mixture models
May 18, 2023
Boston University (Biostatistics Seminar)
Robust, structurally-aware inference for mixture models
Mar 16, 2023
BayesComp 2023
2022
Trustworthy variational inference
Oct 21, 2022
Texas A&M University, Conference on Advances in Data Science
Calibrated model criticism using split predictive checks
Jun 29, 2022
ISBA World Meeting
Algorithmically robust, general-purpose variational inference
Apr 13, 2022
SIAM Conference on Uncertainty Quantification (UQ22) – Minisymposium on ‘Variational Inference Bridging Application and Theory’
2021
Statistically robust inference with stochastic gradient algorithms
Dec 14, 2021
NeurIPS 2021 Workshop: Your Model is Wrong
Robust, scalable Bayesian inference using stochastic gradients
Aug 7, 2021
JSM 2021
Robust, scalable Bayesian inference using stochastic gradients
Jun 29, 2021
ISBA World Meeting
Algorithmically robust, general-purpose variational inference
Apr 5, 2021
Harvard B3D Seminar Series
Algorithmically robust, general-purpose variational inference
Mar 17, 2021
University of Haifa (Statistics Seminar)
Using bagged posteriors for robust inference
Mar 5, 2021
SIAM Conference on Computational Science and Engineering (CSE21) – Minisymposium on ‘Model error in statistical inverse problems: misfit measures, robustness, and calibration’
Algorithmically robust, general-purpose variational inference
Mar 4, 2021
Monash University (Econometrics and Business Statistics Seminar)
2020
Using bagged posteriors for robust inference
Mar 30, 2020
Harvard University (B3D Seminar Series)
Using bagged posteriors for robust inference
Feb 20, 2020
Northeastern University (SPIRAL Seminar Series)
Using bagged posteriors for robust inference
Jan 7, 2020
Bayes Comp 2020
2019
Using bagged posteriors for robust inference
Dec 4, 2019
Broad Institute (Models, Inference & Algorithms)
Using bagged posteriors for robust inference
Oct 30, 2019
Massachusetts Institute of Technology (Doctoral Seminar in Statistics)
Using bagged posteriors for robust inference
Oct 25, 2019
Oxford University
Using bagged posteriors for robust inference
Oct 23, 2019
Bristol University
Robustness and scalability of Bayesian nonnegative matrix factorization
Jul 28, 2019
JSM 2019
Scalable, reliably accurate Bayesian inference via approximate likelihoods and random features
Feb 26, 2019
Google AI
Slides
Scalable, reliably accurate Bayesian inference via approximate likelihoods and random features
Feb 25, 2019
Broad Institute
Slides
Scalable, reliably accurate Bayesian inference via approximate likelihoods and random features
Feb 20, 2019
Northeastern University
Slides
Scalable, reliably accurate Bayesian inference via approximate likelihoods and random features
Jan 31, 2019
Boston University
Slides
2018
Scaling Bayesian inference using exponential family approximations
Jun 27, 2018
ISBA World Meeting
Finite-dimensional approximations of completely random measures
Jun 14, 2018
SPA 2018
Slides
Scaling Bayesian inference using exponential family approximations
Apr 24, 2018
Boston Bayesians Meetup
Slides
2017
Generic finite approximations for practical Bayesian nonparametrics
Dec 8, 2017
NIPS 2017 Workshop on Advances in Approximate Bayesian Inference
Truncated random measures
Jun 26, 2017
BNP 2017
Slides
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