Robust inference and model selection using bagged posteriors.
(slides)
Statistics Department Seminar, Oct 18, 2021, Colorado State University.
Inference in generalized bilinear models.
(slides)
(video)
MIA seminar, Oct 28, 2020, Broad Institute.
Robust Bayesian inference via coarsening.
(slides)
BU Probability and Statistics Seminar, Mar 15, 2018, Boston University.
Combinatorial stochastic processes for variable-dimension models.
(slides)
Duke Statistical Science Seminar, February 7, 2014, Duke University.
A simple example of Dirichlet process mixture inconsistency for the number of components.
(slides)
(video)
NeurIPS 2013, Lake Tahoe, NV.
Posterior consistency for the number of components in a finite mixture.
(slides)
(video)
Workshop on Modern Nonparametric Methods in Machine Learning, NeurIPS 2012, Lake Tahoe, NV.
Dirichlet process mixtures are inconsistent for the number of components in a finite mixture.
(slides)
(video)
ICERM Bayesian Nonparametrics Workshop, 2012, Providence, RI.
Department of Statistics Colloquium, Mar 21, 2024, University of South Carolina. Reproducible inference and model selection using bagged posteriors.
Department of Statistics Seminar, Apr 18, 2024, University of Auckland, New Zealand. Reproducible inference and model selection using bagged posteriors.
Department of Statistics Colloquium, Feb 23, 2024, Florida State University. Reproducible inference and model selection using bagged posteriors.
NEJSDS workshop on Statistics in Data Science, Jan 26, 2024, University of Connecticut. Truth-agnostic diagnostics for calibration under misspecification.
New England Statistics Symposium, June 5, 2023, Boston University. Truth-agnostic diagnostics for calibration under misspecification.
Workshop at Summer School on Bayesian Statistics and Computation, July 13-22, 2023, University of Economics, Ho Chi Minh city, Vietnam. Reproducible inference and model selection using bagged posteriors.
Bayes Comp 2023 conference, Mar 15, 2023, Levi, Finland. Truth-agnostic diagnostics for calibration under misspecification.
Joint Statistical Meetings (JSM), Aug 8, 2022, Washington, DC. Truth-agnostic diagnostics for calibration under misspecification.
International Society for Bayesian Analysis (ISBA) World Meeting, June 30, 2022, Montreal, Canada. Bayesian optimal experimental design for inferring causal structure.
5th International Conference on Econometrics and Statistics (EcoSta 2022), June 4, 2022, Kyoto, Japan. Reproducible model selection using bagged posteriors.
New England Statistics Symposium (NESS), May 24, 2022, University of Connecticut. Inference in generalized bilinear models.
Biostatistics Department Seminar, Jan 13, 2022, University of Washington. Robust inference and model selection using bagged posteriors.
"Your Model is Wrong: Robustness and misspecification in probabilistic modeling" workshop, Dec 13, 2021, NeurIPS conference. Panel discussion.
Statistics Department Seminar, Oct 18, 2021, Colorado State University. Robust inference and model selection using bagged posteriors.
Biostatistics Lightning Talk Series, Oct 8, 2021, Harvard T.H. Chan School of Public Health. Inference in generalized bilinear models.
New England Statistics Symposium (NESS), Oct 2, 2021, Providence, RI. Reproducible model selection using bagged posteriors.
Joint Statistical Meetings (JSM), Aug 12, 2021. Reproducible model selection using bagged posteriors.
Advanced Biomedical Computation (ABC) Seminar Series, May 17, 2021, Brigham and Women’s Hospital. Inference in generalized bilinear models.
IBEST-IMCI Seminar, Apr 29, 2021, University of Idaho. Inference in generalized bilinear models.
Division of Biostatistics Seminar, Mar 31, 2021, University of Minnesota. Robust inference and model selection using bagged posteriors.
Harvard Statistics Departmental Colloquium, Feb 1, 2021, Harvard University. Robust inference and model selection using bagged posteriors.
Cancer Working Group seminar, Nov 16, 2020, Harvard T.H. Chan School of Public Health. Inference in generalized bilinear models.
Models, Inference \& Algorithms (MIA) seminar, Oct 28, 2020, Broad Institute of MIT and Harvard. Inference in generalized bilinear models.
Bayes Comp 2020 conference, Jan 9, 2020, Gainesville, FL. Flexible perturbation models for robustness to misspecification.
Methods Primer Seminar, Dec 5, 2019, Broad Institute. Flexible perturbation models for robustness to misspecification.
Wednesday Statistics Seminar, Dec 4, 2019, Massachusetts Institute of Technology. Flexible perturbation models for robustness to misspecification.
Joint Statistical Meetings (JSM), July 28, 2019, Denver, CO. Generalized bilinear models for bias correction in large-scale genomics data.
12th Conference on Bayesian Nonparametrics (BNP12), June 27, 2019, Oxford, UK. Flexible perturbation models for robustness to misspecification.
BYU Statistics Seminar, Mar 28, 2019, Brigham Young University. Flexible perturbation models for robustness to misspecification.
MyAgeGroup2 meeting, Mar 10, 2019, Birmingham, AL. Statistics and machine learning for the biology of aging.
Joint International Society for Clinical Biostatistics and Australian Statistical Conference (ISCB-ASC), Aug 30, 2018, Melbourne, Australia. Robust inference using power posteriors: Calibration and inference.
Joint Statistical Meetings (JSM), Aug 1, 2018, Vancouver, BC. Robust clustering using power posteriors: Calibration and inference.
Radcliffe exploratory seminar, Statistics When the Model is Wrong, June 1, 2018, Harvard University. Robust Bayes: Perturbations, powers, coarsening, and calibration.
HSPH Faculty Meeting, Mar 27, 2018, Harvard University. Predicting individual response to aging interventions. BU Probability and Statistics Seminar, Mar 15, 2018, Boston University. Robust Bayesian inference via coarsening. WPI Statistics Seminar, Mar 12, 2018, Worcester Polytechnic Institute. Robust Bayesian inference via coarsening. MyAgeGroup meeting, Mar 3, 2018, Austin, TX. Statistics and machine learning for the biology of aging. International Workshop on Objective Bayes Methodology (O-Bayes), Dec 11, 2017, University of Texas, Austin. Inference for cancer phylogenetics. Joint Statistical Meetings (JSM), Jul 31, 2017, Baltimore, MD. Cancer phylogenies and nonparametric clustering. 19th Meeting of New Researchers in Statistics and Probability, Jul 28, 2017, Johns Hopkins University. Cancer phylogenetic inference.
11th Conference on Bayesian Nonparametrics (BNP11), June 29, 2017, Paris, France.
Several interpretations of the power posterior.
(slides)
ICERM Probabilistic Scientific Computing Workshop, June 8, 2017, Providence, RI.
Inference using partial information.
(slides)
MIT Machine Learning Colloquium, April 26, 2017, Massachusetts Institute of Technology.
Robust Bayesian inference via coarsening.
(slides)
9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016), Dec 11, 2016, Seville, Spain.
Non-standard approaches to nonparametric Bayes.
(slides)
FocuStat L^\eta Research Kitchen, Oct 12, 2016, University of Oslo, Norway.
Robust Bayesian inference via coarsening.
Pattern Theory Seminar, Oct 5, 2016, Brown University.
Robust Bayesian inference via coarsening.
Joint Statistical Meetings (JSM), August 3, 2016, Chicago, IL.
Robust Bayesian inference via coarsening.
International Society for Bayesian Analysis (ISBA) World Meeting, June 14, 2016, Sardinia, Italy.
Robust Bayesian inference via coarsening.
(One of 2 winners of travel award)
8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015), Dec 14, 2015, London, UK.
Robust Bayesian inference via coarsening.
Bayesian Nonparametrics: The Next Generation, NeurIPS 2015 Workshop, Dec 12, 2015, Montreal, CA.
Non-standard approaches to nonparametric Bayes (talk),
Microclustering: When the cluster sizes grow sublinearly with the size of the data set (poster).
(One of 5 winners of travel award)
Harvard Statistics Departmental Colloquium, Sept 21, 2015, Harvard University.
Robust Bayesian inference via coarsening.
Joint Statistical Meetings (JSM), August 11, 2015, Seattle, WA.
Robust Bayesian inference via coarsening.
Bayesian Nonparametrics: Synergies between Statistics, Probability and Mathematics, June 30, 2015, SAMSI.
Robust Bayesian inference via coarsening.
10th Conference on Bayesian Nonparametrics (BNP10), June 23, 2015, Raleigh, NC.
An approach to inference under misspecification.
G70: A Celebration of Alan Gelfand's 70th Birthday, April 20, 2015, Duke University.
The small clustering problem: What if the clusters don't grow with N?
Texas A&M Statistics Departmental Colloquium, October 31, 2014, Texas A&M University.
Combinatorial stochastic processes for variable-dimension models.
International Society for Bayesian Analysis (ISBA) World Meeting, July 14 - 18, 2014, Cancun, Mexico.
Combinatorial stochastic processes for variable-dimension models.
New England Statistics Symposium (NESS), April 26, 2014, Harvard School of Public Health.
Combinatorial stochastic processes for variable-dimension models.
Dissertation defense, April 15, 2014, Brown University.
Duke Statistical Science Seminar, February 7, 2014, Duke University.
Combinatorial stochastic processes for variable-dimension models.
Neural Information Processing Systems (NeurIPS) 2013, Lake Tahoe, NV.
A simple example of Dirichlet process mixture inconsistency for the number of components.
(Full oral presentation)
(slides)
(poster)
Pattern Theory Seminar, November 6, 2013, Brown University.
Dirichlet process mixture inconsistency for the number of components, and dimension mixture models.
9th Conference on Bayesian Nonparametrics (BNP9), Amsterdam, 2013.
Dimension mixtures of finite-dimensional models.
(Winner of 1st place in poster competition)
(poster)
New England Machine Learning day (NEML) 2013, Cambridge, MA.
Posterior consistency for the number of components in a finite mixture.
New England Statistics Symposium (NESS) 2013, Storrs, CT.
Posterior consistency for the number of components in a finite mixture.
Brown University Symposium for Undergraduates in the Mathematical Sciences (SUMS), 2013.
High-dimensional parameter spaces and Fisher information.
Neural Information Processing Systems (NeurIPS) 2012, Lake Tahoe, NV
(Workshop on Modern Nonparametric Methods in Machine Learning).
Posterior consistency for the number of components in a finite mixture.
(Please see correction to this abstract.)
ICERM Bayesian Nonparametrics Workshop, 2012, Providence, RI.
Dirichlet process mixtures are inconsistent for the number of components in a finite mixture.
New England Statistics Symposium (NESS) 2011, Storrs, CT.
A practical algorithm for exact inference on tables.
(One of four winners of the IBM Thomas J. Watson Research Center Student Research Award)
Joint Statistical Meetings (JSM) 2010, Vancouver, BC.
A practical algorithm for exact inference on tables.