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20092026
most citedJet-Images -- Deep Learning Edition

281 citations · 1.3k across the 71 of their papers we have counts for

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6 papers · 1 filter

stat.ME2023★ 1 cited

Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations

Hammaad Adam, Fan Yin, Huibin +5

Randomized experiments often need to be stopped prematurely due to the treatment having an unintended harmful effect. Existing methods that determine when to stop an experiment ear…

stat.ME2021★ 1 cited

Stein's Method Meets Computational Statistics: A Review of Some Recent Developments

Andreas Anastasiou, Alessandro Barp, François-Xavier Briol +11

Stein's method compares probability distributions through the study of a class of linear operators called Stein operators. While mainly studied in probability and used to underpin…

stat.ME2020★ 5 cited

Independent finite approximations for Bayesian nonparametric inference

Tin D. Nguyen, Jonathan Huggins, Lorenzo Masoero +2

Completely random measures (CRMs) and their normalizations (NCRMs) offer flexible models in Bayesian nonparametrics. But their infinite dimensionality presents challenges for infer…

stat.ME2020★ 2 cited

Optimal Thinning of MCMC Output

Marina Riabiz, Wilson Chen, Jon Cockayne +4

The use of heuristics to assess the convergence and compress the output of Markov chain Monte Carlo can be sub-optimal in terms of the empirical approximations that are produced. T…

stat.ME2015★ 1 cited

Empirical Bayesian analysis of simultaneous changepoints in multiple data sequences

Zhou Fan, Lester Mackey

Copy number variations in cancer cells and volatility fluctuations in stock prices are commonly manifested as changepoints occurring at the same positions across related data seque…

stat.ME2011★ 7 cited

Combinatorial clustering and the beta negative binomial process

Tamara Broderick, Lester Mackey, John Paisley +1

We develop a Bayesian nonparametric approach to a general family of latent class problems in which individuals can belong simultaneously to multiple classes and where each class ca…