適用於公開取用強制性政策的文章 - Tamara Broderick瞭解詳情
未在任何資料庫公開的文章：1
Comment: Nonparametric Bayes Modeling of Populations of Networks
T Broderick
Journal of the American Statistical Association 112 (520), 1534-1537, 2017
授權規定： US National Institutes of Health
在某個資料庫公開的文章：37
Transparency and reproducibility in artificial intelligence
B Haibe-Kains, GA Adam, A Hosny, F Khodakarami, ...
Nature 586 (7829), E14-E16, 2020
授權規定： US National Institutes of Health, UK Biotechnology and Biological Sciences …
Bayesian coreset construction via greedy iterative geodesic ascent
T Campbell, T Broderick
International Conference on Machine Learning, 698-706, 2018
授權規定： US Department of Defense
Covariances, robustness, and variational Bayes
R Giordano, T Broderick, MI Jordan
Journal of machine learning research 19 (51), 1-49, 2018
授權規定： US National Science Foundation, US Department of Energy, US Department of …
Automated scalable Bayesian inference via Hilbert coresets
T Campbell, T Broderick
Journal of Machine Learning Research 20 (15), 1-38, 2019
授權規定： US Department of Defense
A swiss army infinitesimal jackknife
R Giordano, W Stephenson, R Liu, M Jordan, T Broderick
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
授權規定： US National Science Foundation, US Department of Defense, Gordon and Betty …
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
授權規定： US National Science Foundation, US Department of Defense, Natural Sciences …
Real-time semiparametric regression
J Luts, T Broderick, MP Wand
Journal of Computational and Graphical Statistics 23 (3), 589-615, 2014
授權規定： Australian Research Council
Posteriors, conjugacy, and exponential families for completely random measures
T Broderick, AC Wilson, MI Jordan
授權規定： US National Science Foundation, US Department of Defense
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
授權規定： US Department of Defense, Natural Sciences and Engineering Research Council …
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
授權規定： US National Science Foundation, US Department of Defense
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
授權規定： US National Science Foundation, US Department of Defense
Truncated random measures
T Campbell, JH Huggins, JP How, T Broderick
授權規定： US Department of Defense
Approximate cross-validation in high dimensions with guarantees
W Stephenson, T Broderick
International conference on artificial intelligence and statistics, 2424-2434, 2020
授權規定： US Department of Defense
More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics
L Masoero, F Camerlenghi, S Favaro, T Broderick
Biometrika 109 (1), 17-32, 2022
授權規定： US National Science Foundation, US Department of Defense, European …
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
授權規定： US National Science Foundation, US Department of Defense
Approximate cross-validation for structured models
S Ghosh, W Stephenson, TD Nguyen, S Deshpande, T Broderick
Advances in neural information processing systems 33, 8741-8752, 2020
授權規定： US National Science Foundation, US Department of Energy, US Department of …
Minimal I-MAP MCMC for scalable structure discovery in causal DAG models
R Agrawal, C Uhler, T Broderick
International Conference on Machine Learning, 89-98, 2018
授權規定： US National Science Foundation, US Department of Defense
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
授權規定： US National Science Foundation, US Department of Defense, UK Engineering and …
Closed-form approximations of first-passage distributions for a stochastic decision-making model
T Broderick, KF Wong-Lin, P Holmes
Applied Mathematics Research eXpress 2009 (2), 123-141, 2009
授權規定： US National Institutes of Health
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