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@article{Kass1996,
author = {Kass, Robert E. and Wasserman, Larry},
title = {The Selection of Prior Distributions by Formal Rules},
journal = {Journal of the American Statistical Association},
volume = {91},
number = {435},
pages = {1343--1370},
year = {1996},
publisher = {ASA Website},
doi = {10.1080/01621459.1996.10477003},
}
@article{Zellner1996,
title = {Models, prior information, and Bayesian analysis},
journal = {Journal of Econometrics},
volume = {75},
number = {1},
pages = {51--68},
year = {1996},
issn = {0304-4076},
doi = {10.1016/0304-4076(95)01768-2},
author = {Zellner, Arnold},
}
@article{Soofi2000,
author = {Soofi, Ehsan S.},
title = {Principal Information Theoretic Approaches},
journal = {Journal of the American Statistical Association},
volume = {95},
number = {452},
pages = {1349--1353},
year = {2000},
publisher = {ASA Website},
doi = {10.1080/01621459.2000.10474346}
}
@article{Jaynes1957,
title = {Information Theory and Statistical Mechanics},
author = {Jaynes, E. T.},
journal = {Phys. Rev.},
volume = {106},
issue = {4},
pages = {620--630},
numpages = {0},
year = {1957},
month = {May},
publisher = {American Physical Society},
doi = {10.1103/PhysRev.106.620},
url = {https://link.aps.org/doi/10.1103/PhysRev.106.620}
}
@book{Press2009,
title={Subjective and objective Bayesian statistics: principles, models, and applications},
author={Press, S James},
year={2009},
publisher={John Wiley \& Sons}
}
@article{Reid2003,
title={Some aspects of matching priors},
author={Reid, N and Mukerjee, R and Fraser, DAS},
journal={Lecture Notes-Monograph Series},
pages={31--43},
year={2003},
publisher={JSTOR}
}
@article{Simpson2017,
author = {Simpson, Daniel and Rue, H{\aa}vard and Riebler, Andrea and Martins, Thiago G. and S{\o}rbye, Sigrunn H.},
title = {{Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors}},
volume = {32},
journal = {Statistical Science},
number = {1},
publisher = {Institute of Mathematical Statistics},
pages = {1--28},
keywords = {Bayesian theory, disease mapping, hierarchical models, information geometry, interpretable prior distributions, prior on correlation matrices},
year = {2017},
doi = {10.1214/16-STS576},
}
@InProceedings{kingma2017adam,
title ={Adam: A Method for Stochastic Optimization},
author = {Kingma, Diederik P. and Ba, Jimmy},
booktitle = {Proceedings of the 3rd International Conference on Learning Representations
(ICLR)},
year = {2017},
doi={10.48550/arXiv.1412.6980},
location={San Diego, USA}
}
@inProceedings{nalisnick2017learning,
author = {Nalisnick, Eric and Smyth, Padhraic},
title = {Learning Approximately Objective Priors},
year = {2017},
booktitle = {Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI)},
location = {Sydney, Australia},
publisher = {Association for Uncertainty in Artificial Intelligence (AUAI)},
doi = {10.48550/arXiv.1704.01168}
}
@article{van2024reference,
title={Reference prior for Bayesian estimation of seismic fragility curves},
volume={76},
ISSN={0266-8920},
url={http://dx.doi.org/10.1016/j.probengmech.2024.103622},
DOI={10.1016/j.probengmech.2024.103622},
journal={Probabilistic Engineering Mechanics},
publisher={Elsevier BV},
author={Van Biesbroeck, Antoine and Gauchy, Clément and Feau, Cyril and Garnier, Josselin},
year={2024},
month={4},
pages={103622} }
@misc{van2023generalized,
title={Generalized mutual information and their reference priors under Csizar f-divergence},
author={Van Biesbroeck, Antoine},
year={2024},
eprint={2310.10530},
archivePrefix={arXiv},
primaryClass={math.ST},
url={https://arxiv.org/abs/2310.10530},
note= {arXiv}
}
@misc{van2024constr,
title={Properly constrained reference priors decay rates for efficient and robust posterior inference},
author={Van Biesbroeck, Antoine},
year={2024},
eprint={2409.13041},
archivePrefix={arXiv},
primaryClass={stat.ME},
url={https://arxiv.org/abs/2409.13041},
note={arXiv}
}
@misc{van2025robustpost,
title={Robust a posteriori estimation of probit-lognormal seismic fragility curves via sequential design of experiments and constrained reference prior},
author={Van Biesbroeck, Antoine and Gauchy, Clément and Feau, Cyril and Garnier, Josselin},
year={2025},
eprint={2503.07343},
archivePrefix={arXiv},
primaryClass={stat.AP},
url={https://arxiv.org/abs/2503.07343},
}
@article{berger2009formal,
author = {Berger, James O. and Bernardo, Jos{\'e} M. and Sun, Dongchu },
title = {{The formal definition of reference priors}},
volume = {37},
journal = {The Annals of Statistics},
number = {2},
publisher = {Institute of Mathematical Statistics},
pages = {905--938},
keywords = {Amount of information, Bayesian asymptotics, consensus priors, Fisher information, Jeffreys priors, noninformative priors, objective priors, reference priors},
year = {2009},
doi = {10.1214/07-AOS587},
URL = {https://doi.org/10.1214/07-AOS587}
}
@article{berger1992ordered,
title={Ordered group reference priors with application to the multinomial problem},
author={Berger, James O. and Bernardo, Jos{\'e} M},
journal={Biometrika},
volume={79},
number={1},
pages={25--37},
year={1992},
publisher={Oxford University Press},
doi={10.1093/biomet/79.1.25}
}
@inProceedings{gauchy_var_rp,
title={Inférence
variationnelle de lois a priori de référence},
author={Gauchy, Cl{\'e}ment and Van Biesbroeck, Antoine and Feau, Cyril and Garnier, Josselin},
publisher = {SFDS},
booktitle = {Proceedings des 54\`emes Journ\'ees de Statistiques (JdS)},
year={2023},
month = {07},
url={https://jds2023.sciencesconf.org/resource/page/id/19}
}
@phdthesis{gauchy_thesis,
TITLE = {{Uncertainty quantification methodology for seismic fragility curves of mechanical structures : Application to a piping system of a nuclear power plant}},
AUTHOR = {Gauchy, Cl{\'e}ment},
URL = {https://theses.hal.science/tel-04102809},
NUMBER = {2022IPPAX100},
SCHOOL = {Institut Polytechnique de Paris},
YEAR = {2022},
MONTH = Nov,
KEYWORDS = {Seismic reliability ; Uncertainty quantification ; Design of experiments ; Gaussian process ; Nuclear industry ; Fiabilit{\'e} sismique ; Quantification des incertitudes ; Planification d'exp{\'e}riences ; Processus Gaussien ; Industrie nucl{\'e}aire},
TYPE = {Theses},
pages = {151--177}
}
@inproceedings{jang2017categorical,
title={Categorical Reparameterization with Gumbel-Softmax},
author={Jang, Eric and Gu, Shixiang and Poole, Ben},
booktitle={Proceedings of the 5th International Conference on Learning Representations (ICLR)},
year={2017},
location={Toulon, France},
url={https://openreview.net/forum?id=rkE3y85ee},
doi={10.48550/arXiv.1611.01144}
}
@misc{minka2012,
title={Estimating a Dirichlet distribution},
author={Minka, Thomas},
year={2012},
publisher={Technical report, MIT},
month={01},
url={https://api.semanticscholar.org/CorpusID:6959923}
}
@misc{huang2018neural,
title={Neural Autoregressive Flows},
author={Chin-Wei Huang and David Krueger and Alexandre Lacoste and Aaron Courville},
year={2018},
eprint={1804.00779},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/1804.00779},
}
@article{jeffreys1946prior,
author = {Jeffreys, Harold },
title = {An invariant form for the prior probability in estimation problems},
journal = {Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences},
volume = {186},
number = {1007},
pages = {453-461},
year = {1946},
doi = {10.1098/rspa.1946.0056},
URL = {https://royalsocietypublishing.org/doi/abs/10.1098/rspa.1946.0056},
}
@article{clarke1994jeffreys,
title = {Jeffreys' prior is asymptotically least favorable under entropy risk},
journal = {Journal of Statistical Planning and Inference},
volume = {41},
number = {1},
pages = {37--60},
year = {1994},
issn = {0378-3758},
doi = {10.1016/0378-3758(94)90153-8},
url = {https://www.sciencedirect.com/science/article/pii/0378375894901538},
author = {Clarke, Bertrand S. and Barron, Andrew R.}
}
@article{bernardo1979,
author = {Bernardo, José M.},
year = {1979},
month = {01},
pages = {113--147},
title = {Reference Posterior Distributions for {B}ayesian Inference},
volume = {41},
number = 2,
journal = {Journal of the Royal Statistical Society. Series B},
doi = {10.1111/j.2517-6161.1979.tb01066.x}
}
@incollection{bernardo2005reference,
title = {Reference Analysis},
editor = {Dey, D. K. and Rao, C.R.},
series = {Handbook of Statistics},
publisher = {Elsevier},
volume = {25},
pages = {17--90},
year = {2005},
booktitle = {Bayesian Thinking},
issn = {0169-7161},
doi = {10.1016/S0169-7161(05)25002-2},
url = {https://www.sciencedirect.com/science/article/pii/S0169716105250022},
author = {Bernardo, José M.}
}
@article{berger2015,
title={Overall Objective Priors},
volume={10},
ISSN={1936-0975},
url={http://dx.doi.org/10.1214/14-BA915},
DOI={10.1214/14-ba915},
number={1},
journal={Bayesian Analysis},
publisher={Institute of Mathematical Statistics},
author={Berger, James O. and Bernardo, Jose M. and Sun, Dongchu},
year={2015},
month={3}
}
@article{berger1992develop,
author = {Berger, James O. and Bernardo, José M.},
year = {1992},
month = {11},
pages = {},
title = {On the development of reference priors},
volume = {4},
journal = {Bayesian Statistics}
}
@phdthesis{bioche2015approximation,
TITLE = {{Approximation de lois impropres et applications}},
AUTHOR = {Bioche, Christ{\`e}le},
URL = {https://theses.hal.science/tel-01308523},
NUMBER = {2015CLF22626},
SCHOOL = {{Universit{\'e} Blaise Pascal - Clermont-Ferrand II}},
YEAR = {2015},
MONTH = {11},
KEYWORDS = {Logarithmic convergence ; Jeffreys-Lindley paradox ; Improper prior ; Convergence of priors ; Conjugate prior ; Bayesian statistic ; Noninformative prior ; Reference prior ; Removal sampling ; Vague prior ; A priori conjugu{\'e}s ; A priori de r{\'e}f{\'e}rence ; A priori impropres ; A priori non-informatifs ; A priori vagues ; Convergence d'a priori ; Convergence logarithmique ; Paradoxe de Jeffreys-Lindley ; Statistiques bay{\'e}siennes},
TYPE = {Theses},
PDF = {https://theses.hal.science/tel-01308523/file/BIOCHE_2015CLF22626.pdf},
HAL_ID = {tel-01308523},
HAL_VERSION = {v1},
}
@article{kingma2019introduction,
title={An Introduction to Variational Autoencoders},
volume={12},
ISSN={1935-8245},
url={http://dx.doi.org/10.1561/2200000056},
DOI={10.1561/2200000056},
number={4},
journal={Foundations and Trends® in Machine Learning},
publisher={Now Publishers},
author={Kingma, Diederik P. and Welling, Max},
year={2019},
pages={307-–392} }
@inProceedings{lafferty2013iterative,
author = {Lafferty, John D. and Wasserman, Larry A.},
editor = {Jack S. Breese and Daphne Koller},
title = {Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk},
booktitle = {Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence (UAI)},
pages = {293--300},
publisher = {Morgan Kaufmann},
year = {2001},
location={Seattle, USA},
doi = {10.48550/arXiv.1301.2286}
}
@article{sainct2018efficient,
title = {Efficient methodology for seismic fragility curves estimation by active learning on Support Vector Machines},
journal = {Structural Safety},
volume = {86},
pages = {101972},
year = {2020},
issn = {0167-4730},
doi = {10.1016/j.strusafe.2020.101972},
url = {https://www.sciencedirect.com/science/article/pii/S0167473020300515},
author = {Sainct, R\'emi and Feau, Cyril and Martinez, Jean-Marc and Garnier, Josselin},
}
@inProceedings{torch2019,
author = {Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and Desmaison, Alban and Kopf, Andreas and Yang, Edward and DeVito, Zachary and Raison, Martin and Tejani, Alykhan and Chilamkurthy, Sasank and Steiner, Benoit and Fang, Lu and Bai, Junjie and Chintala, Soumith},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {PyTorch: An Imperative Style, High-Performance Deep Learning Library},
url = {https://Proceedings.neurips.cc/paper_files/paper/2019/file/bdbca288fee7f92f2bfa9f7012727740-Paper.pdf},
volume = {32},
year = {2019}
}
@misc{basir2023adaptive,
title={An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networks},
author={Basir, Shamsulhaq and Senocak, Inanc},
year={2023},
eprint={2306.04904},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2306.04904},
note={arXiv}
}
@inbook{nocedal2006penalty,
title = "Numerical optimization",
author = "Nocedal, Jorge and Wright, {Stephen J.}",
year = "2006",
language = "English (US)",
publisher="Springer New York",
pages = "497--528",
booktitle = "Springer Series in Operations Research and Financial Engineering",
doi={10.1007/978-0-387-40065-5\_17},
chapter ={Penalty and Augmented Lagrangian Methods},
}
@phdthesis{mure2018objective,
title={Objective Bayesian analysis of Kriging models with anisotropic correlation kernel},
author={Mur{\'e}, Joseph},
year={2018},
school={Universit{\'e} Sorbonne Paris Cit{\'e}},
url={https://theses.hal.science/tel-02184403/file/MURE_Joseph_2_complete_20181005.pdf},
chapter={2},
}
@InProceedings{gao2022deep,
title = {Deep Reference Priors: What is the best way to pretrain a model?},
author = {Gao, Yansong and Ramesh, Rahul and Chaudhari, Pratik},
booktitle = {Proceedings of the 39th International Conference on Machine Learning},
pages = {7036--7051},
year = {2022},
volume = {162},
series = {Proceedings of Machine Learning Research},
month = {17--23 Jul},
publisher = {PMLR},
url = {https://Proceedings.mlr.press/v162/gao22d.html},
}
@article{kennedy1980,
title = "Probabilistic seismic safety study of an existing nuclear power plant",
journal = "Nuclear Engineering and Design",
volume = "59",
number = "2",
pages = "315--338",
year = "1980",
issn = "0029-5493",
doi = {10.1016/0029-5493(80)90203-4},
author = {Kennedy, Robert P. and Cornell, C. Allin and Campbell, Robert D. and Kaplan, Stan J. and Harold, F.}
}
@inbook{gelman2013,
title={Bayesian data analysis, third edition},
author={Andrew Gelman and John B. Carlin and Hal S. Stern and David B. Dunson and Aki Vehtari and Donald B. Rubin},
year={2013},
doi={10.1201/b16018},
pages={293--300},
publisher={Chapman and Hall/CRC}
}
@article{gretton_mmd,
author = {Gretton, Arthur and Borgwardt, Karsten M. and Rasch, Malte J. and Sch{{\"o}}lkopf, Bernhard and Smola, Alexander},
title = {A Kernel Two-Sample Test},
journal = {Journal of Machine Learning Research},
year = {2012},
volume = {13},
number = {25},
pages = {723--773},
url = {http://jmlr.org/papers/v13/gretton12a.html}
}
@ARTICLE{kobyzev_flows,
author={Kobyzev, Ivan and Prince, Simon J.D. and Brubaker, Marcus A.},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Normalizing Flows: An Introduction and Review of Current Methods},
year={2021},
volume={43},
number={11},
pages={3964--3979},
keywords={Estimation;Jacobian matrices;Mathematical model;Training;Computational modeling;Context modeling;Random variables;Generative models;normalizing flows;density estimation;variational inference;invertible neural networks},
doi={10.1109/TPAMI.2020.2992934}}
@article{micchelli_univkernels,
author = {Micchelli, Charles A. and Xu, Yuesheng and Zhang, Haizhang},
title = {Universal Kernels},
year = {2006},
issue_date = {12/1/2006},
publisher = {JMLR.org},
volume = {7},
issn = {1532-4435},
abstract = {In this paper we investigate conditions on the features of a continuous kernel so that it may approximate an arbitrary continuous target function uniformly on any compact subset of the input space. A number of concrete examples are given of kernels with this universal approximating property.},
journal = {Journal of Machine Learning Research},
month = {dec},
pages = {2651–-2667},
url = {http://jmlr.org/papers/v7/micchelli06a.html}
}
@Inbook{KStest,
title="Kolmogorov--Smirnov Test",
bookTitle="The Concise Encyclopedia of Statistics",
year="2008",
publisher="Springer New York",
address="New York, NY",
author={Dodge, Yadolah},
pages="283--287",
isbn="978-0-387-32833-1",
doi="10.1007/978-0-387-32833-1\_214",
url="https://doi.org/10.1007/978-0-387-32833-1_214"
}
@InProceedings{buchholz2018qmc,
title ={Quasi-{M}onte {C}arlo Variational Inference},
author = {Buchholz, Alexander and Wenzel, Florian and Mandt, Stephan},
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}
%%%reference priors
@article{Bernardo1979a,
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volume = {16},
pages = {1--19},
}
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author = {Paulo, Rui},
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% f-div
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year = {1997},
lastchecked = {2025-07-18}
}