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A rare event is defined by a low probability of occurrence.
An automatic method for finding the greatest or least value of a function
HoHo Rosenbrock · 1960
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An analysis of transformations
George EP Box and David R Cox · 1964
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A new family of power transformations to improve normality or symmetry
In-Kwon Yeo and Richard A Johnson · 2000
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Estimation of small failure probabilities in high dimensions by subset simulation
Siu-Kui Au and James L Beck · 2001
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Detection probability of trends in rare events: Theory and application to heavy precipitation in the alpine region
Christoph Frei and Christoph Schär · 2001
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Introduction to rare event simulation , volume 5
James Antonio Bucklew and J Bucklew · 2004
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A critical appraisal of reliability estimation procedures for high dimensions
Gerhart Iwo Schuëller, Helmuth J Pradlwarter, and Phaedon-Stelios Koutsourelakis · 2004
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Pattern recognition and machine learning , volume 4
Christopher M Bishop and Nasser M Nasrabadi · 2006
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Sequential monte carlo samplers
Pierre Del Moral, Arnaud Doucet, and Ajay Jasra · 2006
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Mixture importance sampling and its application to the analysis of sram designs in the presence of rare failure events
Rouwaida Kanj, Rajiv Joshi, and Sani Nassif · 2006
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Breaking the simulation barrier: Sram evaluation through norm minimization
Lara Dolecek, Masood Qazi, Devavrat Shah, and Anantha Chandrakasan · 2008
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Forward flux sampling for rare event simulations
Rosalind J Allen, Chantal Valeriani, and Pieter Rein Ten Wolde · 2009
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Meta-analysis for rare events
Tianxi Cai, Layla Parast, and Louise Ryan · 2010
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Experts, bayesian belief networks, rare events and aviation risk estimates
Peter Brooker · 2011
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Nice: Non-linear independent components estimation
Laurent Dinh, David Krueger, and Yoshua Bengio · 2014
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Fast statistical analysis of rare circuit failure events via subset simulation in high-dimensional variation space
Shupeng Sun and Xin Li · 2014
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An introduction to rare event simulation and importance sampling
Gino Biondini · 2015
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
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Fast statistical analysis of rare circuit failure events via scaled-sigma sampling for high-dimensional variation space
Shupeng Sun, Xin Li, Hongzhou Liu, Kangsheng Luo, and Ben Gu · 2015
Cited alongside, same era.
Density estimation using real nvp
Neural importance sampling
Thomas Müller, Brian McWilliams, Fabrice Rousselle, Markus Gross, and Jan Novák · 2019
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Neural approximate sufficient statistics for implicit models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron C. Courville, and Zhanxing Zhu · 2020
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i-flow: High-dimensional integration and sampling with normalizing flows
Christina Gao, Joshua Isaacson, and Claudius Krause · 2020
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Normalizing flows: An introduction and review of current methods
Ivan Kobyzev, Simon JD Prince, and Marcus A Brubaker · 2020
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Srflow: Learning the super-resolution space with normalizing flow
Andreas Lugmayr, Martin Danelljan, Luc Van Gool, and Radu Timofte · 2020
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Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
Cited alongside, same era.
Improved variational inference with inverse autoregressive flow
Durk P Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling · 2016
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Masked autoregressive flow for density estimation
George Papamakarios, Theo Pavlakou, and Iain Murray · 2017
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Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
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Multi-objective bayesian optimization for analog/rf circuit synthesis
Wenlong Lyu, Fan Yang, Changhao Yan, Dian Zhou, and Xuan Zeng · 2018
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Scalable end-to-end autonomous vehicle testing via rare-event simulation
Matthew O’Kelly, Aman Sinha, Hongseok Namkoong, Russ Tedrake, and John C Duchi · 2018
Cited alongside, same era.
A fast and robust failure analysis of memory circuits using adaptive importance sampling method
Xiao Shi, Fengyuan Liu, Jun Yang, and Lei He · 2018
Cited alongside, same era.
Ivan Ostroumov, Karen Marais, Nataliia Kuzmenko, and Nicoletta Fala · 2020
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Enabling wavelength-dependent adjoint-based methods for process variation sensitivity analysis in silicon photonics
Zhengxing Zhang, Sally I El-Henawy, Allan Sadun, Ryan Miller, Luca Daniel, Jacob K White, and Duane S Boning · 2020
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Annealed flow transport monte carlo
Michal Arbel, Alexander G. de G. Matthews, and A. Doucet · 2021
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Adaptive monte carlo augmented with normalizing flows
Marylou Gabri’e, Grant M. Rotskoff, and Eric Vanden-Eijnden · 2021
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Normalizing flows for probabilistic modeling and inference
George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, and Balaji Lakshminarayanan · 2021
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Rare event algorithm study of extreme warm summers and heatwaves over europe
Francesco Ragone and Freddy Bouchet · 2021
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Active learning line sampling for rare event analysis
Jingwen Song, Pengfei Wei, Marcos Valdebenito, and Michael Beer · 2021
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Continual repeated annealed flow transport monte carlo
Alexander G. de G. Matthews, Michal Arbel, Danilo Jimenez Rezende, and A. Doucet · 2022
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A flow-based generative model for rare-event simulation
Lachlan Gibson, Marcus Hoerger, and Dirk Kroese · 2023
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