Fetching the paper…
Reading the bibliography…
A common setting for scientific inference is the ability to sample from a high-fidelity forward model (simulation) without having an explicit probability density of the data.
Bayesian-based iterative method of image restoration
William Hadley Richardson · 1972
Earlier work this paper cites.
An iterative technique for the rectification of observed distributions
L. B. Lucy · 1974
Earlier work this paper cites.
Maximum likelihood reconstruction for emission tomography
L. A. Shepp and Y. Vardi · 1982
Earlier work this paper cites.
A Multidimensional unfolding method based on Bayes’ theorem
G. D’Agostini · 1995
Earlier work this paper cites.
The Elements of Statistical Learning
Trevor Hastie, Robert Tibshirani, and Jerome Friedman · 2001
Earlier work this paper cites.
Machine learning approach to inverse problem and unfolding procedure
Nikolai D. Gagunashvili · 2010
Earlier work this paper cites.
Density Ratio Estimation in Machine Learning
Masashi Sugiyama, Taiji Suzuki, and Takafumi Kanamori · 2012
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Tensorflow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al · 2016
Cited alongside, same era.
Machine learning as an instrument for data unfolding
Alexander Glazov · 2017
Cited alongside, same era.
Unification of deconvolution algorithms for Cherenkov astronomy
Mirko Bunse, Nico Piatkowski, Tim Ruhe, Wolfgang Rhode, and Katharina Morik · 2018
Cited alongside, same era.
Unfolding with Generative Adversarial Networks
Kaustuv Datta, Deepak Kar, and Debarati Roy · 2018
Cited alongside, same era.
Deep sets, 2018
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, and Alexander Smola · 2018
Later among the works it cites.
Energy Flow Networks: Deep Sets for Particle Jets
Patrick T. Komiske, Eric M. Metodiev, and Jesse Thaler · 2019
Later among the works it cites.
OmniFold: A Method to Simultaneously Unfold All Observables
Anders Andreassen, Patrick T. Komiske, Eric M. Metodiev, Benjamin Nachman, and Jesse Thaler · 2020
Later among the works it cites.
Unfolding Quantum Computer Readout Noise
B. Nachman, M. Urbanek, W. de Jong, and C. Bauer · 2020
Later among the works it cites.
Neural resampler for Monte Carlo reweighting with preserved uncertainties
Benjamin Nachman and Jesse Thaler · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Invertible Networks or Partons to Detector and Back Again
Marco Bellagente, Anja Butter, Gregor Kasieczka, Tilman Plehn, Armand Rousselot, Ramon Winterhalder, Lynton Ardizzone, and Ullrich Köthe
Cited in the paper.
How to GAN away Detector Effects
Marco Bellagente, Anja Butter, Gregor Kasieczka, Tilman Plehn, and Ramon Winterhalder
Cited in the paper.