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Resampling is a key component of sample-based recursive state estimation in particle filters.
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
Neil J Gordon, David J Salmond, and Adrian FM Smith · 1993
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Sequential Monte Carlo methods for dynamic systems
Jun S Liu and Rong Chen · 1998
Earlier work this paper cites.
Probabilistic robotics
Sebastian Thrun, Wolfram Burgard, and Dieter Fox · 2005
Earlier work this paper cites.
PointNet: Deep learning on point sets for 3D classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan R Salakhutdinov, and Alexander J Smola · 2017
Cited alongside, same era.
Differentiable particle filters: End-to-end learning with algorithmic priors
Rico Jonschkowski, Divyam Rastogi, and Oliver Brock · 2018
Cited alongside, same era.
Particle filter networks with application to visual localization
Peter Karkus, David Hsu, and Wee Sun Lee · 2018
Later among the works it cites.
Set transformer: A framework for attention-based permutation-invariant neural networks
Juho Lee, Yoonho Lee, Jungtaek Kim, Adam Kosiorek, Seungjin Choi, and Yee Whye Teh · 2019
Later among the works it cites.
Particle filter recurrent neural networks
Xiao Ma, Peter Karkus, David Hsu, and Wee Sun Lee · 2019
Later among the works it cites.
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