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Particle based optimization algorithms have recently been developed as sampling methods that iteratively update a set of particles to approximate a target distribution.
Simulated tempering: a new monte carlo scheme
Enzo Marinari and Giorgio Parisi · 1992
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Annealing markov chain monte carlo with applications to ancestral inference
Charles J Geyer and Elizabeth A Thompson · 1995
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Sampling from multimodal distributions using tempered transitions
Radford M Neal · 1996
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The variational formulation of the fokker–planck equation
Richard Jordan, David Kinderlehrer, and Felix Otto · 1998
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On the surprising behavior of distance metrics in high dimensional space
Charu C Aggarwal, Alexander Hinneburg, and Daniel A Keim · 2001
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Bayesian learning via stochastic gradient langevin dynamics
Max Welling and Yee W Teh · 2011
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Sashank J Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, and Larry Wasserman · 2014
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Stein variational gradient descent: A general purpose bayesian inference algorithm
Qiang Liu and Dilin Wang · 2016
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Variational tempering
Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, and David Blei · 2016
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Snapshot ensembles: Train 1, get m for free
Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E Hopcroft, and Kilian Q Weinberger · 2017
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Message passing stein variational gradient descent
Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, and Bo Zhang · 2018
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On the geometry of stein variational gradient descent
A Duncan, Nikolas Nuesken, and Lukasz Szpruch · 2019
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Cyclical annealing schedule: A simple approach to mitigating kl vanishing
Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, and Lawrence Carin · 2019
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Cyclical stochastic gradient mcmc for bayesian deep learning
Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, and Andrew Gordon Wilson · 2019
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Stein variational gradient descent without gradient
Jun Han and Qiang Liu · 2018
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Improving explorability in variational inference with annealed variational objectives
Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, and Aaron C Courville · 2018
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Wei-Cheng Chang, Chun-Liang Li, Youssef Mroueh, and Yiming Yang · 2020
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How good is the bayes posterior in deep neural networks really?
Florian Wenzel, Kevin Roth, Bastiaan S Veeling, Jakub Światkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, and Sebastian Nowozin · 2020
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Stochastic particle-optimization sampling and the non-asymptotic convergence theory
Jianyi Zhang, Ruiyi Zhang, Lawrence Carin, and Changyou Chen · 2020
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