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Efficient Multimodal Sampling via Tempered Distribution Flow

Efficient Multimodal Sampling via Tempered Distribution Flow

8 April 2023
Yixuan Qiu
Tianlin Li
    OT
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Papers citing "Efficient Multimodal Sampling via Tempered Distribution Flow"

17 / 17 papers shown
Title
Importance Corrected Neural JKO Sampling
Importance Corrected Neural JKO Sampling
Johannes Hertrich
Robert Gruhlke
88
2
0
29 Jul 2024
A Deep Generative Approach to Conditional Sampling
A Deep Generative Approach to Conditional Sampling
Xingyu Zhou
Yuling Jiao
Jin Liu
Jian Huang
46
43
0
19 Oct 2021
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity
Jian Huang
Yuling Jiao
Lican Kang
Xu Liao
Jin Liu
Yanyan Liu
74
28
0
21 Jun 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs,
  Normalizing Flows, Energy-Based and Autoregressive Models
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
95
500
0
08 Mar 2021
Your GAN is Secretly an Energy-based Model and You Should use
  Discriminator Driven Latent Sampling
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
Tong Che
Ruixiang Zhang
Jascha Narain Sohl-Dickstein
Hugo Larochelle
Liam Paull
Yuan Cao
Yoshua Bengio
DiffM
DRL
65
114
0
12 Mar 2020
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry
  Suffices
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices
Santosh Vempala
Andre Wibisono
87
265
0
20 Mar 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural
  Transport
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
Matthew Hoffman
Pavel Sountsov
Joshua V. Dillon
I. Langmore
Dustin Tran
Srinivas Vasudevan
BDL
58
106
0
09 Mar 2019
Deep Knockoffs
Deep Knockoffs
Yaniv Romano
Matteo Sesia
Emmanuel J. Candès
BDL
67
141
0
16 Nov 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
414
5,111
0
19 Jun 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
283
8,883
0
25 Aug 2017
Masked Autoregressive Flow for Density Estimation
Masked Autoregressive Flow for Density Estimation
George Papamakarios
Theo Pavlakou
Iain Murray
210
1,352
0
19 May 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a
  nonasymptotic analysis
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis
Maxim Raginsky
Alexander Rakhlin
Matus Telgarsky
73
521
0
13 Feb 2017
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Dan Garber
Laurent Dinh
Chi Jin
Jascha Narain Sohl-Dickstein
Samy Bengio
Praneeth Netrapalli
Aaron Sidford
266
3,696
0
26 May 2016
A Kernel Test of Goodness of Fit
A Kernel Test of Goodness of Fit
Kacper P. Chwialkowski
Heiko Strathmann
Arthur Gretton
BDL
198
328
0
09 Feb 2016
Deep Learning Face Attributes in the Wild
Deep Learning Face Attributes in the Wild
Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
244
8,408
0
28 Nov 2014
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
292
3,279
0
09 Jun 2012
A Kernel Method for the Two-Sample Problem
A Kernel Method for the Two-Sample Problem
Arthur Gretton
Karsten Borgwardt
Malte J. Rasch
Bernhard Schölkopf
Alex Smola
231
2,360
0
15 May 2008
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