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Projected Wasserstein gradient descent for high-dimensional Bayesian inference
12 February 2021
Yifei Wang
Peng Chen
Wuchen Li
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Papers citing
"Projected Wasserstein gradient descent for high-dimensional Bayesian inference"
18 / 18 papers shown
Sequential Bayesian Design for Efficient Surrogate Construction in the Inversion of Darcy Flows
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Hongqiao Wang
Jinyong Ying
Qingping Zhou
169
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23 Jul 2025
Visual Prompting for One-shot Controllable Video Editing without Inversion
Computer Vision and Pattern Recognition (CVPR), 2025
Zitao Gao
Yuxi Zhou
Duo Peng
Joo-Hwee Lim
Zhigang Tu
De Wen Soh
Lin Geng Foo
DiffM
484
4
0
19 Apr 2025
Path-Guided Particle-based Sampling
International Conference on Machine Learning (ICML), 2024
Mingzhou Fan
Ruida Zhou
C. Tian
Xiaoning Qian
336
10
0
04 Dec 2024
Forward-Euler time-discretization for Wasserstein gradient flows can be wrong
Yewei Xu
Qin Li
273
2
0
12 Jun 2024
Wasserstein Gradient Boosting: A General Framework with Applications to Posterior Regression
Neural Information Processing Systems (NeurIPS), 2024
Takuo Matsubara
222
0
0
15 May 2024
Sampling via Gradient Flows in the Space of Probability Measures
Yifan Chen
Daniel Zhengyu Huang
Jiaoyang Huang
Sebastian Reich
Andrew M. Stuart
503
20
0
05 Oct 2023
Input-gradient space particle inference for neural network ensembles
International Conference on Learning Representations (ICLR), 2023
Trung Trinh
Markus Heinonen
Luigi Acerbi
Samuel Kaski
UQCV
317
4
0
05 Jun 2023
Minimizing
f
f
f
-Divergences by Interpolating Velocity Fields
International Conference on Machine Learning (ICML), 2023
Song Liu
Jiahao Yu
J. Simons
Mingxuan Yi
Mark Beaumont
446
7
0
24 May 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent
Neural Information Processing Systems (NeurIPS), 2023
Tianle Liu
Promit Ghosal
Krishnakumar Balasubramanian
Natesh S. Pillai
565
16
0
23 May 2023
The Score-Difference Flow for Implicit Generative Modeling
Romann M. Weber
DiffM
243
3
0
25 Apr 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space
International Conference on Machine Learning (ICML), 2023
Michael Diao
Krishnakumar Balasubramanian
Sinho Chewi
Adil Salim
BDL
184
47
0
10 Apr 2023
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
Yifan Chen
Daniel Zhengyu Huang
Jiaoyang Huang
Sebastian Reich
Andrew M. Stuart
898
23
0
21 Feb 2023
Particle-based Variational Inference with Preconditioned Functional Gradient Flow
International Conference on Learning Representations (ICLR), 2022
Hanze Dong
Xi Wang
Yong Lin
Tong Zhang
307
23
0
25 Nov 2022
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems
Journal of Computational Physics (JCP), 2022
Lianghao Cao
Thomas O'Leary-Roseberry
Prashant K. Jha
J. Oden
Omar Ghattas
385
37
0
06 Oct 2022
Feature Space Particle Inference for Neural Network Ensembles
International Conference on Machine Learning (ICML), 2022
Shingo Yashima
Teppei Suzuki
Kohta Ishikawa
Ikuro Sato
Rei Kawakami
BDL
377
12
0
02 Jun 2022
Efficient Gradient Flows in Sliced-Wasserstein Space
Clément Bonet
Nicolas Courty
Franccois Septier
Lucas Drumetz
591
23
0
21 Oct 2021
Repulsive Deep Ensembles are Bayesian
Neural Information Processing Systems (NeurIPS), 2021
Francesco DÁngelo
Vincent Fortuin
UQCV
BDL
577
126
0
22 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks
David Alvarez-Melis
Yair Schiff
Youssef Mroueh
350
64
0
01 Jun 2021
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