Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2001.04341
Cited By
v1
v2
v3
v4 (latest)
Information Newton's flow: second-order optimization method in probability space
13 January 2020
Yifei Wang
Wuchen Li
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Information Newton's flow: second-order optimization method in probability space"
25 / 25 papers shown
Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
Naoya Yamamoto
Juno Kim
Taiji Suzuki
171
1
0
21 Sep 2025
Towards understanding Accelerated Stein Variational Gradient Flow -- Analysis of Generalized Bilinear Kernels for Gaussian target distributions
Viktor Stein
Wuchen Li
251
2
0
04 Sep 2025
A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations
Shu Liu
Stanley Osher
Wuchen Li
389
3
0
09 Nov 2024
Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalities
José A. Carrillo
Yifan Chen
Daniel Zhengyu Huang
Jiaoyang Huang
Dongyi Wei
AI4CE
404
11
0
22 Jul 2024
Wasserstein Gradient Boosting: A General Framework with Applications to Posterior Regression
Neural Information Processing Systems (NeurIPS), 2024
Takuo Matsubara
213
0
0
15 May 2024
Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space
Mingyang Yi
Bohan Wang
436
0
0
24 Jan 2024
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow
Neural Information Processing Systems (NeurIPS), 2023
Ziheng Cheng
Shiyue Zhang
Longlin Yu
Cheng Zhang
BDL
241
13
0
25 Oct 2023
Sampling via Gradient Flows in the Space of Probability Measures
Yifan Chen
Daniel Zhengyu Huang
Jiaoyang Huang
Sebastian Reich
Andrew M. Stuart
491
20
0
05 Oct 2023
Wasserstein Mirror Gradient Flow as the limit of the Sinkhorn Algorithm
Nabarun Deb
Young-Heon Kim
Soumik Pal
Geoffrey Schiebinger
261
18
0
31 Jul 2023
Information Geometry of Wasserstein Statistics on Shapes and Affine Deformations
Information Geometry (IG), 2023
S. Amari
Takeru Matsuda
364
12
0
24 Jul 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
559
16
0
23 May 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
890
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
297
23
0
25 Nov 2022
A stochastic Stein Variational Newton method
Alex Leviyev
Joshua Chen
Yifei Wang
Omar Ghattas
A. Zimmerman
197
10
0
19 Apr 2022
Projected Wasserstein gradient descent for high-dimensional Bayesian inference
Yifei Wang
Peng Chen
Wuchen Li
273
33
0
12 Feb 2021
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks
Shiwei Lan
Shuyi Li
Babak Shahbaba
UQCV
BDL
365
20
0
11 Jan 2021
Efficient constrained sampling via the mirror-Langevin algorithm
Neural Information Processing Systems (NeurIPS), 2020
Kwangjun Ahn
Sinho Chewi
437
64
0
30 Oct 2020
Wasserstein Statistics in One-dimensional Location-Scale Model
S. Amari
Takeru Matsuda
237
12
0
21 Jul 2020
Momentum Accelerates Evolutionary Dynamics
Marc Harper
Joshua Safyan
221
3
0
05 Jul 2020
Practical Quasi-Newton Methods for Training Deep Neural Networks
Shiqian Ma
Yi Ren
Achraf Bahamou
ODL
535
120
0
16 Jun 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
Neural Information Processing Systems (NeurIPS), 2020
Sinho Chewi
Thibaut Le Gouic
Chen Lu
Tyler Maunu
Philippe Rigollet
404
80
0
03 Jun 2020
Exponential ergodicity of mirror-Langevin diffusions
Sinho Chewi
Thibaut Le Gouic
Chen Lu
Tyler Maunu
Philippe Rigollet
Austin J. Stromme
258
54
0
19 May 2020
Wasserstein statistics in 1D location-scale model
S. Amari
174
2
0
06 Mar 2020
Projected Stein Variational Gradient Descent
Neural Information Processing Systems (NeurIPS), 2020
Peng Chen
Omar Ghattas
BDL
551
80
0
09 Feb 2020
Accelerated Information Gradient flow
Journal of Scientific Computing (J. Sci. Comput.), 2019
Yifei Wang
Wuchen Li
380
57
0
04 Sep 2019
1
Page 1 of 1
