ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2001.10917
  4. Cited By
High-dimensional Central Limit Theorems by Stein's Method

High-dimensional Central Limit Theorems by Stein's Method

29 January 2020
Xiao Fang
Yuta Koike
ArXivPDFHTML

Papers citing "High-dimensional Central Limit Theorems by Stein's Method"

14 / 14 papers shown
Title
Quantitative CLTs in Deep Neural Networks
Quantitative CLTs in Deep Neural Networks
Stefano Favaro
Boris Hanin
Domenico Marinucci
I. Nourdin
G. Peccati
BDL
43
12
0
12 Jul 2023
Sharp Deviations Bounds for Dirichlet Weighted Sums with Application to
  analysis of Bayesian algorithms
Sharp Deviations Bounds for Dirichlet Weighted Sums with Application to analysis of Bayesian algorithms
Denis Belomestny
Pierre Menard
A. Naumov
D. Tiapkin
Michal Valko
22
2
0
06 Apr 2023
Testing Many Constraints in Possibly Irregular Models Using Incomplete
  U-Statistics
Testing Many Constraints in Possibly Irregular Models Using Incomplete U-Statistics
Nils Sturma
Mathias Drton
Dennis Leung
30
3
0
24 Aug 2022
Berry-Esseen Theorem for Sample Quantiles with Locally Dependent Data
Berry-Esseen Theorem for Sample Quantiles with Locally Dependent Data
P. Dey
Grigory Terlov
21
0
0
18 Aug 2022
High-dimensional Data Bootstrap
High-dimensional Data Bootstrap
Victor Chernozhukov
Denis Chetverikov
Kengo Kato
Yuta Koike
33
28
0
19 May 2022
A Cheap Bootstrap Method for Fast Inference
A Cheap Bootstrap Method for Fast Inference
Henry Lam
29
11
0
31 Jan 2022
Rerandomization with Diminishing Covariate Imbalance and Diverging
  Number of Covariates
Rerandomization with Diminishing Covariate Imbalance and Diverging Number of Covariates
Yuhao Wang
Xinran Li
38
14
0
06 Sep 2021
Nearly optimal central limit theorem and bootstrap approximations in
  high dimensions
Nearly optimal central limit theorem and bootstrap approximations in high dimensions
Victor Chernozhukov
Denis Chetverikov
Yuta Koike
25
42
0
17 Dec 2020
Central Limit Theorem and Near classical Berry-Esseen rate for self
  normalized sums in high dimensions
Central Limit Theorem and Near classical Berry-Esseen rate for self normalized sums in high dimensions
Debraj Das
36
0
0
07 Dec 2020
High-dimensional CLT for Sums of Non-degenerate Random Vectors:
  $n^{-1/2}$-rate
High-dimensional CLT for Sums of Non-degenerate Random Vectors: n−1/2n^{-1/2}n−1/2-rate
Arun K. Kuchibhotla
Alessandro Rinaldo
18
19
0
28 Sep 2020
Central Limit Theorem and Bootstrap Approximation in High Dimensions:
  Near $1/\sqrt{n}$ Rates via Implicit Smoothing
Central Limit Theorem and Bootstrap Approximation in High Dimensions: Near 1/n1/\sqrt{n}1/n​ Rates via Implicit Smoothing
Miles E. Lopes
22
20
0
13 Sep 2020
Inference for high-dimensional exchangeable arrays
Inference for high-dimensional exchangeable arrays
Harold D. Chiang
Kengo Kato
Yuya Sasaki
44
12
0
10 Sep 2020
Improved Central Limit Theorem and bootstrap approximations in high
  dimensions
Improved Central Limit Theorem and bootstrap approximations in high dimensions
Victor Chernozhukov
Denis Chetverikov
Kengo Kato
Yuta Koike
39
74
0
22 Dec 2019
Comparison and anti-concentration bounds for maxima of Gaussian random
  vectors
Comparison and anti-concentration bounds for maxima of Gaussian random vectors
Victor Chernozhukov
Denis Chetverikov
Kengo Kato
68
220
0
21 Jan 2013
1