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Law of Log Determinant of Sample Covariance Matrix and Optimal
  Estimation of Differential Entropy for High-Dimensional Gaussian
  Distributions

Law of Log Determinant of Sample Covariance Matrix and Optimal Estimation of Differential Entropy for High-Dimensional Gaussian Distributions

2 September 2013
T. Tony Cai
Tengyuan Liang
Harrison H. Zhou
ArXivPDFHTML

Papers citing "Law of Log Determinant of Sample Covariance Matrix and Optimal Estimation of Differential Entropy for High-Dimensional Gaussian Distributions"

17 / 17 papers shown
Title
Mutual Information Estimation via Normalizing Flows
Mutual Information Estimation via Normalizing Flows
I. Butakov
Alexander Tolmachev
S. Malanchuk
A. Neopryatnaya
Alexey Frolov
40
7
0
04 Mar 2024
INSIDE: LLMs' Internal States Retain the Power of Hallucination
  Detection
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection
Chao Chen
Kai-Chun Liu
Ze Chen
Yi Gu
Yue-bo Wu
Mingyuan Tao
Zhihang Fu
Jieping Ye
HILM
85
86
0
06 Feb 2024
Justices for Information Bottleneck Theory
Justices for Information Bottleneck Theory
Faxian Cao
Yongqiang Cheng
A. Khan
Zhijing Yang
19
0
0
19 May 2023
Diffeomorphic Information Neural Estimation
Diffeomorphic Information Neural Estimation
Bao Duong
T. Nguyen
21
6
0
20 Nov 2022
VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and
  Uncertainty-Spectrum Modeling
VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and Uncertainty-Spectrum Modeling
Beiwen Tian
Liyi Luo
Hao Zhao
Guyue Zhou
27
23
0
20 Oct 2022
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck
Liyi Luo
Beiwen Tian
Hao Zhao
Guyue Zhou
3DPC
24
9
0
17 Sep 2021
Linear spectral statistics of sequential sample covariance matrices
Linear spectral statistics of sequential sample covariance matrices
Nina Dórnemann
Holger Dette
18
3
0
21 Jul 2021
Understanding Neural Networks with Logarithm Determinant Entropy
  Estimator
Understanding Neural Networks with Logarithm Determinant Entropy Estimator
Zhanghao Zhouyin
Ding Liu
FAtt
16
8
0
08 May 2021
Phase transition in noisy high-dimensional random geometric graphs
Phase transition in noisy high-dimensional random geometric graphs
Suqi Liu
Miklós Z. Rácz
9
16
0
28 Mar 2021
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar
Li Jing
Ishan Misra
Yann LeCun
Stéphane Deny
SSL
81
2,299
0
04 Mar 2021
Learning Condition Invariant Features for Retrieval-Based Localization
  from 1M Images
Learning Condition Invariant Features for Retrieval-Based Localization from 1M Images
Janine Thoma
D. Paudel
Ajad Chhatkuli
Luc Van Gool
17
2
0
27 Aug 2020
How Well Generative Adversarial Networks Learn Distributions
How Well Generative Adversarial Networks Learn Distributions
Tengyuan Liang
GAN
16
94
0
07 Nov 2018
Asymptotically Efficient Estimation of Smooth Functionals of Covariance
  Operators
Asymptotically Efficient Estimation of Smooth Functionals of Covariance Operators
V. Koltchinskii
24
30
0
25 Oct 2017
Estimating Large Precision Matrices via Modified Cholesky Decomposition
Estimating Large Precision Matrices via Modified Cholesky Decomposition
Kyoungjae Lee
Jaeyong Lee
32
23
0
04 Jul 2017
Nonparanormal Information Estimation
Nonparanormal Information Estimation
Shashank Singh
Barnabás Póczós
19
20
0
24 Feb 2017
Optimal Bayesian Minimax Rates for Unconstrained Large Covariance
  Matrices
Optimal Bayesian Minimax Rates for Unconstrained Large Covariance Matrices
Kyoungjae Lee
Jaeyong Lee
6
15
0
24 Feb 2017
Bernstein-von Mises Theorems for Functionals of Covariance Matrix
Bernstein-von Mises Theorems for Functionals of Covariance Matrix
Chao Gao
Harrison H. Zhou
16
13
0
01 Dec 2014
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