Fetching the paper…
Reading the bibliography…
We introduce an information-theoretic quantity with similar properties to mutual information that can be estimated from data without making explicit assumptions on the underlying distribution.
Self-organization in a perceptual network
Ralph Linsker · 1988
Earlier work this paper cites.
Matrix Analysis , volume 169
Rajendra Bhatia · 1997
Earlier work this paper cites.
Multidimensional independent component analysis
J-F Cardoso · 1998
Earlier work this paper cites.
Separation of mixed audio sources by independent subspace analysis
Michael A Casey and Alex Westner · 2000
Earlier work this paper cites.
Emergence of phase-and shift-invariant features by decomposition of natural images into independent feature subspaces
Aapo Hyvärinen and Patrik Hoyer · 2000
Earlier work this paper cites.
Independent component analysis: algorithms and applications
Aapo Hyvärinen and Erkki Oja · 2000
Earlier work this paper cites.
Always good turing: Asymptotically optimal probability estimation
Alon Orlitsky, Narayana P Santhanam, and Junan Zhang · 2003
Earlier work this paper cites.
Estimating mutual information
Alexander Kraskov, Harald Stögbauer, and Peter Grassberger · 2004
Earlier work this paper cites.
Measuring statistical dependence with Hilbert-Schmidt norms
Arthur Gretton, Olivier Bousquet, Alex Smola, and Bernhard Schölkopf · 2005
Earlier work this paper cites.
Random features for large-scale kernel machines
Ali Rahimi and Benjamin Recht · 2007
Earlier work this paper cites.
Estimating divergence functionals and the likelihood ratio by convex risk minimization
XuanLong Nguyen, Martin J Wainwright, and Michael I Jordan · 2010
Earlier work this paper cites.
Algorithms for learning kernels based on centered alignment
Corinna Cortes, Mehryar Mohri, and Afshin Rostamizadeh · 2012
Earlier work this paper cites.
Conditional Rényi entropies
Andreia Teixeira, Armando Matos, and Luis Antunes · 2012
Earlier work this paper cites.
Information theoretic learning with infinitely divisible kernels
Luis G. Sanchez Giraldo and Jose C. Principe · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Competitive distribution estimation: Why is good-turing good
Alon Orlitsky and Ananda Theertha Suresh · 2015
Cited alongside, same era.
Measures of entropy from data using infinitely divisible kernels
Luis Gonzalo Sanchez Giraldo, Murali Rao, and Jose C Principe · 2015
Cited alongside, same era.
On deep multi-view representation learning
Weiran Wang, Raman Arora, Karen Livescu, and Jeff Bilmes · 2015
Cited alongside, same era.
Mmd gan: Towards deeper understanding of moment matching network
Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, and Barnabás Póczos · 2017
Cited alongside, same era.
Mine: mutual information neural estimation
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, and R Devon Hjelm · 2018
Cited alongside, same era.
Image-to-image translation for cross-domain disentanglement
Club: A contrastive log-ratio upper bound of mutual information
Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, and Lawrence Carin · 2020
Later among the works it cites.
Formal limitations on the measurement of mutual information
David McAllester and Karl Stratos · 2020
Later among the works it cites.
Learning disentangled representations via mutual information estimation
Eduardo Hugo Sanchez, Mathieu Serrurier, and Mathias Ortner · 2020
Later among the works it cites.
Contrastive multiview coding
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2020
Later among the works it cites.
Cytokine ranking via mutual information algorithm correlates cytokine profiles with presenting disease severity in patients infected with SARS-CoV-2
Kelsey E Huntington, Anna D Louie, Chun Geun Lee, Jack A Elias, Eric A Ross, and Wafik S El-Deiry · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Abel Gonzalez-Garcia, Joost Van De Weijer, and Yoshua Bengio · 2018
Cited alongside, same era.
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
Cited alongside, same era.
Disentangling by factorising
Hyunjik Kim and Andriy Mnih · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Cited alongside, same era.
Learning representations by maximizing mutual information across views
Philip Bachman, R Devon Hjelm, and William Buchwalter · 2019
Cited alongside, same era.
Strong subadditivity of the Rényi entropies for bosonic and fermionic gaussian states
Giancarlo Camilo, Gabriel T. Landi, and Sebas Eliëns · 2019
Cited alongside, same era.
An introduction to variational autoencoders
Diederik P Kingma and Max Welling · 2019
Cited alongside, same era.
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, and Remi Tachet Des Combes · 2021
Later among the works it cites.
Self-supervised learning with data augmentations provably isolates content from style
Julius Von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, and Francesco Locatello · 2021
Later among the works it cites.
Rethinking InfoNCE: How many negative samples do you need?
Chuhan Wu, Fangzhao Wu, and Yongfeng Huang · 2021
Later among the works it cites.
Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
Later among the works it cites.
Efficient density estimation for high-dimensional data
Aref Majdara and Saeid Nooshabadi · 2022
Later among the works it cites.
The representation jensen-rényi divergence
Jhoan Keider Hoyos Osorio, Oscar Skean, Austin J Brockmeier, and Luis Gonzalo Sanchez Giraldo · 2022
Later among the works it cites.
A normal test for independence via generalized mutual information
Jialin Zhang and Zhiyi Zhang · 2022
Later among the works it cites.
Multi-view information bottleneck without variational approximation
Qi Zhang, Shujian Yu, Jingmin Xin, and Badong Chen · 2022
Later among the works it cites.
Adversarial mutual information-guided single domain generalization network for intelligent fault diagnosis
Chao Zhao and Weiming Shen · 2022
Later among the works it cites.