Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.

A. Singh, R. Borsoi, D. Erdogmus, and T. Imbiriba. ICLR, OpenReview.net, (2024)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Cengiz Deniz

Vedat Deniz

Abdülkerim Deniz

Esen Deniz

Engin Deniz

Other publications of authors with the same name

An analysis of entropy estimators for blind source separationK. II, D. Erdogmus, and J. Principe. Signal Processing, 86 (1): 182--194 (January 2006)RKHS Bayes Discriminant: A Subspace Constrained Nonlinear Feature Projection for Signal Detection.U. Ozertem, and D. Erdogmus. IEEE Trans. Neural Networks, 20 (7): 1195-1203 (2009)Principal Curves as Skeletons of Tubular Objects - Locally Characterizing the Structures of Axons.E. Bas, and D. Erdogmus. Neuroinformatics, 9 (2-3): 181-191 (2011)Divide-and-conquer approach for brain machine interfaces: nonlinear mixture of competitive linear models.S. Kim, J. Sanchez, D. Erdogmus, Y. Rao, J. Wessberg, J. Príncipe, and M. Nicolelis. Neural Networks, 16 (5-6): 865-871 (2003)On visually evoked potentials in eeg induced by multiple pseudorandom binary sequences for brain computer interface design.H. Nezamfar, U. Orhan, D. Erdogmus, K. II, S. Purwar, B. Oken, and M. Fried-Oken. ICASSP, page 2044-2047. IEEE, (2011)Minimax Mutual Information Approach for ICA of Complex-Valued Linear Mixtures.J. Xu, D. Erdogmus, Y. Rao, and J. Príncipe. ICA, volume 3195 of Lecture Notes in Computer Science, page 311-318. Springer, (2004)Robust Classification in RSVP Keyboard.M. Higger, M. Akçakaya, U. Orhan, and D. Erdogmus. HCI (24), volume 8027 of Lecture Notes in Computer Science, page 443-449. Springer, (2013)Linear-least-squares initialization of multilayer perceptrons through backpropagation of the desired response.D. Erdogmus, O. Fontenla-Romero, J. Príncipe, A. Alonso-Betanzos, and E. Castillo. IEEE Trans. Neural Networks, 16 (2): 325-337 (2005)Gaussianization: An Efficient Multivariate Density Estimation Technique for Statistical Signal Processing.D. Erdogmus, R. Jenssen, Y. Rao, and J. Príncipe. VLSI Signal Processing, 45 (1-2): 67-83 (2006)A recursive Renyi's entropy estimator.D. Erdogmus, J. Príncipe, S. Kim, and J. Sanchez. NNSP, page 209-217. IEEE, (2002)

BibSonomy

Disambiguation of "Erdogmus, Deniz"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.

Please choose a person to relate this publication to

Cengiz Deniz

Vedat Deniz

Abdülkerim Deniz

Esen Deniz

Engin Deniz

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Erdogmus, Deniz"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.

Please choose a person to relate this publication to

Cengiz Deniz

Vedat Deniz

Abdülkerim Deniz

Esen Deniz

Engin Deniz

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.