A proposal for improving EEG microstate generation via interpretable deep clustering with convolutional autoencoders.

Arjun Vinayak Chikkankod; Luca Longo

A proposal for improving EEG microstate generation via interpretable deep clustering with convolutional autoencoders.

Arjun Vinayak Chikkankod
, Luca Longo

School of Computer Science and Information Technology

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

Original language	Undefined/Unknown
Title of host publication	xAI (Late-breaking Work, Demos, Doctoral Consortium)
Pages	25-32
Number of pages	8
Publication status	Published - 2024

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@inproceedings{82c15fd2df374263aa633d1631b024a4,

title = "A proposal for improving EEG microstate generation via interpretable deep clustering with convolutional autoencoders.",

author = "Chikkankod, \{Arjun Vinayak\} and Luca Longo",

note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",

year = "2024",

language = "Undefined/Unknown",

pages = "25--32",

booktitle = "xAI (Late-breaking Work, Demos, Doctoral Consortium)",

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AU - Chikkankod, Arjun Vinayak

AU - Longo, Luca

N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2024

Y1 - 2024

M3 - Conference proceeding

SP - 25

EP - 32

BT - xAI (Late-breaking Work, Demos, Doctoral Consortium)

ER -