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M. Westover

20 papers hereh-index 252.4k citations123 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author12
  • last author5

Across the 17 of 20 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.CL3
  • eess.SP2
  • stat.ME2
  • astro-ph1
  • astro-ph.CO1
same name
  • M. Westover — 4 papers, h 6
  • M. Westover — 3 papers, h 3
  • M. Westover — 2 papers, h 15
  • M. Westover — 1 paper, h 37

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20022024
most citedThe 2MASS Redshift Survey - Description and Data Release

741 citations · 1.1k across the 20 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CL2021

Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records

Tanish Tyagi, Colin G. Magdamo, Ayush Noori +22

Dementia is a neurodegenerative disorder that causes cognitive decline and affects more than 50 million people worldwide. Dementia is under-diagnosed by healthcare professionals -…

eess.SP2021★ 20 cited

Self-supervised EEG Representation Learning for Automatic Sleep Staging

Chaoqi Yang, Danica Xiao, M. Brandon Westover +1

Background: Deep learning models have shown great success in automating tasks in sleep medicine by learning from carefully annotated Electroencephalogram (EEG) data. However, effec…

math.NA2021★ 6 cited

ATD: Augmenting CP Tensor Decomposition by Self Supervision

Chaoqi Yang, Cheng Qian, Navjot Singh +4

Tensor decompositions are powerful tools for dimensionality reduction and feature interpretation of multidimensional data such as signals. Existing tensor decomposition objectives…

cs.LG2021

SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models

Zhen Lin, Cao Xiao, Lucas Glass +2

Despite deep learning (DL) success in classification problems, DL classifiers do not provide a sound mechanism to decide when to refrain from predicting. Recent works tried to cont…

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