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1Can A.I. do our literature reviews for us?
https://twitter.com/chris_bail/status/1517158680025870339?t=_qZ0Itw7mqkB2mRc7OAYNw&s=19
2 years ago by @becker
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literature
the
art
of
gpt3
review
immermind
stater
literaturetheartofgpt3reviewimmermindstater
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1Differential co-expression-based detection of conditional relationships in transcriptional data: comparative analysis and application to breast cancer | SpringerLink
https://link.springer.com/article/10.1186/s13059-019-1851-8
3 years ago by @becker
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gene
correlation
review
survey
coexpression
differential
paper:fastcor
dgca
genecorrelationreviewsurveycoexpressiondifferentialpaper:fastcordgca
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1hurcy/awesome-ehr-deeplearning: Curated list of awesome papers for electronic health records(EHR) mining, machine learning, and deep learning.
https://github.com/hurcy/awesome-ehr-deeplearning
4 years ago by @becker
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awesome
overview
deep
cureated
data
review
learning
survey
list
ehr
awesomeoverviewdeepcureateddatareviewlearningsurveylistehr
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1PPL APIs
https://colcarroll.github.io/ppl-api/
4 years ago by @becker
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overview
comparison
language
probabilistic
review
ppl
list
programming
overviewcomparisonlanguageprobabilisticreviewppllistprogramming
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1Disentanglement with Variational Autoencoder: A Review
https://towardsdatascience.com/disentanglement-with-variational-autoencoder-a-review-653a891b69bd
5 years ago by @becker
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variational
beta
autoencoder
auto
survery
disentangle
towardsdatascience.com
vae
review
disentanglement
encoder
variationalbetaautoencoderautosurverydisentangletowardsdatascience.comvaereviewdisentanglementencoder
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1PC FAQ – Ecai 2020
http://ecai2020.eu/pc-faq/
5 years ago by @becker
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cirteria
guidelines
review
ecai
helpful
cirteriaguidelinesreviewecaihelpful
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1Journals and Funders Confront Implicit Bias in Peer Review | AAAS - The World's Largest General Scientific Society
https://www.aaas.org/news/journals-and-funders-confront-implicit-bias-peer-review
7 years ago by @becker
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nationality
gender
peer
bias
paper:country
review
nationalitygenderpeerbiaspaper:countryreview
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1PC Member Login
https://wi-lab.com/cyberchair/2013/icdm13/pcmb/pc_index.php?subarea=DM
11 years ago by @hotho
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icdm
2013
review
icdm2013review
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1/home/lcharlin/school/research/matching_system/reviewer_data/pubs/papers/hotho@cs.uni-kassel.de – File Manager hotho@cs.uni-kassel.de
http://papermatching.cs.toronto.edu/webapp/fm/
12 years ago by @hotho
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ecml
paper
bidding
manager
review
pkdd
ecmlpaperbiddingmanagerreviewpkdd
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1Elsevier Editorial SystemTM
Full-Function Web-Enabled Manuscript Submission and Tracking System for Peer Review
12 years ago by @hotho
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editor
area
semantic
journal
web
jws
review
editorareasemanticjournalwebjwsreview
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1Login - ECMLPKDD'13
https://cmt.research.microsoft.com/ECMLPKDD2013/
12 years ago by @hotho
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ecml
2013
review
pkdd
ecml2013reviewpkdd
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120th European Conference on Artificial Intelligence
http://ecai2012.confmaster.net/pages/login.php?Conf=ECAI2012
13 years ago by @hotho
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system
review
ecai
systemreviewecai
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1EasyChair Login Page
https://www.easychair.org/account/signin.cgi
14 years ago by @hotho
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system
review
easychair
systemrevieweasychair
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1ScholarOne Manuscripts
http://mc.manuscriptcentral.com/tham
14 years ago by @hotho
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journal
review
journalreview
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1Lower Bounds for Selection in X + Y and Other Multisets
http://portal.acm.org/citation.cfm?doid=322092.322097
14 years ago by @cscholz
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review
sum
subset
reviewsumsubset
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1Technology Review | 29.03.10 | Mein Job beim Big Brother
Internet-Überwacher lassen sich bei ihrer Arbeit nicht gern über die Schulter schauen. Für Technology Review gewährte ein Insider einen Blick hinter die Kulissen.
15 years ago by @hotho
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brother
bericht
review
überwachung
technology
big
internet
brotherberichtreviewüberwachungtechnologybiginternet
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1ISTweb - Emerging Technologies and Infrastructures - FET - Useful documents
Information Society Technologies website
15 years ago by @hotho
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management
fet
hinweise
review
eu
managementfethinweiserevieweu
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1Twenty-Fourth AAAI Conference on Artificial Intelligence
http://aaai.confmaster.de/pages/welcome.php?Conf=AAAI2010&PHPSESSID=0fc5c1eda3f639393bde06c1db51453a
15 years ago by @hotho
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conference
review
aaai
2010
conferencereviewaaai2010
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1GOR10 - ConfTool Pro - Login
http://conftool.gor.de/conftool10/
15 years ago by @hotho
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web
gor10
review
conftool
webgor10reviewconftool
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1Login
https://cmt.research.microsoft.com/WWW2010/Default.aspx
15 years ago by @hotho
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www
review
2010
wwwreview2010
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publications (hide)49
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8Representation Learning: A Review and New Perspectives
Y. Bengio, A. Courville, and P. Vincent. IEEE Trans. Pattern Anal. Mach. Intell., 35 (8): 1798-1828 (2013)
6 months ago by @hotho
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toread
perspectives
review
learning
representation
toreadperspectivesreviewlearningrepresentation
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2Image segmentation using deep learning: A survey
S. Minaee, Y. Boykov, F. Porikli, A. Plaza, N. Kehtarnavaz, and D. Terzopoulos. IEEE transactions on pattern analysis and machine intelligence, (2021)
2 years ago by @becker
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image
citedby:scholar:timestamp:2023-1-5
hecodex
review
segmentation
survey
citedby:scholar:count:1330
imagecitedby:scholar:timestamp:2023-1-5hecodexreviewsegmentationsurveycitedby:scholar:count:1330
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2Integrating Machine Learning with Human Knowledge
C. Deng, X. Ji, C. Rainey, J. Zhang, and W. Lu. iScience, 23 (11): 101656 (2020)
2 years ago by @becker
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background
machine
review
learning
survey
knowledge
integration
backgroundmachinereviewlearningsurveyknowledgeintegration
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250 years of hormonal contraception—time to find out, what it does to our brain
B. Pletzer, and H. Kerschbaum. Frontiers in neuroscience, (2014)
2 years ago by @becker
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m:id:contraception:coordinate:y:-518.6786193847656
neural
citedby:scholar:timestamp:2022-5-5
neuro
m:id:contraception:node
contraception
m:
brain
citedby:scholar:count:107
project:contraception
review
m:id:contraception:coordinate:x:-384.2443389892578
survey
m:id:contraception:coordinate:y:-518.6786193847656neuralcitedby:scholar:timestamp:2022-5-5neurom:id:contraception:nodecontraceptionm:braincitedby:scholar:count:107project:contraceptionreviewm:id:contraception:coordinate:x:-384.2443389892578survey
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1Using Community Ecology Theory and Computational Microbiome Methods To Study Human Milk as a Biological System
L. Shenhav, and M. Azad. mSystems, 7 (1): e01132--21 (2022)
3 years ago by @becker
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machine
review
milk
learning
survey
human
computational
machinereviewmilklearningsurveyhumancomputational
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1AI in health and medicine
P. Rajpurkar, E. Chen, O. Banerjee, and E. Topol. Nature Medicine, (2022)
3 years ago by @becker
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citedby:scholar:timestamp:2022-2-9
artificial
citedby:scholar:count:1
nature
machine
ai
review
learning
medicine
survey
health
intelligence
citedby:scholar:timestamp:2022-2-9artificialcitedby:scholar:count:1naturemachineaireviewlearningmedicinesurveyhealthintelligence
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1Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review
Y. Si, J. Du, Z. Li, X. Jiang, T. Miller, F. Wang, W. Zheng, and K. Roberts. Journal of Biomedical Informatics, (2021)
3 years ago by @becker
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citedby:scholar:count:12
deep
records
learning
representation
health
ehr
citedby:scholar:timestamp:2021-12-15
record
review
survey
embedding
electronic
citedby:scholar:count:12deeprecordslearningrepresentationhealthehrcitedby:scholar:timestamp:2021-12-15recordreviewsurveyembeddingelectronic
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1A survey on contrastive self-supervised learning
A. Jaiswal, A. Babu, M. Zadeh, D. Banerjee, and F. Makedon. Technologies, 9 (1): 2 (2021)
3 years ago by @becker
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citedby:scholar:count:67
supervised
contrastive
review
learning
survey
self
citedby:scholar:timestamp:2021-10-17
citedby:scholar:count:67supervisedcontrastivereviewlearningsurveyselfcitedby:scholar:timestamp:2021-10-17
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1Machine learning for perturbational single-cell omics
Y. Ji, M. Lotfollahi, F. Wolf, and F. Theis. Cell Systems, 12 (6): 522--537 (2021)
3 years ago by @becker
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models
modeling
deep
wolf
perturbation
theis
learning
multi
cell
omics
background
machine
multiomics
review
survey
model
knowledge
single
generative
integration
modelsmodelingdeepwolfperturbationtheislearningmulticellomicsbackgroundmachinemultiomicsreviewsurveymodelknowledgesinglegenerativeintegration
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1A Comprehensive Survey on Graph Neural Networks
Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and P. Yu. IEEE Transactions on Neural Networks and Learning Systems, (2020)
3 years ago by @becker
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project:bmbf
neural
review
networks
graph
paper:fastcor
project:bmbfneuralreviewnetworksgraphpaper:fastcor
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2Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
A. Andoni, and P. Indyk. 2006 47th annual IEEE symposium on foundations of computer science (FOCS'06), page 459--468. IEEE, (2006)
4 years ago by @becker
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approximate
hashing
lsh
sensitive
review
locality
survey
nearest
neighbor
nn
paper:fastcor
approximatehashinglshsensitivereviewlocalitysurveynearestneighbornnpaper:fastcor
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1Multi-omics data integration, interpretation, and its application
I. Subramanian, S. Verma, S. Kumar, A. Jere, and K. Anamika. Bioinformatics and biology insights, (2020)
4 years ago by @becker
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citedby:scholar:timestamp:2021-2-14
paper:milkreview:selected
data
citedby:scholar:count:57
application
multi
paper:fastcor
p21
omics
multiomics
review
survey
relatedwork
integration
citedby:scholar:timestamp:2021-2-14paper:milkreview:selecteddatacitedby:scholar:count:57applicationmultipaper:fastcorp21omicsmultiomicsreviewsurveyrelatedworkintegration
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1Omics, big data and machine learning as tools to propel understanding of biological mechanisms and to discover novel diagnostics and therapeutics
N. Perakakis, A. Yazdani, G. Karniadakis, and C. Mantzoros. Metabolism-Clinical and Experimental, (2018)
4 years ago by @becker
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editorial
omics
methods
citedby:scholar:count:25
machine
multiomics
review
learning
survey
citedby:scholar:timestamp:2020-8-6
descritpion
editorialomicsmethodscitedby:scholar:count:25machinemultiomicsreviewlearningsurveycitedby:scholar:timestamp:2020-8-6descritpion
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1A survey of multi-view machine learning
S. Sun. Neural computing and applications, 23 (7-8): 2031--2038 (2013)
4 years ago by @becker
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multiview
view
citedby:scholar:timestamp:2020-7-29
review
learning
survey
citedby:scholar:count:576
multi
multiviewviewcitedby:scholar:timestamp:2020-7-29reviewlearningsurveycitedby:scholar:count:576multi
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1A review on machine learning principles for multi-view biological data integration
Y. Li, F. Wu, and A. Ngom. Briefings in bioinformatics, 19 (2): 325--340 (2018)
4 years ago by @becker
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biology
multiview
view
citedby:scholar:timestamp:2020-7-29
paper:milkreview:selected
omics
citedby:scholar:count:143
multiomics
review
relatedwork
multi
p21
biologymultiviewviewcitedby:scholar:timestamp:2020-7-29paper:milkreview:selectedomicscitedby:scholar:count:143multiomicsreviewrelatedworkmultip21
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1Systems immunology: just getting started
M. Davis, C. Tato, and D. Furman. Nat Immunol, 18 (7): 725-732 (June 2017)
4 years ago by @becker
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overview
immune
system
systems
review
survey
relatedwork
immunology
p21
overviewimmunesystemsystemsreviewsurveyrelatedworkimmunologyp21
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2A survey of transfer learning
K. Weiss, T. Khoshgoftaar, and D. Wang. Journal of Big data, 3 (1): 9 (2016)
5 years ago by @becker
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project:bmbf
adaption
nalab
deep
neural
learning
network
networks
p21
domain
transfer
review
survey
relatedwork
project:bmbfadaptionnalabdeepneurallearningnetworknetworksp21domaintransferreviewsurveyrelatedwork
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1A survey on transfer learning
S. Pan, and Q. Yang. IEEE Transactions on knowledge and data engineering, 22 (10): 1345--1359 (2009)
5 years ago by @becker
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domain
adaption
nalab
transfer
deep
neural
review
learning
survey
network
networks
domainadaptionnalabtransferdeepneuralreviewlearningsurveynetworknetworks
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3A survey on deep transfer learning
C. Tan, F. Sun, T. Kong, W. Zhang, C. Yang, and C. Liu. International conference on artificial neural networks, page 270--279. Springer, (2018)
5 years ago by @becker
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domain
project:bmbf
adaption
nalab
transfer
deep
neural
review
learning
survey
network
networks
domainproject:bmbfadaptionnalabtransferdeepneuralreviewlearningsurveynetworknetworks
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3Machine Learning on Human Connectome Data from MRI
C. Brown, and G. Hamarneh. (2016)cite arxiv:1611.08699Comment: 51 pages, 6 figures. To be submitted to a journal.
5 years ago by @becker
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image
nalab
functional
disruption
cordis
learning
images
fmri
brain
correlation
machine
connectome
review
survey
imagenalabfunctionaldisruptioncordislearningimagesfmribraincorrelationmachineconnectomereviewsurvey
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