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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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correlation
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coexpression
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dgca
genecorrelationreviewsurveycoexpressiondifferentialpaper:fastcordgca
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1GitHub - sebastianruder/NLP-progress: Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
https://github.com/sebastianruder/NLP-progress
3 years ago by @hotho
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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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1Marc Sebban - Homepage
https://perso.univ-st-etienne.fr/sebbanma/
5 years ago by @hotho
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learning
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2KI-Landkarte (Karte) - PLS
https://www.plattform-lernende-systeme.de/ki-landkarte.html
5 years ago by @hotho
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Germany
DeutschlandÜbersichtlandkarteAIsurveyinstitutekiGermany
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1ALLBUS: ALLBUS
https://www.gesis.org/allbus/allbus/
7 years ago by @becker
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1ISSP: Home
https://www.gesis.org/issp/home/
7 years ago by @becker
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1Data and Documentation by Year | European Social Survey (ESS)
http://www.europeansocialsurvey.org/data/round-index.html
7 years ago by @becker
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1Wearable Technology Database | Vandrico Inc
http://vandrico.com/wearables/
7 years ago by @hotho
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list
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1Deep Learning - Scholarpedia
Deep Learning has revolutionised Pattern Recognition and Machine Learning. It is about credit assignment in adaptive systems with long chains of potentially causal links between actions and consequences.
8 years ago by @hotho
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learning
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wikipedia
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6Publications
http://www.ontologymatching.org/publications.html
10 years ago by @hotho
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surveymatchingontology
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1Das Poster - Le Poster – The Poster - Il Poster
http://www.computerposter.ch/
13 years ago by @hotho
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computer
informatik
überblick
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history
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computerinformatiküberblicksurveyhistorygeschichte
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1KWTR: Ontology Learning - semanticweb.org
http://semanticweb.org/wiki/KWTR:_Ontology_Learning
14 years ago by @hotho
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ol
tools
surveyoltools
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2MAGIX Blog - Das deutsche Social Media Prisma
http://blog.magix.com/de/archives/783-Das-deutsche-Social-Media-Prisma.html
15 years ago by @hotho
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überblick
landschaft
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1Public Deliverables
http://www.mymediaproject.org/Deliverables.aspx
15 years ago by @hotho
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state_of_the_artsurveyrecommender
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1Yury Lifshits | A Guide to Web Research
http://yury.name/webguide/
15 years ago by @hotho
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2Kochbuch / FrontPage
http://kochbuch.pbwiki.com/
15 years ago by @hotho
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2.0
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1weberwu's plagiat Bookmarks on Delicious
http://delicious.com/weberwu/plagiat
15 years ago by @hotho
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plagiatplagiarismsurvey
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4netbib weblog » Literaturverwaltungsprogramme …
http://log.netbib.de/archives/2009/03/27/literaturverwaltungsprogramme-3/
15 years ago by @hotho
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literature
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Bibliothek
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literaturelibraryBibliothekLiteraturverwaltungsurveyvortragtools
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1100 Social Networks to Help You Reach All Your Goals | Rated Colleges
http://www.ratedcolleges.com/blog/2009/100-social-networks-to-help-you-reach-all-your-goals/
15 years ago by @hotho
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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)
a year 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)
2 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)
2 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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2Deep 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)
2 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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2A survey on image data augmentation for deep learning
C. Shorten, and T. Khoshgoftaar. Journal of Big Data, 6 (1): 1--48 (2019)
2 years ago by @becker
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image
citedby:scholar:timestamp:2021-11-23
deep
citedby:scholar:count:2261
data
learning
survey
augmentation
imagecitedby:scholar:timestamp:2021-11-23deepcitedby:scholar:count:2261datalearningsurveyaugmentation
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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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3A survey of outlier detection methodologies
V. Hodge, and J. Austin. Artificial intelligence review, 22 (2): 85--126 (2004)
3 years ago by @becker
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project:bmbf
citedby:scholar:count:3689
detection
outlier
survey
citedby:scholar:timestamp:2021-7-28
project:bmbfcitedby:scholar:count:3689detectionoutliersurveycitedby:scholar:timestamp:2021-7-28
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2A comprehensive survey of anomaly detection techniques for high dimensional big data
S. Thudumu, P. Branch, J. Jin, and J. Singh. Journal of Big Data, 7 (1): 1--30 (2020)
3 years ago by @becker
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project:bmbf
detection
citedby:scholar:count:23
outlier
survey
citedby:scholar:timestamp:2021-7-28
project:bmbfdetectioncitedby:scholar:count:23outliersurveycitedby:scholar:timestamp:2021-7-28
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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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7An overview of multi-task learning in deep neural networks
S. Ruder. arXiv preprint arXiv:1706.05098, (2017)
3 years ago by @becker
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overview
citedby:scholar:count:1237
task
paper:milkreview:selected
deep
neural
machine
learning
survey
networks
multi
citedby:scholar:timestamp:2021-5-29
overviewcitedby:scholar:count:1237taskpaper:milkreview:selecteddeepneuralmachinelearningsurveynetworksmulticitedby:scholar:timestamp:2021-5-29
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1Multi-task learning for dense prediction tasks: A Survey
S. Vandenhende, S. Georgoulis, W. Van Gansbeke, M. Proesmans, D. Dai, and L. Van Gool. IEEE Transactions on Pattern Analysis and Machine Intelligence, (2021)
3 years ago by @becker
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multitask
task
toread
citedby:scholar:count:6
learning
survey
multi
citedby:scholar:timestamp:2021-5-29
multitasktasktoreadcitedby:scholar:count:6learningsurveymulticitedby:scholar:timestamp:2021-5-29
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2Multi-Task Learning with Deep Neural Networks: A Survey
M. Crawshaw. arXiv preprint arXiv:2009.09796, (2020)
3 years ago by @becker
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multitask
task
toread
citedby:scholar:count:12
learning
survey
multi
citedby:scholar:timestamp:2021-5-29
multitasktasktoreadcitedby:scholar:count:12learningsurveymulticitedby:scholar:timestamp:2021-5-29
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1A survey on multi-task learning
Y. Zhang, and Q. Yang. IEEE Transactions on Knowledge and Data Engineering, (2021)
3 years ago by @becker
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citedby:scholar:count:635
multitask
task
paper:milkreview:selected
learning
survey
multi
citedby:scholar:timestamp:2021-5-29
citedby:scholar:count:635multitasktaskpaper:milkreview:selectedlearningsurveymulticitedby:scholar:timestamp:2021-5-29
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1Multimodal machine learning: A survey and taxonomy
T. Baltrusaitis, C. Ahuja, and L. Morency. IEEE transactions on pattern analysis and machine intelligence, 41 (2): 423--443 (2018)
3 years ago by @becker
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citedby:scholar:count:842
paper:milkreview:selected
machine
learning
survey
taxonomy
model
multimodal
multi
citedby:scholar:timestamp:2021-5-29
citedby:scholar:count:842paper:milkreview:selectedmachinelearningsurveytaxonomymodelmultimodalmulticitedby:scholar:timestamp:2021-5-29
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1Deep Learning for Anomaly Detection
G. Pang, C. Shen, L. Cao, and A. Hengel. ACM Computing Surveys, 54 (2): 1--38 (March 2021)
3 years ago by @hotho
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anomaly
detection
survey
2020
anomalydetectionsurvey2020
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3A Survey of the State of Explainable AI for Natural Language Processing
M. Danilevsky, K. Qian, R. Aharonov, Y. Katsis, B. Kawas, and P. Sen. (2020)cite arxiv:2010.00711Comment: To appear in AACL-IJCNLP 2020.
3 years ago by @hotho
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nlp
survey
xai
nlpsurveyxai
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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)
3 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)
3 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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