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1Profiling and Timing Code | Python Data Science Handbook
https://jakevdp.github.io/PythonDataScienceHandbook/01.07-timing-and-profiling.html
4 years ago by @becker
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memory
python
profile
runtime
profiling
measurement
time
memorypythonprofileruntimeprofilingmeasurementtime
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1python - How to store %%time values in a variable in Jupyter? - Stack Overflow
https://stackoverflow.com/questions/52738709/how-to-store-time-values-in-a-variable-in-jupyter
4 years ago by @becker
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magic
result
jupyter
jupyterlab
python
time
store
timeit
lab
variable
magicresultjupyterjupyterlabpythontimestoretimeitlabvariable
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1How to use Pearson correlation correctly with time series - Cross Validated
https://stats.stackexchange.com/questions/133155/how-to-use-pearson-correlation-correctly-with-time-series
5 years ago by @becker
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spurious
timeseries
pearson
correlation
series
time
spurioustimeseriespearsoncorrelationseriestime
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1google/adb-sync
Preserves timestamps: ```./adb-sync -e ../sdk/platform-tools/adb -R -t /sdcard/DCIM/Camera ~/Pictures/backup/Camera```
5 years ago by @becker
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stamps
date
android
timestamps
stamp
sync
rsync
transfer
file
phone
sdk
time
copy
platform-tools
timestamp
adb
stampsdateandroidtimestampsstampsyncrsynctransferfilephonesdktimecopyplatform-toolstimestampadb
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1TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach | BMC Bioinformatics | Full Text
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-154
5 years ago by @becker
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shen-orr
stanford
time
information
theory
shen-orrstanfordtimeinformationtheory
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1A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring | Nature Medicine
https://www.nature.com/articles/s41591-019-0381-y?fbclid=IwAR3DzRY896PFOVgXNGxTwR-DT2xV0pRyjuTi5IWWMAPRV9NlfCQZHTFXR3Y
5 years ago by @becker
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immune
system
shen-orr
interpolation
stanford
time
model
human
longitudinal
age
immunesystemshen-orrinterpolationstanfordtimemodelhumanlongitudinalage
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1ratschlab/RGAN: Recurrent (conditional) generative adversarial networks for generating real-valued time series data.
https://github.com/ratschlab/RGAN
5 years ago by @becker
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gan
dimensional
neural
dim
conditional
valued
series
real
time
network
recurrent
multi
gandimensionalneuraldimconditionalvaluedseriesrealtimenetworkrecurrentmulti
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1Mage: The Magical Time Series Backend Behind Parse.ly Analytics | Parse.ly
https://blog.parse.ly/post/1633/mage/
6 years ago by @becker
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mage
storm
log
python
py
real
parse.ly
stack
apache
python3
timeseries
spark
kafka
series
processing
dashboard
time
hadoop
logs
s3
magestormlogpythonpyrealparse.lystackapachepython3timeseriessparkkafkaseriesprocessingdashboardtimehadooplogss3
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1Li-wei H. Lehman - Google Scholar Citations
https://scholar.google.ch/citations?hl=en&user=cIjXidQAAAAJ&view_op=list_works&sortby=pubdate
6 years ago by @becker
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medical
timeseries
bayes
mit
series
parametric
medicin
time
nonparametric
non
medicaltimeseriesbayesmitseriesparametricmedicintimenonparametricnon
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1Run multiple commands and kill them as one in bash - Unix & Linux Stack Exchange
https://unix.stackexchange.com/questions/204480/run-multiple-commands-and-kill-them-as-one-in-bash
6 years ago by @becker
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same
the
at
processes
trap
time
two
start
bash
kill
script
sametheatprocessestraptimetwostartbashkillscript
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1A little function to extract heart rates with absolute timestamps from Polar CSV files
https://gist.github.com/mgbckr/ce942044a35dd828be36073ff997e75d
7 years ago by @becker
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polar
csv
python
heartrate
timestamps
hr
rate
heart
python3
watch
absolute
fitness
time
polarcsvpythonheartratetimestampshrrateheartpython3watchabsolutefitnesstime
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1A Comparison of Time Series Databases and Netsil’s Use of Druid
https://blog.netsil.com/a-comparison-of-time-series-databases-and-netsils-use-of-druid-db805d471206
7 years ago by @becker
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comparison
database
series
time
db
databases
comparisondatabaseseriestimedbdatabases
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3patrickzib/SFA: Scalable Time Series Data Analytics
https://github.com/patrickzib/SFA
7 years ago by @becker
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fourier
of
bag
series
words
time
classification
fourierofbagserieswordstimeclassification
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11 Second - Internet Live Stats
http://www.internetlivestats.com/one-second/
7 years ago by @hotho
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one
real
second
time
wj2017
traffic
internet
onerealsecondtimewj2017trafficinternet
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110 Cool Sites for Seeing Worldwide Internet Activity in Real Time
https://www.lifewire.com/worldwide-internet-activity-in-real-time-3486148
7 years ago by @hotho
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size
data
real
time
wj2017
internet
sizedatarealtimewj2017internet
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1Taking Prophet for a Spin
http://blog.fastforwardlabs.com/2017/03/22/prophet.html
7 years ago by @becker
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prophet
bayes
series
forecasting
probabilistic
time
stan
google
programming
prophetbayesseriesforecastingprobabilistictimestangoogleprogramming
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1Foursquare check-ins show the pulse of cities
https://foursquare.com/infographics/pulse
8 years ago by @becker
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visualize
visualization
navigation
cities
nyc
manhattan
foursquare
citiy
time
diss
movement
visualizevisualizationnavigationcitiesnycmanhattanfoursquarecitiytimedissmovement
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3GitHub - patrickzib/SFA: Scalable Time Series Data Analytics
https://github.com/patrickzib/SFA
8 years ago by @hotho
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kallimachos
software
series
time
analysis
kallimachossoftwareseriestimeanalysis
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1Dual-Boot-System: Windows-Uhr läuft regelmäßig falsch - Articles - KittBlog
https://kittblog.com/article/3/windows/dual-boot-system-windows-uhr-laeuft-regelmaessig-falsch/675/dual-boot-system-windows-uhr-laeuft-regelmaessig-falsch/
8 years ago by @becker
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problem
dual
uefi
win10
clock
time
windows
10
boot
problemdualuefiwin10clocktimewindows10boot
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2GitHub - millecker/senti-storm: SentiStorm - Real-time Twitter Sentiment Classification based on Apache Storm
senti-storm - SentiStorm - Real-time Twitter Sentiment Classification based on Apache Storm
8 years ago by @hotho
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sentiment
storm
toread
twitter
real
time
sentistorm
classification
sentimentstormtoreadtwitterrealtimesentistormclassification
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1Time series extrinsic regression: Predicting numeric values from time series data
C. Tan, C. Bergmeir, F. Petitjean, and G. Webb. Data Mining and Knowledge Discovery, (2021)
9 months ago by @becker
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citedby:scholar:timestamp:2023-11-4
citedby:scholar:count:65
extrinsic
series
regression
time
citedby:scholar:timestamp:2023-11-4citedby:scholar:count:65extrinsicseriesregressiontime
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1Analysis of the time complexity of quick sort algorithm
W. Xiang. 2011 international conference on information management, innovation management and industrial engineering, 1, page 408--410. IEEE, (2011)
2 years ago by @becker
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sorting
complexity
citedby:scholar:timestamp:2022-9-23
citedby:scholar:count:31
sort
time
quicksort
algorithm
paper:fastcor
sortingcomplexitycitedby:scholar:timestamp:2022-9-23citedby:scholar:count:31sorttimequicksortalgorithmpaper:fastcor
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1Longitudinal variational autoencoder
S. Ramchandran, G. Tikhonov, K. Kujanpää, M. Koskinen, and H. Lähdesmäki. International Conference on Artificial Intelligence and Statistics, page 3898--3906. PMLR, (2021)
2 years ago by @becker
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variational
autoencoder
deep
data
citedby:scholar:count:6
learning
gain
citedby:scholar:timestamp:2022-5-13
timeseries
imputation
series
time
missing
model
net
temporal
nn
generative
longitudinal
variationalautoencoderdeepdatacitedby:scholar:count:6learninggaincitedby:scholar:timestamp:2022-5-13timeseriesimputationseriestimemissingmodelnettemporalnngenerativelongitudinal
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1Multitask learning and benchmarking with clinical time series data
H. Harutyunyan, H. Khachatrian, D. Kale, G. Ver Steeg, and A. Galstyan. Scientific data, 6 (1): 1--18 (2019)
3 years ago by @becker
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multitask
task
serial
clinical
paper:milkreview:selected
data
learning
time
multi
citedby:scholar:count:322
citedby:scholar:timestamp:2021-5-29
multitasktaskserialclinicalpaper:milkreview:selecteddatalearningtimemulticitedby:scholar:count:322citedby:scholar:timestamp:2021-5-29
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6Community structure in time-dependent, multiscale, and multiplex networks
P. Mucha, T. Richardson, K. Macon, M. Porter, and J. Onnela. science, 328 (5980): 876--878 (2010)
4 years ago by @becker
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project:bmbf
cluster
cordis
scale
dis
network
community
graph
multi
structure
clustering
funcdis
citedby:scholar:timestamp:2020-9-15
time
multiplex
dependent
multiscale
citedby:scholar:count:1565
project:bmbfclustercordisscaledisnetworkcommunitygraphmultistructureclusteringfuncdiscitedby:scholar:timestamp:2020-9-15timemultiplexdependentmultiscalecitedby:scholar:count:1565
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3Deep learning for time series classification: a review
H. Ismail Fawaz, G. Forestier, J. Weber, L. Idoumghar, and P. Muller. Data Mining and Knowledge Discovery, 33 (4): 917--963 (Jul 1, 2019)
4 years ago by @becker
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cnn
deep
neural
series
learning
time
networks
nn
classification
cnndeepneuralserieslearningtimenetworksnnclassification
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1Undulating changes in human plasma proteome profiles across the lifespan
B. Lehallier, D. Gate, N. Schaum, T. Nanasi, S. Lee, H. Yousef, P. Losada, D. Berdnik, A. Keller, J. Verghese and 1 other author(s). Nature Medicine, 25 (12): 1843--1850 (2019)
5 years ago by @becker
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nalab
lifespan
old
young
time
vs
proteome
longitudinal
plasma
age
nalablifespanoldyoungtimevsproteomelongitudinalplasmaage
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5Mass Cytometry and Topological Data Analysis Reveal Immune Parameters Associated with Complications after Allogeneic Stem Cell Transplantation
T. Lakshmikanth, A. Olin, Y. Chen, J. Mikes, E. Fredlund, M. Remberger, B. Omazic, and P. Brodin. Cell Reports, 20 (9): 2238 - 2250 (2017)
5 years ago by @becker
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cytometry
mass
nalab
immune
topology
network
cell
system
timeseries
transplantation
correlation
allogeneic
series
multiomics
time
stem
longitudinal
cytof
cytometrymassnalabimmunetopologynetworkcellsystemtimeseriestransplantationcorrelationallogeneicseriesmultiomicstimestemlongitudinalcytof
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2Detecting Change Points in the Large-Scale Structure of Evolving Networks
L. Peel, and A. Clauset. (2015)
5 years ago by @becker
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nalab
detection
cor
corr
network
graph
eveolving
evolve
point
timeseries
correlation
change
time
nalabdetectioncorcorrnetworkgrapheveolvingevolvepointtimeseriescorrelationchangetime
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3Gaussian Process Prior Variational Autoencoders
F. Casale, A. Dalca, L. Saglietti, J. Listgarten, and N. Fusi. Advances in Neural Information Processing Systems, page 10369--10380. (2018)
5 years ago by @becker
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autoencoder
comparison
auto
process
neural
encoder
network
nips
variation
prior
vae
time
model
gaussian
nn
generative
autoencodercomparisonautoprocessneuralencodernetworknipsvariationpriorvaetimemodelgaussiannngenerative
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1The Promise of Social Signal Processing for Research on Decision Making in Entrepreneurial Contexts
W. Liebregts, P. Darnihamedani, E. Postma, and M. Atzmueller. Small Business Economics. Special Issue on Big Data and Artificial Intelligence, ((In Press) 2019)
5 years ago by @atzmueller
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myown
making
decision
social
data
discovery
entrepreneurship
research
2019
signal
mining
computing
series
processing
time
human
myownmakingdecisionsocialdatadiscoveryentrepreneurshipresearch2019signalminingcomputingseriesprocessingtimehuman
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3Healing Time Correlates With the Quality of Scaring: Results From a Prospective Randomized Control Donor Site Trial
F. Werdin, M. Tenenhaus, M. Becker, and H. Rennekampff. Dermatologic Surgery, 44 (4): 521--527 (2018)
6 years ago by @becker
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myown
healing
statistical
scar
test
medicin
time
tissue
myownhealingstatisticalscartestmedicintimetissue
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8Improved recurrent neural networks for session-based recommendations
Y. Tan, X. Xu, and Y. Liu. Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, page 17--22. ACM, (2016)
6 years ago by @becker
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neural
citedby:scholar:count:44
session
time4all
time
recommender
citedby:scholar:timestamp:2018-3-14
network
nn
neuralcitedby:scholar:count:44sessiontime4alltimerecommendercitedby:scholar:timestamp:2018-3-14networknn
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14Session-based recommendations with recurrent neural networks
B. Hidasi, A. Karatzoglou, L. Baltrunas, and D. Tikk. arXiv preprint arXiv:1511.06939, (2015)
6 years ago by @becker
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dynamics
neural
session
time4all
recommendation
citedby:scholar:count:110
time
citedby:scholar:timestamp:2018-3-14
network
recurrent
nn
dynamicsneuralsessiontime4allrecommendationcitedby:scholar:count:110timecitedby:scholar:timestamp:2018-3-14networkrecurrentnn
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1Time-series clustering--A decade review
S. Aghabozorgi, A. Shirkhorshidi, and T. Wah. Information Systems, (2015)
6 years ago by @becker
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clustering
citedby:scholar:count:140
time4all
series
time
citedby:scholar:timestamp:2018-3-13
clusteringcitedby:scholar:count:140time4allseriestimecitedby:scholar:timestamp:2018-3-13
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4Bayesian nonparametric hidden semi-Markov models
M. Johnson, and A. Willsky. Journal of Machine Learning Research, 14 (Feb): 673--701 (2013)
6 years ago by @becker
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bayesian
time4all
citedby:scholar:count:182
hidden
nonparametric
non
bayes
series
unsupervised
parametric
semi
time
model
markov
citedby:scholar:timestamp:2018-3-13
bayesiantime4allcitedby:scholar:count:182hiddennonparametricnonbayesseriesunsupervisedparametricsemitimemodelmarkovcitedby:scholar:timestamp:2018-3-13
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2Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering
A. Karatzoglou, X. Amatriain, L. Baltrunas, and N. Oliver. Proceedings of the fourth ACM conference on Recommender systems, page 79--86. ACM, (2010)
6 years ago by @becker
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system
aware
citedby:scholar:count:502
time4all
context
time
recommender
citedby:scholar:timestamp:2018-3-13
systemawarecitedby:scholar:count:502time4allcontexttimerecommendercitedby:scholar:timestamp:2018-3-13
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2Context-aware recommender systems
G. Adomavicius, and A. Tuzhilin. Recommender systems handbook, Springer, (2015)
6 years ago by @becker
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system
citedby:scholar:count:1547
aware
time4all
context
time
recommender
citedby:scholar:timestamp:2018-3-13
systemcitedby:scholar:count:1547awaretime4allcontexttimerecommendercitedby:scholar:timestamp:2018-3-13
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4Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols
P. Campos, F. D\'ıez, and I. Cantador. User Modeling and User-Adapted Interaction, 24 (1-2): 67--119 (2014)
6 years ago by @becker
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based
system
time4all
citedby:scholar:count:192
dependant
time
recommender
citedby:scholar:timestamp:2018-3-13
basedsystemtime4allcitedby:scholar:count:192dependanttimerecommendercitedby:scholar:timestamp:2018-3-13
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2The BOSS is concerned with time series classification in the presence of noise
P. Schäfer. Data Mining and Knowledge Discovery, 29 (6): 1505--1530 (Nov 1, 2015)
7 years ago by @becker
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boss
fourier
of
bag
series
words
time
classification
bossfourierofbagserieswordstimeclassification
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