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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
profiling
profile
runtime
time
measurement
memorypythonprofilingprofileruntimetimemeasurement
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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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time
jupyter
timeit
magic
store
variable
result
python
lab
jupyterlab
timejupytertimeitmagicstorevariableresultpythonlabjupyterlab
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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
correlation
pearson
time
series
timeseries
spuriouscorrelationpearsontimeseriestimeseries
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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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adb
sync
android
phone
file
transfer
sdk
platform-tools
time
timestamp
timestamps
stamp
stamps
date
copy
rsync
adbsyncandroidphonefiletransfersdkplatform-toolstimetimestamptimestampsstampstampsdatecopyrsync
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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
time
information
theory
stanford
shen-orrtimeinformationtheorystanford
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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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time
human
immune
system
longitudinal
age
model
interpolation
shen-orr
stanford
timehumanimmunesystemlongitudinalagemodelinterpolationshen-orrstanford
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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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real
valued
time
series
multi
dim
dimensional
gan
recurrent
neural
network
conditional
realvaluedtimeseriesmultidimdimensionalganrecurrentneuralnetworkconditional
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1Mage: The Magical Time Series Backend Behind Parse.ly Analytics | Parse.ly
https://blog.parse.ly/post/1633/mage/
5 years ago by @becker
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mage
real
time
log
processing
kafka
hadoop
storm
apache
stack
s3
spark
parse.ly
python
python3
py
series
timeseries
dashboard
logs
magerealtimelogprocessingkafkahadoopstormapachestacks3sparkparse.lypythonpython3pyseriestimeseriesdashboardlogs
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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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time
series
timeseries
bayes
nonparametric
non
parametric
medical
medicin
mit
timeseriestimeseriesbayesnonparametricnonparametricmedicalmedicinmit
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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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trap
bash
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processes
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at
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same
time
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trapbashtwoprocesseskillatthesametimestartscript
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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)
6 months ago by @becker
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time
series
extrinsic
regression
citedby:scholar:count:65
citedby:scholar:timestamp:2023-11-4
timeseriesextrinsicregressioncitedby:scholar:count:65citedby:scholar:timestamp:2023-11-4
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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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paper:fastcor
quicksort
complexity
time
algorithm
sort
sorting
citedby:scholar:count:31
citedby:scholar:timestamp:2022-9-23
paper:fastcorquicksortcomplexitytimealgorithmsortsortingcitedby:scholar:count:31citedby:scholar:timestamp:2022-9-23
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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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imputation
gain
missing
data
generative
model
net
nn
deep
learning
autoencoder
variational
longitudinal
temporal
timeseries
time
series
citedby:scholar:count:6
citedby:scholar:timestamp:2022-5-13
imputationgainmissingdatagenerativemodelnetnndeeplearningautoencodervariationallongitudinaltemporaltimeseriestimeseriescitedby:scholar:count:6citedby:scholar:timestamp:2022-5-13
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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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paper:milkreview:selected
multi
task
learning
multitask
time
serial
clinical
data
citedby:scholar:count:322
citedby:scholar:timestamp:2021-5-29
paper:milkreview:selectedmultitasklearningmultitasktimeserialclinicaldatacitedby: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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citedby:scholar:count:1565
citedby:scholar:timestamp:2020-9-15
cluster
clustering
community
cordis
dependent
dis
funcdis
graph
multi
multiplex
multiscale
network
project:bmbf
scale
structure
time
citedby:scholar:count:1565citedby:scholar:timestamp:2020-9-15clusterclusteringcommunitycordisdependentdisfuncdisgraphmultimultiplexmultiscalenetworkproject:bmbfscalestructuretime
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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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classification
cnn
deep
learning
networks
neural
nn
series
time
classificationcnndeeplearningnetworksneuralnnseriestime
(0)
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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)
4 years ago by @becker
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age
lifespan
longitudinal
nalab
old
plasma
proteome
time
vs
young
agelifespanlongitudinalnalaboldplasmaproteometimevsyoung
(0)
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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)
4 years ago by @becker
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allogeneic
cell
correlation
cytof
cytometry
immune
longitudinal
mass
multiomics
nalab
network
series
stem
system
time
timeseries
topology
transplantation
allogeneiccellcorrelationcytofcytometryimmunelongitudinalmassmultiomicsnalabnetworkseriesstemsystemtimetimeseriestopologytransplantation
(0)
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2Detecting Change Points in the Large-Scale Structure of Evolving Networks
L. Peel, and A. Clauset. (2015)
4 years ago by @becker
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change
cor
corr
correlation
detection
eveolving
evolve
graph
nalab
network
point
time
timeseries
changecorcorrcorrelationdetectioneveolvingevolvegraphnalabnetworkpointtimetimeseries
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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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auto
autoencoder
comparison
encoder
gaussian
generative
model
network
neural
nips
nn
prior
process
time
vae
variation
autoautoencodercomparisonencodergaussiangenerativemodelnetworkneuralnipsnnpriorprocesstimevaevariation
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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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healing
medicin
myown
scar
statistical
test
time
tissue
healingmedicinmyownscarstatisticaltesttimetissue
(0)
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9Improved 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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time4all
neural
network
recommender
nn
time
session
citedby:scholar:count:44
citedby:scholar:timestamp:2018-3-14
time4allneuralnetworkrecommendernntimesessioncitedby:scholar:count:44citedby:scholar:timestamp:2018-3-14
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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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time4all
session
time
dynamics
recommendation
neural
network
nn
recurrent
citedby:scholar:count:110
citedby:scholar:timestamp:2018-3-14
time4allsessiontimedynamicsrecommendationneuralnetworknnrecurrentcitedby:scholar:count:110citedby:scholar:timestamp:2018-3-14
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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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time4all
clustering
time
series
citedby:scholar:count:140
citedby:scholar:timestamp:2018-3-13
time4allclusteringtimeseriescitedby:scholar:count:140citedby:scholar:timestamp:2018-3-13
(0)
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5Bayesian 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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bayes
bayesian
citedby:scholar:count:182
citedby:scholar:timestamp:2018-3-13
hidden
markov
model
non
nonparametric
parametric
semi
series
time
time4all
unsupervised
bayesbayesiancitedby:scholar:count:182citedby:scholar:timestamp:2018-3-13hiddenmarkovmodelnonnonparametricparametricsemiseriestimetime4allunsupervised
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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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time4all
context
aware
time
recommender
system
citedby:scholar:count:502
citedby:scholar:timestamp:2018-3-13
time4allcontextawaretimerecommendersystemcitedby:scholar:count:502citedby: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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time4all
context
aware
time
recommender
system
citedby:scholar:count:1547
citedby:scholar:timestamp:2018-3-13
time4allcontextawaretimerecommendersystemcitedby:scholar:count:1547citedby: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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time4all
time
based
dependant
recommender
system
citedby:scholar:count:192
citedby:scholar:timestamp:2018-3-13
time4alltimebaseddependantrecommendersystemcitedby:scholar:count:192citedby: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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bag
boss
classification
fourier
of
series
time
words
bagbossclassificationfourierofseriestimewords
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3Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs
O. Zaiane, M. Xin, and J. Han. Research and Technology Advances in Digital Libraries (ADL), page 19--29. IEEE, (1998)
7 years ago by @becker
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citedby:scholar:count:698
citedby:scholar:timestamp:2017-7-3
diss
inthesis
navigation
temporal
time
web
citedby:scholar:count:698citedby:scholar:timestamp:2017-7-3dissinthesisnavigationtemporaltimeweb
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1Profiling and Timing Code | Python Data Science Handbook

1python - How to store %%time values in a variable in Jupyter? - Stack Overflow

1How to use Pearson correlation correctly with time series - Cross Validated

1google/adb-sync

1TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach | BMC Bioinformatics | Full Text

1A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring | Nature Medicine

1ratschlab/RGAN: Recurrent (conditional) generative adversarial networks for generating real-valued time series data.

1Mage: The Magical Time Series Backend Behind Parse.ly Analytics | Parse.ly

1Li-wei H. Lehman - Google Scholar Citations

1Run multiple commands and kill them as one in bash - Unix & Linux Stack Exchange

publications (hide)40
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1Time series extrinsic regression: Predicting numeric values from time series data

1Analysis of the time complexity of quick sort algorithm

1Longitudinal variational autoencoder

1Multitask learning and benchmarking with clinical time series data

6Community structure in time-dependent, multiscale, and multiplex networks

3Deep learning for time series classification: a review

1Undulating changes in human plasma proteome profiles across the lifespan

5Mass Cytometry and Topological Data Analysis Reveal Immune Parameters Associated with Complications after Allogeneic Stem Cell Transplantation

2Detecting Change Points in the Large-Scale Structure of Evolving Networks

3Gaussian Process Prior Variational Autoencoders

3Healing Time Correlates With the Quality of Scaring: Results From a Prospective Randomized Control Donor Site Trial

9Improved recurrent neural networks for session-based recommendations

14Session-based recommendations with recurrent neural networks

1Time-series clustering--A decade review

5Bayesian nonparametric hidden semi-Markov models

2Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering

2Context-aware recommender systems

4Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols

2The BOSS is concerned with time series classification in the presence of noise

3Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs

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