The conda package distribution for Lightkurve - your gateway to analyzing stellar light curves from NASA's Kepler and TESS missions with beautiful Python tools for exoplanet discovery.

https://github.com/conda-forge/lightkurve-feedstock

#Exoplanets #TimeSeriesAnalysis #AstronomyTools

The impact of data quality and outlier detection in high-frequency water quality data on water management and process understanding Detecting outliers in environmental data is a common challenge in assessing river water quality using high-frequency monitoring. While the importance …

New publication by Nikolaus Weber et al: "The impact of data quality and #outlier detection in high-frequency #WaterQuality data on #WaterManagement and process understanding"

www.sciencedirect.com/science/arti...

#EnvironmentalMonitoring #DataScience #TimeSeriesAnalysis #DataValidation

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Learning time series analysis through CDR – PID Perspectives In January, I started attending police-led training on CDR analysis through the American Association of Crime Analysts. This topic is particularly fascinating for anyone with a background in working with telcos and their data, as records can contain all sorts of valuable information. Especially when it comes to solving crime through time series analysis. 

Time series analysis is an effective tool for cracking real-world crime cases. It's only one of the many techniques that we have explored during a police-led training5. Here's how we have added our spin using R.

#crimeAnalysis #timeSeriesAnalysis #CDR #callRecords

negativepid.blog/learning-tim...

Identification of periodicities with arbitrary shapes in AGN light curves
Fabio Rigamonti, Jessie Runnoe et al.
Paper
Details
#AGN #TimeSeriesAnalysis #LightCurves

APL Quest 2013-9: It Is a Moving Experience Write a function which produces n month moving averages for a year's worth of data.

#APLQuest 2013-09: Write a function that produces n month moving averages for a year's worth of data (see apl.quest/2013/9/ to test your solution and view ours). #APL #MovingAverage #TimeSeriesAnalysis

There is No "apple" in Timeseries: Rethinking TSFM through the Lens of
Invariance
Arian Prabowo, Flora D. Salim
Paper
Details
#TimeseriesAnalysis #InvariancePrinciples #TSFMRethinking

Toto: Time Series Optimized Transformer for Observability Table of Links Background Problem statement Model architecture Training data Results Conclusions Impact statement Future directions Contributions Acknowledgements and References Appendix 6 Conclusions...

Toto: Time Series Optimized Transformer for Observability #Technology #EmergingTechnologies #ArtificialIntelligence #TimeSeriesAnalysis #Observability

Use Origin's Time Series Pivot table to summarize time series data both column and row-wise to better analyze data and find patterns. The tool can be found under the Restructure menu and Statistics : Time Series menu.
#TimeSeriesAnalysis #statistics #DataAnalysis #scientificgraph #originpro2025b

Looking for #teamplayers with some* of these relevant prior experiences, & much curiosity to understand the neural principles behind how animals think and move. #Electrophysiology, #TimeSeriesAnalysis, #Behavior, #Biomechanics, #DynamicalSystems, #OpenData, #OpenCode practices 👀

https://machinelearningmastery.com/7-pandas-tricks-for-time-series-feature-engineering/

Enhancing time-series data for machine learning is crucial for effective models. #FeatureEngineering #TimeSeriesAnalysis machinelearningmastery.com/7-pandas-tricks-for-time...

Abnormal wind speed detection and prediction: methodology and case study <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d3979900e157">Accurate wind speed prediction is crucial for conserving power resources and enhancing power utilizati...

🆕🔓 on #ScienceOpen: 'Abnormal wind speed detection and prediction: methodology and case study' - a research paper published in 𝘐𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘵 𝘔𝘢𝘳𝘪𝘯𝘦 𝘛𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘢𝘯𝘥 𝘚𝘺𝘴𝘵𝘦𝘮𝘴 -

🖇️ #WindForecasting #AIForEnergy #RenewableEnergy #TimeSeriesAnalysis #MultifractalAnalysis

L-GTA: Latent Generative Modeling for Time Series Augmentation
Carlos Soares, Luis Roque et al.
Paper
Details
#LatentGenerativeModeling #TimeSeriesAnalysis #MachineLearningInnovation

How an Open Model and a Pile of Data are Changing Time Series Analysis Table of Links Abstract and 1. Introduction Related Work Methodology Experimental Setup and Results Conclusion and Future Work \ Acknowledgments Reproducibility statement Impact statement, and References...

How an Open Model and a Pile of Data are Changing Time Series Analysis #Technology #SoftwareandApps #OpenSource #TimeSeriesAnalysis #OpenModel #DataScience

mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and
Model Selection at Scale
Constantin Brif, Ismini Lourentzou et al.
Paper
Details
#mTSBench #TimeSeriesAnalysis #AnomalyDetection

Foundation models fail on the majority of real world (timeseries) datasets. Who knew?.. these guys -> arxiv.org/pdf/2502.12944

#BigData #TimeseriesAnalysis #DataAnalysis #DataEngineering

#TScourses #KeepLearning #GAMM #SpatialStatistics #MixedModels #TimeSeriesAnalysis #RStats #StatisticalModelling

Whether it’s Excel, AutoARIMA, or any other solution—it's the skill behind the tool that makes the difference.


#Forecasting #TimeSeriesAnalysis #DataScience #ARIMA #BoxJenkins #Analytics #ProfessionalSkills

Whether it’s Excel, AutoARIMA, or any other solution—it's the skill behind the tool that makes the difference.


#Forecasting #TimeSeriesAnalysis #DataScience #ARIMA #BoxJenkins #Analytics #ProfessionalSkills

We dive a bit into the reasons why current time series FMs not trained for DS reconstruction fail, and conclude that a DS perspective on time series forecasting & models may help to advance the #TimeSeriesAnalysis field.

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New ICPSR Summer Program Workshop "The Do's and Don'ts of Time Series Analysis," May 19-23, Online!

🚨Register Now!🚨

Learn about the problems that "memory" in time series pose to OLS models, how to choose the proper time series model for your research question, and how to run cutting-edge models and interpret the results easily and correctly. myumi.ch/AZzmG

#SumProg25 #ICPSR #TimeSeriesAnalysis

Time Data Series: It's Not About What You Said - It's More About How You Said It In my last post on PHP Zmanim, I said the next thing I’d write about was astronomy calculations. I still plan to do that, but something came up recently that caught my attention, so I’m going to...

Time Data Series: It's Not About What You Said - It's More About How You Said It #Technology #Other #DataScience #Communication #TimeSeriesAnalysis

EffConPy: Open Source Causality Discovery in Python

EffConPy is an open-source Python library designed to study time series beyond correlation and prediction. It provides many tools for causal discovery. #timeseriesanalysis

Eamonn Keogh on LinkedIn: #aics2024 #timeseries #anomalydetection #datamining I am looking forward to giving a keynote talk next Tuesday at the 32nd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2024), in my old…

Day 2 of the #AICSconference 2024 in #UCD has been filled with engaging discussions, particularly sparked by Eamonn Keogh's thought-provoking keynote on #TimeSeriesAnalysis.

www.linkedin.com/posts/eamonn...

#TimeSeriesAnalysis for #TemporalNetworks

Based on the abstract and inspection of figures, the impact of this work will be huge!

Long Memory in Time Series PhD Course – AAU-Math Department of Mathematical Sciences, Aalborg University

Today marked the last day of the PhD course in Long Memory in Time Series at Aalborg University. An excellent course by Prof. Dr. Uwe Hassler. math-at-aalborg-university.github.io/LM-PhD.html #TimeSeriesAnalysis #Econometrics #LongMemory

Neural ODEs Vs. RNNs Vs. LSTMs: Best For Sequential Data? Explore the differences between Neural ODEs, RNNs, and LSTMs, and learn when each model is best suited for sequential data analysis tasks.

Advances in deep learning have opened new pathways for handling sequential data, a cornerstone of applications in finance, healthcare, NLP, and beyond. #datamodeling #deeplearningmodels #LSTM #NeuralNetworks #NeuralODEs #RNN #SequentialData #timeseriesanalysis
aicompetence.org/neural-odes-...

Latest preprint: "Parameter Inference from a Non-stationary Unknown Process" (PINUP)
We unify a previously disjoint literature on algorithms for this important problem and introduce new benchmarking results.

arxiv.org/abs/2407.089...

#timeseriesanalysis #complexsystems

Brushing up on my #timeseriesanalysis skills. Any good datasets out there to practice with? #DataScience #TimeSeries #learning #Statistics

New NIOO publication: Temporal modelling of long-term heavy metal concentrations in #AquaticEcosystems. #timeseriesanalysis #artificialneuralnetwork #metalconcentration
https://doi.org/10.2166/hydro.2023.151