Time Series Features @compTimeSeries
Tweets by @bendfulcher about time-series analysis. github.com/benfulcher/hct… Sydney, New South Wales Joined July 2015-
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New preprint!: "Using matrix-product states for time-series machine learning". arxiv.org/abs/2412.15826 Quick summary below 👇
Better believe it, there are now TWO #timeseries feature sets available in #julialang. The new CatchaMouse16.jl package joins Catch22.jl, bringing 16 more features tailored to (mouse) fMRI data: github.com/brendanjohnhar… Check out the CatchaMouse16 paper below
Better believe it, there are now TWO #timeseries feature sets available in #julialang. The new CatchaMouse16.jl package joins Catch22.jl, bringing 16 more features tailored to (mouse) fMRI data: github.com/brendanjohnhar… Check out the CatchaMouse16 paper below
A new method of detecting criticality from time-series data outperforms conventional metrics in the presence of variable noise levels for both simulated systems and real neural recordings. Read go.aps.org/3WBjcXf #PRXjustpublished #PRXopenaccess #PRXComplexSystems
Our work by @brendanjohnh (w Leo Gollo) on tracking the distance to criticality in noisy systems is now out in @PhysRevX 🙂 (includes an application tracking criticality across the mouse visual hierarchy) doi.org/10.1103/PhysRe… Code details: time-series-features.gitbook.io/time-series-an…
Our work by @brendanjohnh (w Leo Gollo) on tracking the distance to criticality in noisy systems is now out in @PhysRevX 🙂 (includes an application tracking criticality across the mouse visual hierarchy) doi.org/10.1103/PhysRe… Code details: time-series-features.gitbook.io/time-series-an…
New preprint by Rishi Maran @eli_j_muller "Analyzing the Brain's Dynamic Response to Targeted Stimulation using Generative Modeling" A review/perspective on why new mechanisms may be found by modeling brain stimulation dynamics 🧠⚡️ arxiv.org/abs/2407.19737 Quick summary 👇
New preprint by Rishi Maran @eli_j_muller "Analyzing the Brain's Dynamic Response to Targeted Stimulation using Generative Modeling" A review/perspective on why new mechanisms may be found by modeling brain stimulation dynamics 🧠⚡️ arxiv.org/abs/2407.19737 Quick summary 👇 https://t.co/58AQRQ3PLO
New preprint w/ Imran Alam, Patrick Cahill @Valerio_Zerbi @m_markicevic @brendanjohnh @olivercliff "Canonical time-series features for characterizing biologically informative dynamical patterns in fMRI" biorxiv.org/content/10.110… Code: github.com/DynamicsAndNeu… Short summary 👇
Latest preprint: "Parameter Inference from a Non-stationary Unknown Process" (PINUP) We're really interested in the problem of inferring sources of non-stationary variation directly from measured time-series data. arxiv.org/abs/2407.08987… Quick summary 👇
If you're at OHBM this year, check out @AnnieGBryant's great work developing a systematic method to extract interpretable dynamical patterns from fMRI time series!
If you're at OHBM this year, check out @AnnieGBryant's great work developing a systematic method to extract interpretable dynamical patterns from fMRI time series!
Curious about scientific papers that have used hctsa for time-series feature extraction? I maintain a log of this here, categorized across Biology, Cellular Neuroscience, Neuroimaging, Medicine, Pathology, Engineering, Geoscience: time-series-features.gitbook.io/hctsa-manual/i…
"Extensive MEG time-series phenotyping unveils neural markers predictive of age" Using the hctsa time-series feature set, finding age-predictive patterns of autocorrelation within the visual and temporal cortex. doi.org/10.1101/2024.0…
@misicbata @olivercliff @bendfulcher @compTimeSeries Amazing work using the great pyspi package! We also used it in our recent work and examined the sensitivity of (only) 20 representative FC metrics regarding neural decline induced by age and malignant brain tumors doi.org/10.1101/2024.0…!
Benchmarking methods for mapping functional connectivity in the brain | doi.org/10.1101/2024.0… What is the best FC metric? Led by @liuzhenqi0303 avec @loopyluppi @JustineYHansen @yetianmed @AndrewZalesky @bttyeo @bendfulcher ⤵️
catch22 documentation for efficient time-series feature extraction is now live on @GitBookIO, with docs for #RStats #Python #Julia and #Matlab and full descriptions of all time-series features time-series-features.gitbook.io/catch22
#Satellite ComplexTime explores temporal dynamics in complex systems across various domains. They invite submissions on topics related to temporal data handling, methods, and tools. Learn more at: sites.google.com/view/complexti…
Beyond oscillations - A novel feature space for characterizing brain states biorxiv.org/content/10.110…
bake off redux is online first, it reviews and compares recent algorithms for time series classification using the @aeon_toolkit for the vast majority of experiments link.springer.com/article/10.100…
New results now live! Most exciting is @brendanjohnh mouse #neuropixels application. We find that brain areas higher in the visual hierarchy are closer to #criticality (in a way that cannot be detected with existing #timeseries measures) 😄🐭⬇️ arxiv.org/abs/2310.14791
New results now live! Most exciting is @brendanjohnh mouse #neuropixels application. We find that brain areas higher in the visual hierarchy are closer to #criticality (in a way that cannot be detected with existing #timeseries measures) 😄🐭⬇️ arxiv.org/abs/2310.14791 https://t.co/3S8aizhnYA
Looking at training of a neural network as a (temporal) network trajectory, we can investigate the blackbox of machine learning training through dynamical systems and network theory. Great & fun collab w/ @kaloyandanovski & @miguelcsoriano preprint: arxiv.org/pdf/2404.05782…
New pre-print by @aria_mt_nguyen w @jlizier: "A feature-based information-theoretic approach for detecting interpretable, long-timescale pairwise interactions from time series" Introduces a new method: uses features to infer time-series interactions arxiv.org/abs/2404.05929
Reminder that I'll be running a second edition of my Ecological forecasting in R workshop in May this year. Learn to use #mgcv, #mvgam and #brms to analyse complex ecological time series and produce meaningful insights #rstats physalia-courses.org/courses-worksh…
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