NITheCS & SU Seminar: ‘Tree-based Imputations in the Presence of Right-Censored Data for Machine Learning Applications’ – James Grove (SU)
📅 Fri, 13 March 2026
🕐 13h10 SAST
📍 Attend in person or online
buff.ly/DwJ3ZqT
#MachineLearning #StatisticalLearning #SurvivalAnalysis #DataImputation

🤔 Haven't you submitted your individual paper to #StatLearnBCBL yet?

The conference will discuss #statisticallearning and its underlying mechanisms from behaviour to #neuroscience.

✍🏼 Submission deadline: 01/03/2026

+info ⬇️

www.bcbl.eu/events/stati...

Hello E-DLD followers! Today's research study aimed to understand whether children with DLD show impairments in Statistical Learning

Article summary: www.engage-dld.com/post/statist...
Original article: doi.org/10.3389/fnhu...

#DevLangDis #DLD #StatisticalLearning #OnlineTesting #OfflineTesting

EEG insights into predictive coding of temporal regularity in shape sequences The human brain extracts statistical regularities from sensory input as a foundational mechanism for anticipating future events. This process, known a…

New paper “EEG insights into predictive coding of temporal regularity in shape sequences” now published in Biological Psychology. Open access: www.sciencedirect.com/science/arti...
#predictivecoding #statisticallearning #ERP

Autistic traits relate to speed/accuracy trade-off but not statistical learning and updating - Scientific Reports Scientific Reports - Autistic traits relate to speed/accuracy trade-off but not statistical learning and updating

Excited to share our latest paper! We show that autistic traits are associated with a different speed-accuracy strategy when the environment changes. This highlights the power of a dimensional approach over rigid categorical views.
doi.org/10.1038/s415...
#Autism #Learning #StatisticalLearning

It’s the future of forecasting. 💥
#TimeSeries #Forecasting #MLOps #DataScience #AI #DeepLearning #ModelEvaluation #NewRelease #Python #StatisticalLearning #ForecastStability #DriftDetection #AIProductivity

It’s the future of forecasting. 💥
#TimeSeries #Forecasting #MLOps #DataScience #AI #DeepLearning #ModelEvaluation #NewRelease #Python #StatisticalLearning #ForecastStability #DriftDetection #AIProductivity

It’s the future of forecasting. 💥
#TimeSeries #Forecasting #MLOps #DataScience #AI #DeepLearning #ModelEvaluation #NewRelease #Python #StatisticalLearning #ForecastStability #DriftDetection #AIProductivity

It’s the future of forecasting. 💥
#TimeSeries #Forecasting #MLOps #DataScience #AI #DeepLearning #ModelEvaluation #NewRelease #Python #StatisticalLearning #ForecastStability #DriftDetection #AIProductivity

Advanced Conformal Prediction: Reliable Uncertainty Quantification for Real-World Machine Learning (Preorder / Early Access) 🚀 Advanced Conformal Prediction: Practical Uncertainty Quantification for Real-World ML 🚀Preorder / Early Access – Chapters released progressivelyFull book priced at over $80+ USD.Are you ready to take your machine learning models to the next level? Move beyond basic predictions and master advanced techniques for quantifying and managing uncertainty with confidence.In "Advanced Conformal Prediction," you'll dive deep into sophisticated methods designed to enhance reliability and decision-making in real-world AI applications. This comprehensive guide equips you with practical skills and cutting-edge tools, empowering you to confidently deploy machine learning solutions in high-stakes environments.Whether you're a data scientist, engineer, researcher, or practitioner, this book will become your essential resource for ensuring the trustworthiness of your AI models.📖 What's Inside: Advanced methods for uncertainty quantification Practical insights for real-world AI deployment Techniques for improving model reliability Join the journey and transform your approach to AI uncertainty today!🌟 Perfect for: Data Scientists and ML Engineers AI Researchers Professionals deploying ML in critical industries Secure your copy now and revolutionize how you manage uncertainty in machine learning!

valeman.gumroad.com/...

#MachineLearning #ConformalPrediction #Quantification #STEM #AdvancedML #StatisticalLearning #BeyondSplitConformal #LearnLikeAPro

It’s the future of forecasting. 💥
#TimeSeries #Forecasting #MLOps #DataScience #AI #DeepLearning #ModelEvaluation #NewRelease #Python #StatisticalLearning #ForecastStability #DriftDetection #AIProductivity

A functional trade-off between executive control and implicit statistical learning is dynamically gated by mind wandering Human cognition must balance goal-directed behavior with the need to learn from environmental regularities. Mind wandering (MW), a state of attentional decoupling from the task at hand, is paradoxical...

Our new preprint: Mind wandering is a cognitive trade-off.
Our study shows MW impairs executive control but BOOSTS implicit learning of hidden patterns. We found that the weaker the control, the greater the learning gain.
doi.org/10.1101/2025...
#statisticallearning
#sleeppeeps #psychscisky

Only 1 week until #JSM2025!

Visit AthlyticZ at Booth 405 to see how we’re making data science training real, practical, and career-ready—with Python, R, Bayesian stats, Shiny, and more.

Let’s talk #StatisticalLearning, #AnalyticsEducation, and #STEMCareers in Nashville!

These publications showcase Warwick Statistics' commitment to pushing the boundaries of statistical machine learning and AI methodology. Interested in our research? Connect with our department to explore potential collaborations!
#WarwickStats #AIResearch #StatisticalLearning #ReinforcementLearning

Marlene Meyer & @robertoostenveld.bsky.social just received an NWO grant for studying how statistical learning in infants shapes language and social skills 👶 🧠. Congrats, Marlene & Robert!

#grant #nwo #babybrain #statisticallearning

Multiresolution Analysis and Statistical Thresholding on Dynamic Networks Detecting structural change in dynamic network data has wide-ranging applications. Existing approaches typically divide the data into time bins, extract network features within each bin, and then comp...

📄 Preprint available:
 arxiv.org/abs/2506.01208

Joint work with @tijldebie.bsky.social @nickheard @alexandermodell
#TemporalNetworks #DynamicGraphs #NetworkScience #ChangeDetection #Cybersecurity #SignalProcessing #Wavelets #StatisticalLearning #TimeSeries #GraphML

Multiresolution Analysis and Statistical Thresholding on Dynamic Networks Detecting structural change in dynamic network data has wide-ranging applications. Existing approaches typically divide the data into time bins, extract network features within each bin, and then comp...

📄 Full preprint available:
arxiv.org/abs/2506.01208

Joint work with @tijldebie.bsky.social @alexandermodell @nickheard
#TemporalNetworks #DynamicGraphs #NetworkScience #ChangeDetection #Cybersecurity #SignalProcessing #Wavelets #StatisticalLearning #TimeSeries #GraphML

Multiresolution Analysis and Statistical Thresholding on Dynamic Networks Detecting structural change in dynamic network data has wide-ranging applications. Existing approaches typically divide the data into time bins, extract network features within each bin, and then comp...

📄 Link to the full preprint:
arxiv.org/abs/2506.01208

Joint work with @tijldebie.bsky.social @alexandermodell @nickheard
#TemporalNetworks #DynamicGraphs #NetworkScience #ChangeDetection #Cybersecurity #SignalProcessing #Wavelets #StatisticalLearning #TimeSeries #GraphML

A Wandering Mind Improves Inferential Learning Leverage the power of the spontaneously wandering mind to enhance learning, problem-solving, and creativity.

Our recent study on mind wandering and local sleep has received additional media coverage.
www.psychologytoday.com/us/blog/expe...

#predictiveprocessing #Neuroscience #statisticallearning #cognition

Excited to be opening for this symposium on developmental dynamics between cognitive control and statistical learning today! @nemeth.bsky.social, Rachel Foster, and Qianqian Wang.

Time: 10:00 AM - 11:30 AM

203AB | Minneapolis Convention Center, Level Two
#SRCD2025 #statisticallearning #ef

Excited to be opening for this symposium today with @nemeth.bsky.social, Rachel Foster, and Qianqian Wang.

Join us today at 10:00AM in Room 203AB

#SRCD #statisticallearning #cognitivecontrol

Bertold Mariën talks with Maria Eriksson in IceLab

Global vegetation models that predict forest growth and carbon storage should consider the clock to improve predictions of how forests will respond to climate change, according to Bertold Mariën. #SystemsBiology #StatisticalLearning

Mind wandering during implicit learning is associated with increased periodic EEG activity and improved extraction of hidden probabilistic patterns Mind wandering, occupying 30-50% of our waking time, remains an enigmatic phenomenon in cognitive neuroscience. A large number of studies showed a negative association between mind wandering and atten...

Our paper is out! We found that when the human brain builds predictive representations implicitly, mind wandering can support the process—linked to slow and delta-range oscillations.
#statisticallearning
#neuroscience
#learning
#PsychSciSky
#neuroskyence

www.jneurosci.org/content/earl...

Our new MEG preprint on Building&Updating Predictive Models in auditory sequences 🧠🔊
✅ auditory-frontal areas & #hippocampus drive adaptive perception

with Maria Chait, M Pearce, K Magami @UCL
#Neuroscience #PredictiveProcessing #StatisticalLearning #BrainResearch #AuditoryPerception #musicscience

#statisticallearning #patterntracking #bilingualism #multilingualism #bilingualismmatters #multilingualismmatters #duolingouser #duolingousers

"These findings clearly show that the learning via exposure is slow and does not guarantee successful learning of regularities in written languages, especially when there is more than one pattern in the input."

#statisticallearning #language #literacy

osf.io/preprints/os...

✨Playback of #teap2025 (Part 2)

A thought-provoking symposium on #StatisticalLearning & its role in #language & #reading, chaired by @troembke.bsky.social & @xeniaschmalz.bsky.social. Great contributions by @mireiamarimon.bsky.social, Haoyu Zhou, Lukas Hauser & @matildellen.bsky.social!

Proud PI! 👏 On #TeaP2025 two lab members presented their work:

Haoyu Zhou in the symposium #StatisticalLearning and its Role in #Language and #Reading acquisition.

@boevesam.bsky.social in the symposium From Babies to Semantics: Leveraging #LanguageModels for #Psycholinguistic Research.

Looking forward to seeing you at our symposium on #StatisticalLearning & #language & #reading at #teap2025!

For the first time, I (a long-term cynic about the literature about statistical learning/reading/dyslexia) will present something that hints at an effect of #statisticallearning on #reading!