C. Lu MSc (Changqing) | Universiteit Twente

Engineering & Materials Science

# Sleep

Mathematics

# Infill Asymptotics
# Learning Process
# Logistic Regression
# Point Process
# Prediction
# Sleep
# Spatio-Temporal Process

Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Mathematics of Operations Research (MOR)

Lu, C., Guan, Y. , van Lieshout, M.-C., & Xu, G. (2024). XGBoostPP: Tree-based Estimation of Point Process Intensity Functions. ArXiv.org. https://doi.org/10.48550/arXiv.2401.17966

van Lieshout, M.-C. , & Lu, C. (2024). Contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning. Journal of the Royal Statistical Society. Series B: Statistical Methodology. Advance online publication. https://doi.org/10.1093/jrsssb/qkad150

Lu, C. , van Lieshout, M.-C. , de Graaf, M., & Visscher, P. (2023). Data-driven chimney fire risk prediction using machine learning and point process tools. Annals of applied statistics, 17(4), 3088-3111. https://doi.org/10.1214/23-AOAS1752

Lu, C. , Pathak, S. , Englebienne, G. , & Seifert, C. (2022). Channel Contribution In Deep Learning Based Automatic Sleep Scoring – How Many Channels Do We Need? IEEE transactions on neural systems and rehabilitation engineering, 31, 494-505. https://doi.org/10.1109/TNSRE.2022.3227040

van Lieshout, M.-C. , & Lu, C. (2022). Infill asymptotics for logistic regression estimators for spatio-temporal point processes. ArXiv.org. https://doi.org/10.48550/arXiv.2208.12080

Lu, C. , van Lieshout, M.-C. , de Graaf, M., & Visscher, P. (2021). Data-driven chimney fire risk prediction using machine learning and point process tools. ArXiv.org. https://doi.org/10.48550/arXiv.2112.07257

Lu, C. , van Lieshout, M.-C. , de Graaf, M., & Visscher, P. (2021). Chimney fire prediction based on environmental variables. 288-291. Paper presented at 63rd World Statistics Congress, ISI 2021, Virtual. https://www.isi-web.org/files/docs/papers-and-abstracts/86-day2-cps036-chimney-fire-prediction-based.pdf

Pathak, S. , Lu, C., Belur Nagaraj, S. , van Putten, M. J. A. M. , & Seifert, C. (2021). STQS: Interpretable multi-modal Spatial-Temporal-seQuential model for automatic Sleep scoring. Artificial intelligence in medicine, 114, Article 102038. https://doi.org/10.1016/j.artmed.2021.102038

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c.lu@utwente.nl

Bezoekadres

Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (gebouwnr. 11)
Hallenweg 19
7522NH Enschede

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Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
Postbus 217
7500 AE Enschede

Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Mathematics of Operations Research (MOR)

Universiteit Twente Drienerlolaan 5
7522 NB Enschede

+31 (0)53 489 9111
info@utwente.nl
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