Łukasz Kidziński
TitleCited byYear
Dynamic functional principal components
S Hörmann, Ł Kidziński, M Hallin
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2015
MOOC video interaction patterns: What do they tell us?
N Li, Ł Kidziński, P Jermann, P Dillenbourg
Design for teaching and learning in a networked world, 197-210, 2015
How do in-video interactions reflect perceived video difficulty?
N Li, L Kidzinski, P Jermann, P Dillenbourg
Proceedings of the European MOOCs Stakeholder Summit 2015, 112-121, 2015
Translating head motion into attention-towards processing of student’s body-language
M Raca, L Kidzinski, P Dillenbourg
Proceedings of the 8th international conference on educational data mining, 2015
Introduction to smart learning analytics: foundations and developments in video-based learning
MN Giannakos, DG Sampson, L Kidziński
A note on estimation in Hilbertian linear models
S Hörmann, Ł Kidziński
Scandinavian journal of statistics 42 (1), 43-62, 2015
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Ł Kidziński, SP Mohanty, CF Ong, Z Huang, S Zhou, A Pechenko, ...
The NIPS'17 Competition: Building Intelligent Systems, 121-153, 2018
Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data
LP Prieto, K Sharma, Ł Kidzinski, MJ Rodríguez‐Triana, P Dillenbourg
Journal of computer assisted learning 34 (2), 193-203, 2018
A tutorial on machine learning in educational science
Ł Kidziński, M Giannakos, DG Sampson, P Dillenbourg
State-of-the-Art and Future Directions of Smart Learning, 453-459, 2016
Learning to run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning
Ł Kidziński, SP Mohanty, CF Ong, JL Hicks, SF Carroll, S Levine, ...
The NIPS'17 Competition: Building Intelligent Systems, 101-120, 2018
How to quantify student’s regularity?
MS Boroujeni, K Sharma, Ł Kidziński, L Lucignano, P Dillenbourg
European Conference on Technology Enhanced Learning, 277-291, 2016
Semi-Markov Model for Simulating MOOC Students.
L Faucon, L Kidzinski, P Dillenbourg
International Educational Data Mining Society, 2016
Orchestration load indicators and patterns: In-the-wild studies using mobile eye-tracking
LP Prieto, K Sharma, Ł Kidzinski, P Dillenbourg
IEEE Transactions on Learning Technologies 11 (2), 216-229, 2017
Estimation in functional lagged regression
S Hörmann, Ł Kidziński, P Kokoszka
Journal of time series analysis 36 (4), 541-561, 2015
Semiautomatic annotation of mooc forum posts
W Liu, Ł Kidziński, P Dillenbourg
State-of-the-Art and Future Directions of Smart Learning, 399-408, 2016
Automatic real-time gait event detection in children using deep neural networks
Ł Kidziński, S Delp, M Schwartz
PloS one 14 (1), e0211466, 2019
Automated human-level diagnosis of dysgraphia using a consumer tablet
T Asselborn, T Gargot, Ł Kidziński, W Johal, D Cohen, C Jolly, ...
npj Digital Medicine 1 (1), 42, 2018
Longitudinal data analysis using matrix completion
Ł Kidziński, T Hastie
arXiv preprint arXiv:1809.08771, 2018
Gene expression profiling of low-grade endometrial stromal sarcoma indicates fusion protein-mediated activation of the Wnt signaling pathway
J Przybyl, L Kidzinski, T Hastie, M Debiec-Rychter, R Nusse, ...
Gynecologic oncology 149 (2), 388-393, 2018
Enhancing video-based learning experience through smart environments and analytics
MN Giannakos, DG Sampson, L Kidzinski, A Pardo
workshop on smart environments and analytics in video-based learning (SE@ VBL), 2016
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