Réda, Clémence, Tomas Rigaux, Hiba Bederina, Koh Takeuchi, Hisashi
Kashima, and Jill-Jênn Vie. 2026.
“Adaptive Quality-Diversity
Trade-Offs for Large-Scale Batch Recommendation.” https://openreview.net/forum?id=s6MBBiKsIP.
Vassoyan, Jean, Anan Schütt, Jill-Jênn Vie, Arun-Balajiee
Lekshmi-Narayanan, Elisabeth André, and Nicolas Vayatis. 2024.
“A
Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational
Documents.” https://inria.hal.science/hal-04779162.
Bergner, Yoav, Peter Halpin, and Jill-Jênn Vie. 2022.
“Multidimensional Item Response Theory in the Style of
Collaborative Filtering.” Psychometrika 87 (1): 266–88.
https://rdcu.be/cAcgu.
Brat, Gabriel A, Griffin M Weber, Nils Gehlenborg,
et al. 2020.
“International Electronic Health
Record-Derived COVID-19 Clinical Course Profiles: The 4CE
Consortium.” Npj Digital Medecine 3 (1): 109.
https://www.nature.com/articles/s41746-020-00308-0.
Kandemir, Erva, Jill-Jênn Vie, Adam Sanchez-Ayte, Olivier Palombi, and
Franck Ramus. 2025.
“Investigating the Influence of Training
Difficulty on the Learning Outcomes of Medical Students.”
Journal of Computer Assisted Learning, in press.
https://inria.hal.science/hal-05371759v1.
Khonsari, Roman Hossein, Mélodie Bernaux, Jill-Jênn Vie, et al. 2021.
“Risks of early mortality and pulmonary
complications following surgery in patients with
COVID-19.” British Journal of Surgery, February.
https://doi.org/10.1093/bjs/znab007.
Petria, Iulia, Samuel Albuquerque, Gael Varoquaux, et al. 2022.
“424-P: Body-Weight Variability and Risk of
Cardiovascular Outcomes in Type 1 Diabetes: Results from the DCCT/EDIC
Studies.” Diabetes 71
(Supplement_1).
https://hal.archives-ouvertes.fr/hal-03818459.
Réda, Clémence, Jill-Jênn Vie, and Olaf Wolkenhauer. 2024.
“Stanscofi and Benchscofi: A New Standard for Drug Repurposing by
Collaborative Filtering.” Journal of Open Source
Software 9 (93): 5973.
Réda, Clémence, Jill-Jênn Vie, and Olaf Wolkenhauer. 2025a.
“Comprehensive evaluation of pure and hybrid collaborative
filtering in drug repurposing.” Scientific
Reports 15 (2711): 2711.
https://doi.org/10.1038/s41598-025-85927-x.
Réda, Clémence, Jill-Jênn Vie, and Olaf Wolkenhauer. 2025b.
“Joint Embedding-Classifier Learning for Interpretable
Collaborative Filtering.” BMC
Bioinformatics 26 (1): 26.
https://doi.org/10.1186/s12859-024-06026-8.
Vie, Jill-Jênn, Fabrice Popineau, Éric Bruillard, and Yolaine Bourda.
2018a.
“Automated Test Assembly for Handling Learner Cold-Start in
Large-Scale Assessments.” International Journal of Artificial
Intelligence in Education, 1–16.
https://rdcu.be/G30H.
Vie, Jill-Jênn, Fabrice Popineau, Éric Bruillard, and Yolaine Bourda.
2018b.
“Utilisation de tests adaptatifs dans les MOOC dans un
cadre de crowdsourcing.” Revue STICEF, Volume 24, numéro 2, 2017, ahead of print.
https://doi.org/10.23709/sticef.24.2.6.
Yordanov, Youri, Aurélien Dinh, Alexandre
Bleibtreu, et al. 2021.
“Clinical Characteristics and
Factors Associated with Hospital Admission or Death in 43103 Adult
Outpatients with Coronavirus Disease 2019 Managed with the Covidom
Telesurveillance Solution: A Prospective Cohort Study.”
Clinical Microbiology and Infection 27 (8): 1158–66.
https://www.sciencedirect.com/science/article/pii/S1198743X21001932.
Belghiti, Ismael, Roger Mansuy, and Jill-Jênn Vie. 2016. Les clés pour
l’info : ENS et
agrégation (option D). Calvage et Mounet.
Dürr, Christoph, and Jill-Jênn Vie. 2016.
Programmation efficace:
Les 128 algorithmes qu’il faut avoir compris et codés dans
sa vie. Ellipses.
https://tryalgo.org.
Dürr, Christoph, and Jill-Jênn Vie. 2018.
高效算法:
竞赛、应试与提高必修128例. 人民邮电出版社.
https://book.douban.com/subject/30210075/.
Dürr, Christoph, and Jill-Jênn Vie. 2019.
培養與鍛鍊程式設計的邏輯腦:
程式設計大賽的128個進階技巧(使用Python). 博碩文化股份.
http://www.drmaster.com.tw/Bookinfo.asp?BookID=MP11906.
Dürr, Christoph, and Jill-Jênn Vie. 2020. Competitive Programming in
Python: 128 Algorithms to Develop Your Coding Skills. Cambridge
University Press.
Hsiao, I-Han Sharon, Shaghayegh Sherry Sahebi, François Bouchet, and
Jill-Jênn Vie, eds. 2021.
Proceedings of the
14th International Conference on Educational Data Mining.
https://hal.science/hal-03918191.
Popineau, Fabrice, Michal Valko, and Jill-Jênn Vie, eds. 2018.
Proceedings of the 1st International Workshop Eliciting Adaptive
Sequences for Learning (WeASeL). CEUR Workshop Proceedings 1. June
12, 2018, Montr
éal, Canada.
https://humanlearn.io/proceedings/vol-1/.
Vie, Jill-Jênn, Fabrice Popineau, Yolaine Bourda, and Éric Bruillard.
2017.
“A Review of Recent Advances in Adaptive Assessment.”
In
Learning Analytics: Fundaments, Applications, and Trends.
Springer.
https://hal.archives-ouvertes.fr/hal-01488284/document.
Abdalla, Michel, and Jill-Jênn Vie. 2012. “Leakage-Resilient
Spatial Encryption.” International Conference on Cryptology
and Information Security in Latin America, 78–99.
Agrawal, Anav, and Jill-Jênn Vie. 2025.
“AlgoAce: Retrieval-Augmented Generation for Assistance in
Competitive Programming.” Proceedings of 9th Educational Data Mining in Computer
Science Education Workshop (CSEDM 2025) (Palermo, Italy),
July.
https://hal.science/hal-05089333.
Choffin, Benoît, Fabrice Popineau, Yolaine Bourda, and Jill-Jênn Vie.
2019.
“DAS3H: Modeling Student Learning and
Forgetting for Optimally Scheduling Distributed Practice of
Skills.” Proceedings of the
Twelfth International Conference on Educational Data Mining (EDM
2019), 29–38.
https://arxiv.org/abs/1905.06873.
Girard, Samuel, Juan D. Pinto, Jill-Jênn Vie, and Amel Bouzeghoub. 2025.
“RegKT: Interpretable and Robust Deep Knowledge Tracing with
IRT-Regularizer.” The 2nd Human-Centric eXplainable AI in
Education (HEXED) Workshop at EDM (Educational Data Mining) 2025.
https://drive.google.com/file/d/12IMLMyo6cZif12YwxhekrHDI_RMIh04N/view.
Ibrahim, Carole, Hiba Bederina, Daniel Cuesta, Laurent Montier, Cyrille
Delabre, and Jill-Jênn Vie. 2025. “Diversified recommendations of cultural activities with
personalized determinantal point processes.” Proceedings of RecSoGood workshop at RecSys
2025 (Prague, Czech Republic), September, in press.
Kandemir, Erva Nihan, Jill-Jênn Vie, Adam Sanchez-Ayte, Olivier Palombi,
and Franck Ramus. 2024.
“Adaptation of the Multi-Concept
Multivariate Elo Rating System to Medical Students’ Training
Data.” Proceedings of the Fourteenth
International Conference on Learning Analytics and Knowledge (LAK
2024), in press.
https://arxiv.org/abs/2403.07908.
Kita, Naoyuki, Jill-Jênn Vie, Koh Takeuchi, and Hisashi Kashima. 2026.
“Robust Post-Hoc Score Allocation in Exams.” The 16th
International Learning Analytics & Knowledge Conference, Bergen,
Norway.
Minn, Sein, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima, and Feida Zhu.
2022.
“Interpretable Knowledge Tracing: Simple and Efficient
Student Modeling with Causal Relations.” Proceedings of the
AAAI Conference on Artificial Intelligence 36: 12810–18.
https://ojs.aaai.org/index.php/AAAI/article/view/21560.
Minn, Sein, Yi Yu, Michel Desmarais, Feida Zhu, and Jill-Jênn Vie. 2018.
“Deep Knowledge Tracing and Dynamic Student Classification for
Knowledge Tracing.” Proceedings of the 18th IEEE
International Conference on Data Mining, 1182–87.
https://arxiv.org/abs/1809.08713.
Vassoyan, Jean, Jill-Jênn Vie, and Pirmin Lemberger. 2023.
“Towards Scalable Adaptive Learning with Graph Neural Networks and
Reinforcement Learning.” In
Proceedings of the 16th
International Conference on Educational Data Mining, EDM
2023, Bengaluru, India, July 11-14, 2023, edited by Mingyu Feng,
Tanja Käser, Partha P. Talukdar, Rakesh Agrawal, Y. Narahari, and Mykola
Pechenizkiy. International Educational Data Mining Society.
https://arxiv.org/abs/2305.06398.
Vie, Jill-Jênn, and Hisashi Kashima. 2019.
“Knowledge Tracing Machines: Factorization Machines for
Knowledge Tracing.” Proceedings of the 33th
AAAI Conference on Artificial Intelligence, 750–57.
https://arxiv.org/abs/1811.03388.
Vie, Jill-Jênn, and Hisashi Kashima. 2023.
“Deep Knowledge Tracing
Is an Implicit Dynamic Multidimensional Item Response Theory
Model.” Proceedings of the 31st International Conference on
Computers in Education, in press.
https://inria.hal.science/hal-04180391.
Vie, Jill-Jênn, Fabrice Popineau, Yolaine Bourda, and Éric Bruillard.
2016. “Adaptive Testing Using a General Diagnostic Model.”
European Conference on Technology Enhanced Learning, 331–39.
Vie, Jill-Jênn, Tomas Rigaux, and Hisashi Kashima. 2022.
“Variational Factorization Machines for Preference Elicitation in
Large-Scale Recommender Systems.” 2022 IEEE International
Conference on Big Data (Big Data) (Los Alamitos, CA, USA),
December, 5607–14.
https://ieeexplore.ieee.org/document/10020448.
Vie*, Jill-Jênn, Tomas Rigaux*, and Sein Minn. 2022.
“Privacy-Preserving Synthetic Educational Data Generation.”
Proceedings of EC-TEL 2022. Educating for a New Future: Making Sense
of Technology-Enhanced Learning Adoption, 393–406.
https://hal.archives-ouvertes.fr/hal-03715416.
Choffin, Benoît, Fabrice Popineau, Yolaine Bourda, and Jill-Jênn Vie.
2021.
“Evaluating DAS3H on the EdNet
Dataset.” AAAI 2021 - The 35th
Conference on Artificial Intelligence / Imagining Post-COVID Education
with AI (Virtual, United States), February.
https://hal.archives-ouvertes.fr/hal-03175874.
Vie, Jill-Jênn. 2018.
“Deep Factorization
Machines for Knowledge Tracing.” Proceedings of the Thirteenth Workshop on Innovative Use
of NLP for Building Educational Applications, 370–73.
https://arxiv.org/abs/1805.00356.
Vie, Jill-Jênn, Fabrice Popineau, Jean-Bastien Grill, Éric Bruillard,
and Yolaine Bourda. 2015a. “Predicting Performance over
Dichotomous Questions: Comparing Models for Large-Scale Adaptive
Testing.” 8th International Conference on Educational Data
Mining.
Vie, Jill-Jênn, Fabrice Popineau, Jean-Bastien Grill, Éric Bruillard,
and Yolaine Bourda. 2015b. “Prédiction de performance
sur des questions dichotomiques : comparaison de modèles
pour des tests adaptatifs à grande
échelle.” Atelier Évaluation des
Apprentissages et Environnements Informatiques.
Vie, Jill-Jênn, Fabrice Popineau, Françoise Tort, Benjamin Marteau, and
Nathalie Denos. 2017.
“A Heuristic Method for Large-Scale
Cognitive-Diagnostic Computerized Adaptive Testing.”
Proceedings of the Fourth (2017) ACM Conference on Learning @
Scale, 323–26.
https://github.com/jilljenn/las2017-wip/.
Vie, Jill-Jênn, Florian Yger, Ryan Lahfa, et al. 2017.
“Using Posters to Recommend Anime and Mangas in a
Cold-Start Scenario.” 2017 14th
IAPR International Conference on Document Analysis and Recognition
(ICDAR) – Second International Workshop on Comics Analysis, Processing
and Understanding 03 (November): 21–26.
https://arxiv.org/abs/1709.01584.
Vie, Jill-Jênn. 2009.
“Un Algorithme de Composition
Musicale.” Quadrature, no. 72: 10–14.
https://jill-jenn.net/_static/works/un-algorithme-de-composition-musicale.pdf.
Vie, Jill-Jênn. 2014a. “Grolopin Et Les Plans Projectifs
Finis.” Tangente Hors-Série, no. 52:
128–31.
Vie, Jill-Jênn. 2014b. “Langages Rationnels Et Automates
Finis.” Bibliothèque Tangente, no. 52:
52–55.
Vie, Jill-Jênn. 2018.
“Comment Coder Un Système de
Recommandation En Python : L’exemple de Mangaki.” GNU/Linux
Magazine Hors-Série, no. 94.
https://mangaki.fr/static/mangaki-linuxmag.pdf.
Vie, Jill-Jênn, Alexandre Talon, and Arthur Charguéraud. 2014.
“Les Concours Informatiques Destinés Aux
Jeunes.” Tangente Hors-Série, no. 52: 22.