{"id":2,"date":"2020-12-04T15:11:06","date_gmt":"2020-12-04T15:11:06","guid":{"rendered":"http:\/\/quentin-duchemin.alwaysdata.net\/wiki\/?page_id=2"},"modified":"2026-04-21T09:02:08","modified_gmt":"2026-04-21T09:02:08","slug":"research","status":"publish","type":"page","link":"https:\/\/quentin-duchemin.alwaysdata.net\/wiki\/index.php\/research\/","title":{"rendered":"Research"},"content":{"rendered":"\n

PhD dissertation<\/a>, Universit\u00e9 Gustave Eiffel. (Defended on June 20, 2022) Slides of the defense<\/a>.<\/p>\n\n\n\n

Publications<\/h4>\n\n\n\n

<\/a>A data-driven model to estimate time-variable catchment transit time distributions<\/a>, with Miazza, R.; Kirchner, J. W.; Benettin, P. Water Resources Research<\/strong>, 2026<\/p>\n\n\n\n

Data-Driven Estimation of the hydrologic response via Generalized Additive Models<\/a>, with Maria Grazia Zanoni, Marius G. Floriancic, Hansj\u00f6rg Seybold, Guillaume Obozinski, James W. Kirchner, and Paolo Benettin. Geoscientific Model Development<\/strong>, 2025

Rapid quantitative magnetization transfer imaging:Utilizing the hybrid state and the generalized Bloch model,<\/a> Magnetic Resonance in Medecine<\/strong>, 2023.

Reliable Time Prediction in the Markov Stochastic Block Model,<\/a> ESAIM: Probability & Statistics<\/strong>, <\/strong>2022. Python Notebook<\/strong><\/a><\/p>\n\n\n\n

The Random Geometric Graph: Recent developments and perspectives<\/a>, with Yohann De-Castro.  High Dimensional Probability volume 9<\/strong>, 2022<\/p>\n\n\n\n

M<\/a>arkov Random Geometric Graph (MRGG): A Growth Model for Temporal Dynamic Networks<\/a>,<\/a> with Yohann De-Castro. Electronic Journal of Statistics<\/strong>, 2022. Python Notebook<\/strong><\/a><\/p>\n\n\n\n

Concentration inequality for U-statistics of order two for uniformly ergodic Markov chains,<\/a> with Yohann De-Castro and Claire Lacour. Bernoulli, <\/strong>2022.<\/p>\n\n\n\n

Three rates of convergence or separation via U-statistics in a dependent framework<\/a>, with Yohann De-Castro and Claire Lacour. Journal of Machine Learning Research<\/strong>, 2022<\/p>\n\n\n\n

Cram\u00e9r-Rao bound-informed training of neural networks for quantitative MRI<\/a>, with Xiaoxia Zhang, Kangning Liu, Sebastian Flassbeck, Cem Gultekin, Carlos Fernadez-Granda and Jakob Assl\u00e4nder. Magnetic Resonance in Medicine<\/strong>, 2022<\/p>\n\n\n\n

Preprints<\/strong><\/h4>\n\n\n\n

Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts<\/a>, with Guillaume Obozinski. 2025

SIGLE: a valid procedure for Selective Inference with the Generalized Linear Lasso<\/a>, with Yohann De-Castro. 2026


<\/p>\n\n\n\n

Conference papers<\/strong><\/h4>\n\n\n\n

Rapid quantitative magnetization transfer imaging: utilizing the hybrid state and the generalized Bloch model<\/a>, J. Assl\u00e4nder, C. Gultekin, X. Zhang, Q. Duchemin, K. Liu, R. WE Charlson, T. Shepherd, C. Fernandez-Granda, and S. Flassbeck. Proc. 31th Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) 2022 (selected for oral presentation<\/em><\/strong>)<\/p>\n\n\n\n

Optimized dimensionality reduction for parameter estimation in MR fingerprinting via deep learning<\/a> Q. Duchemin, K. Liu, C. Fernandez-Granda, J. Asslaender. Proc. 28th Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) 2020 (selected for oral presentation<\/em><\/strong>)
Watch the video presenting our work<\/span><\/a> and read the slides of the presentation.<\/span><\/a><\/p>\n\n\n\n

Concentration inequality for U-statistics for uniformly ergodic Markov chains, and applications, Q.Duchemin, Y. De Castro & C. Lacour. Bernoulli-IMS 10th World Congress in Probability and Statistics 2021 (selected for oral presentation<\/em><\/strong>) Watch the video presenting our work<\/span><\/a>, read the slides of the presentation<\/span><\/a> and read our poster<\/a>.<\/span><\/p>\n\n\n\n

Awards<\/strong><\/h4>\n\n\n\n