GAMME, a meta-model to unify data needs in simulation modeling (WIP). - Judicaël Bedouet; Nicolas Huynh; Romain Kervarc (SpringSim (TMS-DEVS), 2013)

Active Preference-Based Gaussian Process Regression for Reward Learning. - Erdem Biyik; Nicolas Huynh; Mykel J. Kochenderfer; Dorsa Sadigh (Robotics: Science and Systems, 2020)

GraphCite: Citation Intent Classification in Scientific Publications via Graph Embeddings. - Dan Berrebbi; Nicolas Huynh; Oana Balalau (WWW (Companion Volume), 2022)

Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in ultra low-data regimes. - Nabeel Seedat; Nicolas Huynh; Boris van Breugel; Mihaela van der Schaar (CoRR, 2023)

DAGnosis: Localized Identification of Data Inconsistencies using Structures. - Nicolas Huynh; Jeroen Berrevoets; Nabeel Seedat; Jonathan Crabbé; Zhaozhi Qian; Mihaela van der Schaar (AISTATS, 2024)

Time Series Diffusion in the Frequency Domain. - Jonathan Crabbé; Nicolas Huynh; Jan Stanczuk; Mihaela van der Schaar (ICML, 2024)

Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes. - Nabeel Seedat; Nicolas Huynh; Boris van Breugel; Mihaela van der Schaar (ICML, 2024)

You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling. - Nabeel Seedat; Nicolas Huynh; Fergus Imrie; Mihaela van der Schaar (CoRR, 2024)

Active preference-based Gaussian process regression for reward learning and optimization. - Erdem Biyik; Nicolas Huynh; Mykel J. Kochenderfer; Dorsa Sadigh (Int. J. Robotics Res., 2024)

Decision Tree Induction Through LLMs via Semantically-Aware Evolution. - Tennison Liu; Nicolas Huynh; Mihaela van der Schaar (ICLR, 2025)