| Active preference-based gaussian process regression for reward learning E Bıyık*, N Huynh*, MJ Kochenderfer, D Sadigh RSS 2020, 2020 | 113 | 2020 |
| Curated llm: Synergy of llms and data curation for tabular augmentation in ultra low-data regimes N Seedat*, N Huynh*, B van Breugel, M van der Schaar ICML 2024, 2023 | 23* | 2023 |
| Active preference-based Gaussian process regression for reward learning and optimization E Bıyık, N Huynh, MJ Kochenderfer, D Sadigh The International Journal of Robotics Research 43 (5), 665-684, 2024 | 15 | 2024 |
| GraphCite: citation intent classification in scientific publications via graph embeddings D Berrebbi*, N Huynh*, O Balalau Companion Proceedings of the Web Conference 2022, 779-783, 2022 | 11 | 2022 |
| Time series diffusion in the frequency domain J Crabbé*, N Huynh*, J Stanczuk, M van der Schaar ICML 2024, 2024 | 8 | 2024 |
| DAGnosis: Localized Identification of Data Inconsistencies using Structures N Huynh, J Berrevoets, N Seedat, J Crabbé, Z Qian, M van der Schaar AISTATS 2024, 2024 | 2 | 2024 |
| You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling N Seedat*, N Huynh*, F Imrie, M van der Schaar Journal of Data-centric Machine Learning Research (DMLR), 2024 | 1 | 2024 |
| Decision Tree Induction via Semantically-Aware Evolution T Liu*, N Huynh*, M van der Schaar The Thirteenth International Conference on Learning Representations, 0 | | |