Few-Shot Learning for Argument Aspects of the Nuclear Energy Debate. In Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, and Stelios Piperidis (Eds.), 2022 Language Resources and Evaluation Conference, LREC 2022, 663--672, European Language Resources Association (ELRA), 2022. [PUMA: FIS_scads argument aspect-based aspects, classification discourse, energy few-shot frames, learning, mining, nuclear text xack]
A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data. Scientific reports, (14)1Nature Publishing Group, Jan 27, 2024. [PUMA: Databases, Electronic FIS_scads Factual, Health Humans, Informatics, Learning, Machine Medical Records topic_lifescience yaff]
Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, (3):1252--1259, European Society for Composite Materials (ESCM), Jul 2, 2024. [PUMA: Convolutional Direct FIS_scads Fiber Machine Strain area_architectures dependency, identification, learning, networks, neural parameter plastics rate reinforced topic_engineering yaff] URL