Nicholas I-Hsien Kuo

Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models

Mar 22, 2023
Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri

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Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV

Aug 18, 2022
Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri

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* In the near future, we will make our codes and synthetic datasets publicly available to facilitate future research. Follow us on https://healthgym.ai/

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The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms

Mar 12, 2022
Nicholas I-Hsien Kuo, Mark N. Polizzotto, Simon Finfer, Federico Garcia, Anders Sönnerborg, Maurizio Zazzi, Michael Böhm, Louisa Jorm, Sebastiano Barbieri

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Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project

Dec 07, 2021
Nicholas I-Hsien Kuo, Mark Polizzotto, Simon Finfer, Louisa Jorm, Sebastiano Barbieri

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Learning to Continually Learn Rapidly from Few and Noisy Data

Mar 06, 2021
Nicholas I-Hsien Kuo, Mehrtash Harandi, Nicolas Fourrier, Christian Walder, Gabriela Ferraro, Hanna Suominen

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* Accepted to the Meta-Learning and Co-Hosted Competition of AAAI 2021. See https://aaai.org/Conferences/AAAI-21/ws21workshops/ and see https://sites.google.com/chalearn.org/metalearning?pli=1#h.kt23ep5wlehv

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MTL2L: A Context Aware Neural Optimiser

Jul 18, 2020
Nicholas I-Hsien Kuo, Mehrtash Harandi, Nicolas Fourrier, Christian Walder, Gabriela Ferraro, Hanna Suominen

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* Published in the ICML workshop of Automated Machine Learning (AutoML) 2020. Also see https://www.automl.org/wp-content/uploads/2020/07/AutoML_2020_paper_5.pdf

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