Nicholas I-Hsien Kuo

According to our database, Nicholas I-Hsien Kuo authored at least 11 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Generating synthetic clinical data that capture class imbalanced distributions with generative adversarial networks: Example using antiretroviral therapy for HIV.

Nicholas I-Hsien Kuo, Federico Garcia, Anders Sönnerborg, Michael Böhm, Rolf Kaiser, Maurizio Zazzi, Mark N. Polizzotto, Louisa Jorm, Sebastiano Barbieri

J. Biomed. Informatics, August, 2023

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

Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri

CoRR, 2023

Rule-Based Natural Language Processing Pipeline to Detect Medication-Related Named Entities: Insights for Transfer Learning.

Zoie Shui-Yee Wong, Neil Waters, Nicholas I-Hsien Kuo, Jiaxing Liu

Proceedings of the MEDINFO 2023 - The Future Is Accessible, 2023

2022

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

Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri

CoRR, 2022

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

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

CoRR, 2022

2021

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

Nicholas I-Hsien Kuo, Mark N. Polizzotto, Simon Finfer, Louisa Jorm, Sebastiano Barbieri

CoRR, 2021

Plastic and Stable Gated Classifiers for Continual Learning.

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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Learning to Continually Learn Rapidly from Few and Noisy Data.

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

Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2020

MTL2L: A Context Aware Neural Optimiser.

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

CoRR, 2020

An Input Residual Connection for Simplifying Gated Recurrent Neural Networks.

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

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

M²SGD: Learning to Learn Important Weights.

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

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020