M2SGD: Learning to Learn Important Weights. - Nicholas I-Hsien Kuo; Mehrtash Harandi; Nicolas Fourrier; Christian Walder; Gabriela Ferraro; Hanna Suominen (CVPR Workshops, 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 (IJCNN, 2020)

MTL2L: A Context Aware Neural Optimiser. - Nicholas I-Hsien Kuo; Mehrtash Harandi; Nicolas Fourrier; Christian Walder; Gabriela Ferraro; Hanna Suominen (CoRR, 2020)

Learning to Continually Learn Rapidly from Few and Noisy Data. - Nicholas I-Hsien Kuo; Mehrtash Harandi; Nicolas Fourrier; Christian Walder; Gabriela Ferraro; Hanna Suominen (MetaDL@AAAI, 2021)

Plastic and Stable Gated Classifiers for Continual Learning. - Nicholas I-Hsien Kuo; Mehrtash Harandi; Nicolas Fourrier; Christian Walder; Gabriela Ferraro; Hanna Suominen (CVPR Workshops, 2021)

Dependency Learning Graph Neural Network for Multivariate Forecasting. - Arth Patel; Abishek Sriramulu; Christoph Bergmeir; Nicolas Fourrier (ICONIP (5), 2021)

Adaptive dependency learning graph neural networks. - Abishek Sriramulu; Nicolas Fourrier; Christoph Bergmeir (Inf. Sci., 2023)

Handwriting for Efficient Text Entry in Industrial VR Applications: Influence of Board Orientation and Sensory Feedback on Performance. - Nicolas Fourrier; Guillaume Moreau; Mustapha Benaouicha; Jean-Marie Normand (IEEE Trans. Vis. Comput. Graph., 2023)

DeepHGNN: Study of graph neural network based forecasting methods for hierarchically related multivariate time series. - Abishek Sriramulu; Nicolas Fourrier; Christoph Bergmeir (Expert Syst. Appl., 2025)