Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking. - Ping Zhou 003; Heda Song; Hong Wang 001; Tianyou Chai (IEEE Trans. Control. Syst. Technol., 2017)

Graph Node-Feature Convolution for Representation Learning. - Li Zhang; Heda Song; Haiping Lu (CoRR, 2018)

A review on the self and dual interactions between machine learning and optimisation. - Heda Song; Isaac Triguero; Ender Özcan (Prog. Artif. Intell., 2019)

Few-Shot Learning for Postnatal Gestational Age Estimation. - Stepan Romanov; Heda Song; Michel F. Valstar; Don Sharkey; Caz Henry; Isaac Triguero; Mercedes Torres Torres (IJCNN, 2021)

L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout. - Heda Song; Mercedes Torres Torres; Ender Özcan; Isaac Triguero (Neurocomputing, 2021)

A fusion spatial attention approach for few-shot learning. - Heda Song; Bowen Deng; Michael P. Pound; Ender Özcan; Isaac Triguero (Inf. Fusion, 2022)

Node-Feature Convolution for Graph Convolutional Networks. - Li Zhang 131; Heda Song; Nikolaos Aletras; Haiping Lu (Pattern Recognit., 2022)

Novel meta-learning approaches for few-shot image classification. - Heda Song (2022)

The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond. - Direnc Pekaslan; Jose Maria Alonso-Moral; Kasun Bandara; Christoph Bergmeir; Juan Bernabé-Moreno; Robert Eigenmann; Nils Einecke; Selvi Ergen; Rakshitha Godahewa; Hansika Hewamalage; Jesus Lago; Steffen Limmer; et al. (CoRR, 2023)