1 code implementation • 24 Jan 2022 • Tin Lok James Ng, Andrew Zammit-Mangion
Recent years have seen an increased interest in the application of methods and techniques commonly associated with machine learning and artificial intelligence to spatial statistics.
no code implementations • 29 Jun 2021 • Linyi Yang, Tin Lok James Ng, Barry Smyth, Ruihai Dong
The explosion in the sheer magnitude and complexity of financial news data in recent years makes it increasingly challenging for investment analysts to extract valuable insights and perform analysis.
no code implementations • 14 May 2021 • Weipeng Huang, Tin Lok James Ng, Nishma Laitonjam, Neil J. Hurley
Bayesian hierarchical mixture clustering (BHMC) improves traditionalBayesian hierarchical clustering by replacing conventional Gaussian-to-Gaussian kernels with a Hierarchical Dirichlet Process Mixture Model(HDPMM) for parent-to-child diffusion in the generative process.
no code implementations • COLING 2020 • Linyi Yang, Eoin M. Kenny, Tin Lok James Ng, Yi Yang, Barry Smyth, Ruihai Dong
Corporate mergers and acquisitions (M&A) account for billions of dollars of investment globally every year, and offer an interesting and challenging domain for artificial intelligence.
no code implementations • 6 Jun 2019 • Andrew Zammit-Mangion, Tin Lok James Ng, Quan Vu, Maurizio Filippone
Spatial processes with nonstationary and anisotropic covariance structure are often used when modelling, analysing and predicting complex environmental phenomena.