2 citations · 3 across the 4 of their papers we have counts for
5 papers
Transformed Latent Variable Multi-Output Gaussian Processes
Xiaoyu Jiang, Xinxing Shi, Sokratia Georgaka +2
Multi-Output Gaussian Processes (MOGPs) provide a principled probabilistic framework for modelling correlated outputs but face scalability bottlenecks when applied to datasets with…
Multimodal Spatial Omics: From Data Acquisition to Computational Integration
Esra Busra Isik, Yusuf Hakan Usta, Haozhe Liu +5
Recent developments in spatial omics technologies have enabled the generation of high dimensional molecular data, such as transcriptomes, proteomes, and epigenomes, within their sp…
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference
Xiaoyu Jiang, Sokratia Georgaka, Magnus Rattray +1
The Multi-Output Gaussian Process is is a popular tool for modelling data from multiple sources. A typical choice to build a covariance function for a MOGP is the Linear Model of C…
A Hybrid Reduced Order Method for Modelling Turbulent Heat Transfer Problems
Sokratia Georgaka, Giovanni Stabile, Kelbij Star +2
A parametric, hybrid reduced order model approach based on the Proper Orthogonal Decomposition with both Galerkin projection and interpolation based on Radial Basis Functions metho…
Parametric POD-Galerkin Model Order Reduction for Unsteady-State Heat Transfer Problems
Sokratia Georgaka, Giovanni Stabile, Gianluigi Rozza +1
A parametric reduced order model based on proper orthogonal decomposition with Galerkin projection has been developed and applied for the modeling of heat transport in T-junction p…