New Papers

Congratulations to those with new publications!:

Toyah Overton, Allan Tucker, Tim James and Dimitar Hristozov. dunXai: DO-U-Net for Explainable (Multi-Label) Image Classification, Intelligent Data Analysis Symposium 2022;

Ghoshal, B., Hikmet, F., Pineau, C., Tucker, A. and Lindskog, C. (2021) ‘DeepHistoClass: A novel strategy for confident classification of immunohistochemistry images using Deep Learning‘. Molecular & Cellular Proteomics, 0 (In Press). pp. 1 - 71. ISSN: 1535-9476

Barnaby E. Walker, Allan Tucker and Nicky Nicolson, Harnessing Large-Scale Herbarium Image Datasets Through Representation Learning, Front. Plant Sci., 13 January 2022 | https://doi.org/10.3389/fpls.2021.806407

New publications

Congratulations to Erfan Sajjadi and Ben Evans for their succesful submissions to the SOGOOD workship at ECML this year:

Erfan Sajjadi et al. Building Trajectories over Topology with TDA-PTS: An Application in Modelling Temporal Phenotypes of Disease

Ben Evans et al. Reasoning about Neural Network Activations: An Application in Spatial Animal Behaviour from Camera Trap Classifications

Other new publications from the group include:

Biraja Ghoshal & Allan Tucker, On Calibrated Model Uncertainty in Deep Learning, ECML Workshop on Uncertainty in Machine Learning

Juan de Benediti et al. Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks, SOGOOD, ECML 2020

Arianna Dagliati et al. Using Topological Data Analysis and Pseudo Time Series to Infer Temporal Phenotypes from Electronic Health Records, AI in Medicine Journal

Covid19 Update

The Group is on lockdown but work continues:

Seminars are continuing online

Some staff are volunteering their hardware and data analysis skills at Hillingdon hospital

A collaboration with the MHRA and CPRD will result in synthetic primary care data being made available for Covid19 research.

Biraja Ghoshal has been exploring his methods for identifying Covid19 from lung images: https://arxiv.org/abs/2003.10769