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:

IDA Seminar (Virtual) 15th April 2020

IDA seminars will continue in spite of the UK lockdown. Last week’s was held successfully with three talks from successful IDA 2020 submissions.

IDA 2020 going online

Due to the ongoing Corona virus restrictions IDA 2020 will be held as a virtual conference online on the original dates. As a result it will be free to all! More information will be posted here nearer the time: IDA2020

IDA 2020 Success

Congratulations to Toyah Overton & Biraja Ghoshal for their papers accepted to IDA 2020 this year:

Biraja Ghoshal, Cecilia Lindskog, Allan Tucker, “Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics”

Toyah Overton, Allan Tucker, “DO-U-Net for Segmentation and Counting”

Yani Xue, Miqing Li, Xiaohui Liu, “Angle-based Crowding Degree Estimation for Many-Objective Optimization”