Powered by OpenAIRE graph
Found an issue? Give us feedback

Healthsolve

Country: United Kingdom
2 Projects, page 1 of 1
  • Funder: UK Research and Innovation Project Code: EP/K009788/1
    Funder Contribution: 104,530 GBP

    The aim of this network is to establish the UK as the world leading authority in the joint area of Computational Statistics and Machine Learning (CompStat & ML) by advancing communication, interchange and collaboration within the UK between the disciplines of Computational Statistics (CompStat) and Machine Learning (ML). The UK has tremendous research strength and depth that is widely acknowledged as world leading in both the individual areas of Computational Statistics and Machine Learning. Despite each of these fields of research developing, largely, independently and having their own separate journals, international societies, conferences and curricula both areas of investigation share a common theoretical foundation based on the underlying formal principles of mathematical statistics and statistical inference. As such there is a natural diffusion of concepts, research and individuals between both disciplines. This network will seek to formalise as well as enhance this interchange and in the process capitalise on important synergies that will emerge from the combined and shared research agendas of CompStat & ML.

    more_vert
  • Funder: UK Research and Innovation Project Code: EP/K009788/2
    Funder Contribution: 93,194 GBP

    The aim of this network is to establish the UK as the world leading authority in the joint area of Computational Statistics and Machine Learning (CompStat & ML) by advancing communication, interchange and collaboration within the UK between the disciplines of Computational Statistics (CompStat) and Machine Learning (ML). The UK has tremendous research strength and depth that is widely acknowledged as world leading in both the individual areas of Computational Statistics and Machine Learning. Despite each of these fields of research developing, largely, independently and having their own separate journals, international societies, conferences and curricula both areas of investigation share a common theoretical foundation based on the underlying formal principles of mathematical statistics and statistical inference. As such there is a natural diffusion of concepts, research and individuals between both disciplines. This network will seek to formalise as well as enhance this interchange and in the process capitalise on important synergies that will emerge from the combined and shared research agendas of CompStat & ML.

    more_vert

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.

Content report
No reports available
Funder report
No option selected
arrow_drop_down

Do you wish to download a CSV file? Note that this process may take a while.

There was an error in csv downloading. Please try again later.