Open to all researchers, PGRs and anyone involved in Machine Learning at an N8 institution, this event will bring the Machine Learning community from across N8 together to find out more about N8 CIR, plans for the theme and all-important networking opportunities.
The event will have three key parts:
We are still working on finalising the agenda and details will be shared as soon as possible.
Bayesian Methods in Machine Learning
Machine learning in any area requires data, both for training prediction models and for applying them to solve real-world problems. Bayesian methods are known to be useful to make sense of data, to make better models and to interpret the predictions, especially in the presence of noise in either input data or inference data. With this N8 CIR event, we want to share current practices in using Bayesian methods across a wide range of disciplines and applications, so that this can provide cross-pollination and enrich our understanding of which methods might be applicable.
Submit your 300 word abstracts to firstname.lastname@example.org by the 30th of September. Successful presenters will be informed by mid-October.
Poster submissions are welcome on any aspect of Machine Learning, simply provide a poster title when you register.