Sheffield Machine Learning Network

A forum for those working in and with machine learning


Project maintained by SheffieldMLNet Hosted on GitHub Pages — Theme by mattgraham

About the network

The Machine Learning Research Network is a forum for ML researchers, based at the University of Sheffield.

Coordinated by the Machine Learning group in the Department of Computer Science, with support from the Statistics group in the School of Mathematics and Statistics, we host a series of activities and events.

These currently include a regular seminar series and a fortnightly journal club.

The aim of the network is to promote collaboration and to provide support for researchers and students who are working with or have interest in machine learning topics. We also promote the Open Data Science Initiative and the philosophy of resource sharing in the research community, particularly research software.

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Journal Club

Please email me if there are any interesting ML papers you’d like to chat about in a future meeting.

Below is the provisional schedule for the sessions and leaders:

Paper Title (link) Leader Time / Place Notes
Spatio-Temporal Statistics with R; Chapter 5: Dynamic Spatio-Temporal Models (link) Chris and Richard 21/04/22 28/04/22 19/05/22 4pm-5pm, Ada Lovelace Note it’s been moved back one two four weeks!
Collett, Thomas S., et al. “Coordinating compass-based and nest-based flight directions during bumblebee learning and return flights.” Journal of Experimental Biology 216.6 (2013): 1105-1113. (link) Mike Smith 07/04/22 4pm-5pm, Ada Lovelace  
Wilson, Andrew G., and Pavel Izmailov. “Bayesian deep learning and a probabilistic perspective of generalization.” Advances in neural information processing systems 33 (2020): 4697-4708. (link) Mike Smith 10/03/22 17/03/22 4pm-5pm, Ada Lovelace (delayed a week)
    24/02/22 (No JC this week as Wessel Bruinsma is visiting to speak about “Meta-Learning as Prediction Map Approximation”)
“Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm.”Advances in Neural Information Processing Systems 29 (2016) (link) Magnus Ross 10/02/22 4pm-5pm, Ada Lovelace  
A tutorial “PDE-constrained optimization and the adjoint method” (link) Chris Lanyon 25/11/21 4pm-5pm, Ada Lovelace  
“Bayesian computing with INLA: a review.” (second attempt!) (link) Mike Smith 11/11/21 4pm-5pm, Ada Lovelace We had a lot of questions and didn’t get to the end of the paper. Hopefully at this meeting we can work through the questions from last time.
“Bayesian computing with INLA: a review.” (link) Mike Smith 14/10/21 4pm-5pm, Ada Lovelace  

Seminars

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Who we are

Some of those involved, include: