Projects supervised by Iain Murray
This page lists project dissertations authored by students who worked with my supervision for part of their undergraduate or master’s degree programme.
- Font Style Transfer using Deep Learning, UG5 project 2018.
- Recurrent Neural Networks for Dasher, UG4 project 2018.
- Benchmarking Differentiable Neural Computers, UG4 project 2018.
- In 2018 I collaborated with MSc supervisors from Amazon Development Centre Scotland, who took on 20 students, rather than supervising projects directly myself.
- A Model for predicting the Outcomes of Professional Tennis Matches, MSc 2017.
- Differentiating linear algebra routines, MSc 2017.
- Fast inference for Cosmology, MSc 2017.
- Probabilistic modelling for inventory forecasting, MSc 2017.
- When and why do differentiable deep learning systems lose to random forests?, MSc 2017.
- Differentiating Gaussian process models, MSc 2017.
- A Synthetic Data Generating Approach and Synthetic Data Mechanisms for Regularization, MSc 2017.
- What is the capacity of printed paper?, UG4 2016.
- Machine learning of fonts, UG4 2016.
- (I took a six-month sabbatical in Spring/Summer 2016.)
- Distilling Model Knowledge, George Papamakarios, MSc 2015.
- Approximate inference for large-scale probabilistic ranking, Qi Hu, MSc 2015.
- Implementing a training procedure for Mixture Density Network with full covariance components, Longfei Xu, MSc 2015.
- Machine Learning Approaches to Automatic Validation of Fibre Placement in Carbon Fibre Composite Manufacturing, Alessandro Di Martino, MSc 2015. (Supervised by Korin Richmond; I was a second supervisor.)
- Machine learning and inferring cosmological parameters, Denitsa Saynova, 2015.
- Spotting presentation slides in video, Jason Xie, UG4 project, 2015.
- Machine learning and inferring cosmological parameters, Curtis Holmes, MSc 2014.
- Machine learning of multivariate probabilities, Theo Varvadoukas, MSc 2014.
- Realtime Recommendation System for Online Games, Tautvydas Misiunas, MSc 2014.
- Comparison of Markov chain Monte Carlo methods for Gaussian Processes, Fei Yang, MSc 2014.
- Machine learning of dependencies in high density neural recordings, Pol Moreno Comellas, MSc 2013.
- Measuring pulse rate with a webcam, Abel Gonzalez Garcia, MSc 2013.
- Better approximate inference for probabilistic ranking, Pim Heesterbeek, MSc 2013.
- Automatic evaluation of photographic images, Jason Ebbin, UG4 project, 2013.
- Unshredding, Razvan Ranca, UG4 project, 2013.
International Winner, Undergraduate Awards 2013, Computer Science.
- DOG removal — Inpainting Digital Onscreen Graphics, Konstantinos Kanellis, MSc 2012.
- Fast optimization of non-convex Machine Learning objectives, Nikolaos Nikolaou, MSc 2012.
- Improving the appearance and compression of scanned documents, Nutthaporn Sethasathien, MSc 2012.
- Effect of graph structure on predicting game outcomes, Yu Yang, MSc 2012.
- Cleaning up photos of indexed colour documents, Andrew Burnie, UG4 project, 2012.
- Fast low-rank metric learning, Dan Oneaţă, MSc 2011.
- Rating systems with multiple factors, Marius Stănescu, MSc 2011.
- Empirical evaluation of Gaussian process approximation algorithms, Krzysztof Chalupka, MInf 2011. (Supervised by Chris Williams; I was a second supervisor.)
University of Edinburgh Students: Please see the core skills section of my teaching page. My proposals for this year will appear on DPMT when I have written them. I have a high bar for supervising self-proposed projects. They have to be really well motivated, you have to really know what you are doing, and I have to be good match to the project.
I don't supervise project students from other Universities.
Any past student who would like links to their name or project added or removed, get back in touch.