Past and Current PhD Students and Postdocs
PhD Students
(with year and thesis title for graduated students)
- Francesco Vivarelli (1999)
Studies on the Generalisation of Gaussian Processes and Bayesian
Neural Networks
- Nicholas Adams (2001)
Dynamic Trees: A Hierachical Probabilistic Approach to Image Modelling
- Stephen Felderhof (2003)
Tree-Structured Graphical Models and Image Analysis
- Matthias Seeger (2003)
Bayesian Gaussian Process Models: PAC-Bayesian Generalisation Error
Bounds and Sparse Approximations
- Michalis Titsias (2005)
Unsupervised Learning of Multiple Objects in Images
- Michael Schouten (2006)
Modeling Dependencies in Genetic-marker Data
and its Application to Haplotype Analysis
- John Quinn (2007)
Bayesian Condition Monitoring in Neonatal Intensive Care
- Moray Allan (2007)
Sprite Learning and Object Category Recognition using Invariant Features
- Edwin Bonilla (2008)
Compilers that Learn to Optimise: A Probabilistic Machine Learning
Approach
- Kian Ming Adam Chai (2010)
Multi-task Learning with Gaussian Processes
- Nicolas Heess (2011)
Learning Generative Models of Mid-level Structure in Natural Images
- Ondrej Mandula (2013)
Super-resolution Methods for Fluorescence Microscopy
- Ali Eslami (2013)
Generative Probabilistic Models for Object Segmentation
- Jyri Kivinen (2013)
Statistical Models for Natural Scene Data
- Ioan Stanculescu (2015)
Dynamical Models for Neonatal Intensive Care Monitoring
- Konstantinos Georgatzis (2017)
Dynamical Probabilistic Graphical Models
applied to Physiological Condition Monitoring
- Pol Moreno (2018)
Vision as Inverse Graphics for Detailed Scene Understanding
- Lukasz Romaszko
- Charlie Nash
- Alex Bird
- Taha Ceritli
- Cian Eastwood
- Michael Camilleri
Postdocs
- Xiaojuan Feng
- Amos Storkey
- Marc Toussaint
- Felix Agakov
- Stefan Harmeling
- Edwin Bonilla
- Partha Lal
- Sohan Seth
Chris Williams