Past and Current PhD Students and Postdocs

PhD 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