Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
Machine learning, kernel methods, kernel independent component analysis and graphical models
Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.
Statistical learning theory, support vector machines and kernel methods.
Machine learning and medical data analysis, independent component analysis and information theory.
Graphical models, variational methods, pattern recognition.
An artrificial intelligence researcher who is an expert on neural networks.
Iterative decoding, unsupervised learning, graphical models.
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.
Bayesian theory and inference, error-correcting codes, machine learning.