Artificial Intelligence: Neural Networks: People: Page 3

Bayesian theory and inference, error-correcting codes, machine learning.

Vision, Bayesian methods, neural computation.

Gaussian processes, image interpretation, graphical models, pattern recognition.

Research papers and information on biologically inspired neural networks, brain modelling, AI and related topics. A cross-disciplinary site mixing information from physics, neuroscience, cognitive science and other fields.

Learning of probabilistic models, applications to computational biology.

Reinforcement learning, machine learning, supervised learning.

Probabilistic models, variational methods.

Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.

Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.

Automated Analysis of ECG.

Statistical signal and image processing, natural image modelling, graphical models.

Bayesian inference, variational methods, graphical models.

Neural networks and nonlinear modelling for process engineering.

Particle filtering and Monte Carlo Markov Chain methods.

Computational learning theory, discrete mathematics.

Neural networks applied to visual perception and computational modeling of mental disorders.

Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.

Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.

Data structures for computational intelligence.

Computer vision, probabilistic models for image sequences, invariant features.

Machine learning and probabilistic graphical models for computer vision and computational molecular biology.

Learning and generalization in neural networks.