People Websites

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

Graphical models, learning in high dimensions, tree networks.

Machine learning and medical data analysis, independent component analysis and information theory.

Bayesian inference, variational methods, graphical models, nonparametric Bayes.

Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.

Graphical models, variational methods, machine learning, reasoning under uncertainty.

Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.

Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.

Graphical models, variational methods, kernel methods.

Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.

Computer vision, computational olfaction.

Non-linear neural dynamics, visual segmentation, sensory processing.

Graphical models, machine learning, reinforcement learning.

Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.

Computer vision, model-based object recognition, face recognition.

Unsupervised learning, machine learning, computational models of neural processing.

Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.

Multitask learning.

Stochastic generative models for complex visual phenomena.

Object recognition, cognitive neuroscience, interaction between vision and motor movements.

Models of human and computer vision.

Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.

Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.

Bayesian inference, Markov chain Monte Carlo simulation, machine learning.

Handwritten recognition, convolutional networks, image compression. Noted for LeNet.

Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.

Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.

Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.

Graphical models, variational methods, pattern recognition.

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.

Vision, Bayesian methods, neural computation.

Learning of probabilistic models, applications to computational biology.

Reinforcement learning, machine learning, supervised learning.

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.

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.

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

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

Learning and generalization in neural networks.

Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures

Hybrid and Bayesian networks.

Probabilistic models for complex uncertain domains.

Machine learning, text and information retrieval and extraction, reinforcement learning.

Statistical learning, machine learning approaches to computational biology, pattern recognition and control.

Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.

Neural network learning, information geometry.

Neural networks, fuzzy systems, computational intelligence.

Machine learning, computer vision, Bayesian methods.

Statistical machine learning, text and natural language processing, information retrieval, information theory.

Learning distributed representation of concepts from relational data.

Neural network ensembles, adaptive systems and applications in neuroinformatics.

Bayesian perception, computer vision, image processing.

Theory of computation, computation in spiking neurons.

Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.

Visual coding, statistics of images, independent components analysis.

Machine learning, pattern recognition, neural networks, voice processing, auditory computation.

Varied machine learning and data analysis topics, including Bayesian inference, relevance vector machine, probabilistic principal component analysis and visualisation methods.

Neural computing, data mining, evolutionary computing, ensemble networks.

Machine learning, kernel methods, kernel independent component analysis and graphical models

Machine learning, Learning from uncertain data.

Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.

Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.

Dedicated to artificial neural networks and their applications in medical research and computational chemistry. Offers a quick tutorial on theory on ANNs written in Persian.

Computational Neuroscientist. Research interests: reservoir computing, computational motor control, computation with spiking neurons.

Researcher at Methodist Hospital Research Institute on classification technology and related fields.

Researcher at University of Science and Technology of China. About image annotation, image retrieval, social network analysis, pattern recognition and machine learning.

Research focusing on Machine Learning, Neural Networks, Kernel Machines, Computer Vision and Speech Processing.

Speech processing, auditory scene analysis, machine learning.

Visual perception, machine vision, image processing.

Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning, causal inference, knowledge representation, preference reasoning.