Koller, Daphne
Probabilistic models for complex uncertain domains.
Lerner, Uri N.
Hybrid and Bayesian networks.
Dr Hooman Shadnia
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.
Cottrell, Garrison W.
An artrificial intelligence researcher who is an expert on neural networks.
Zhou, Zhi-Hua
Neural computing, data mining, evolutionary computing, ensemble networks.
Dietterich, Thomas G.
Reinforcement learning, machine learning, supervised learning.
Hansen, Lars Kai
Neural network ensembles, adaptive systems and applications in neuroinformatics.
Winther, Ole
Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.
Bartlett, Marian Stewart
Image analysis with unsupervised learning, face recognition, facial expression analysis.
Calvin, William H.
Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.
Seung, Sebastian
Short-term memory, learning and memory in the brain, computational learning theory.
Malchiodi, Dario
Machine learning, Learning from uncertain data.
Paccanaro, Alberto
Learning distributed representation of concepts from relational data.
Wiskott, Laurenz
Face recognition, Invariances in learning and vision.
Lawrence, Steve
Information dissemination and retrieval, machine learning and neural networks.
Sallans, Brian
Decision making under uncertainty, reinforcement learning, unsupervised learning.
Smola, Alex J.
Kernel methods for prediction and data analysis.
Joseph Wakeling's Neural Systems Research Page
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.
Schetinin, Vitaly
Biomedical data mining, diagnostic rule extraction and quality control in industry using a variety of techniques.
Freeman, William T.
Bayesian perception, computer vision, image processing.
Olshausen, Bruno
Visual coding, statistics of images, independent components analysis.
Attias, Hagai
Graphical models, variational Bayes, independent factor analysis.
Bishop, Chris
Graphical models, variational methods, pattern recognition.
Minka, Thomas P.
Machine learning, computer vision, Bayesian methods.
Frohlich, Jochen
Overview of neural networks, and explanation of Java classes that implement backpropagation, and Kohonen feature maps.
Adelson, Edward T.
Visual perception, machine vision, image processing.
Shkolnik, Alexander
Neurally controlled robotics.
Sutton, Richard S.
Reinforcement learning.
Pearlmutter, Barak
Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.
Chu, Selina
Artificial intelligence, machine learning, data mining.
Bulsari, A.
Neural networks and nonlinear modelling for process engineering.
De vito, Saverio
Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures
Jaakkola, Tommi S.
Graphical models, variational methods, kernel methods.
Storkey, Amos
Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.
Amari, Shun-ichi
Neural network learning, information geometry.
Oja, Erkki
Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.
Schein, Andrew I.
Machine learning approaches to data mining focussing on text mining applications.
Kearns, Michael
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
Leow, Wee Kheng
Computer vision, computational olfaction.
Jensen, Finn Verner
Graphical models, belief propagation.
Jordan, Michael I.
Graphical models, variational methods, machine learning, reasoning under uncertainty.
Murphy, Kevin P.
Graphical models, machine learning, reinforcement learning.
Russell, Stuart
Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.
Caruana, Rich
Multitask learning.
Xing, Eric
Statistical learning, machine learning approaches to computational biology, pattern recognition and control.
Lafferty, John D.
Statistical machine learning, text and natural language processing, information retrieval, information theory.
Beveridge, Ross
Computer vision, model-based object recognition, face recognition.
Friedman, Nir
Learning of probabilistic models, applications to computational biology.
Tishby, Naftali
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.
Weiss, Yair
Vision, Bayesian methods, neural computation.
Honavar, Vasant
Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.
Ballard, Dana H.
Visual perception with neural networks.
Heskes, Tom
Learning and generalization in neural networks.
Boutilier, Craig
Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.
Hinton, Geoffrey E.
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.
Neal, Radford
Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.
Revow, Michael
Hand-written character recognition.
Roweis, Sam T.
Speech processing, auditory scene analysis, machine learning.
de Freitas, Nando
Bayesian inference, Markov chain Monte Carlo simulation, machine learning.
Saul, Lawrence K.
Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
McCallum, Andrew
Machine learning, text and information retrieval and extraction, reinforcement learning.
Welling, Max
Unsupervised learning, probabilistic density estimation, machine vision.
Teh, Yee Whye
Learning and inference in complex probabilistic models.
Zemel, Richard
Unsupervised learning, machine learning, computational models of neural processing.
Rao, Rajesh P. N.
Models of human and computer vision.
Garcia, Christophe
Computer vision, image analysis, neural networks.
Beal, Matthew J.
Bayesian inference, variational methods, graphical models, nonparametric Bayes.
Leen, Todd
Online learning, machine learning, learning dynamics.
Brody, Carlos D.
Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology.
Andonie, Razvan
Data structures for computational intelligence.
Williams, Christopher K. I.
Gaussian processes, image interpretation, graphical models, pattern recognition.
Murray-Smith, Roderick
Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.
Lawrence, Neil
Probabilistic models, variational methods.
Bach, Francis
Machine learning, kernel methods, kernel independent component analysis and graphical models
Rovetta, Stefano
Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.
Brown, Andrew
Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
Murray, Alan
Neural networks and VLSI hardware.
Wainwright, Martin
Statistical signal and image processing, natural image modelling, graphical models.
Dayan , Peter
Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.
Rasmussen, Carl Edward
Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.
Sahani, Maneesh
Statistical analysis of neural data, experimental design in neuroscience.
Kakade, Sham
Reinforcement learning and conditioning, mathematical models of neural processing.
Kali, Szabolcs
Learning and memory in the brain, hippocampus.
Li, Zhaoping
Non-linear neural dynamics, visual segmentation, sensory processing.
Ghahramani, Zoubin
Sensorimotor control, unsupervised learning, probabilistic machine learning.
Bengio, Samy
Torch machine learning library, including SVMTorch support vector machine program. Research on mixture models, hidden markov models, multimodal fusion, speaker verification.
Joshi, Prashant
Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.
Maass, Wolfgang
Theory of computation, computation in spiking neurons.
Agakov, Felix
Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and causality.
MacKay, David
Bayesian theory and inference, error-correcting codes, machine learning.
de Garis, Hugo
Evolvable neural network models, neural networks for programmable hardware, large neural networks.
Rutkowski, Leszek
Neural networks, fuzzy systems, computational intelligence.
Prashant, Joshi
Computational neuroscientist, with main areas of research interest being computational motor control, computational models of olfaction, computation with spiking neurons, neurocomputational basis of working memory and decision making, learning in biologically realistic circuits.
Shuurmans, Dale
Computational learning, complex probability modelling.
Olier, Ivan
Artificial intelligence, generative topographic map, missing data.
De Wilde, Philippe
Brain inspired models of uncertainty, linguistic and fuzzy uncertainty, uncertainty in dynamic multi-user environments.
Anthony, Martin
Computational learning theory, discrete mathematics.
Versace, Massimiliano
Neural networks applied to visual perception and computational modeling of mental disorders.
Wiegerinck, Wim
Inference in graphical models, mean field and variational approaches.
Yedidia, Jonathan S.
Statistical methods for inference and learning.
Dahlem, Markus A.
Neural network models of visual cortex to model neurological symptoms of migraine.
Tipping, Mike
Varied machine learning and data analysis topics, including Bayesian inference, relevance vector machine, probabilistic principal component analysis and visualisation methods.
Allan, Moray
Computer vision, probabilistic models for image sequences, invariant features.
Coolen, Ton
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
Opper, Manfred
Statistical physics, information theory and applied probability and applications to machine learning and complex systems.
Saad, David
Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques.
Cheung, Vincent
Machine learning and probabilistic graphical models for computer vision and computational molecular biology.
Frey, Brendan J.
Iterative decoding, unsupervised learning, graphical models.
Muresan, Raul C.
Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.
Herbrich, Ralph
Statistical learning theory, support vector machines and kernel methods.
Simard, Patrice
Machine learning and generalization.
Hughes, Nicholas
Automated Analysis of ECG.
Sykacek, Peter
Brain Computer Interface.
Roberts, Stephen
Machine learning and medical data analysis, independent component analysis and information theory.
Sejnowski, Terry
Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations.
Becker, Sue
Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.
Wu, Yingnian
Stochastic generative models for complex visual phenomena.
Meila, Marina
Graphical models, learning in high dimensions, tree networks.
Andrieu, Christophe
Particle filtering and Monte Carlo Markov Chain methods.
Wallis, Guy
Object recognition, cognitive neuroscience, interaction between vision and motor movements.
Saund, Eric
Intermediate level structure in vision.
LeCun, Yann
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
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