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Related categories 2

Adelson, Edward T.
Visual perception, machine vision, image processing.
Allan, Moray
Computer vision, probabilistic models for image sequences, invariant features.
Amari, Shun-ichi
Neural network learning, information geometry.
Andrieu, Christophe
Particle filtering and Monte Carlo Markov Chain methods.
Anthony, Martin
Computational learning theory, discrete mathematics.
Bach, Francis
Machine learning, kernel methods, kernel independent component analysis and graphical models
Beal, Matthew J.
Bayesian inference, variational methods, graphical models, nonparametric Bayes.
Becker, Sue
Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.
Beveridge, Ross
Computer vision, model-based object recognition, face recognition.
Bishop, Chris
Graphical models, variational methods, pattern recognition.
Boutilier, Craig
Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.
Brown, Andrew
Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
Bulsari, A.
Neural networks and nonlinear modelling for process engineering.
Calvin, William H.
Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.
Caruana, Rich
Multitask learning.
Coolen, Ton
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
Dayan , Peter
Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.
de Freitas, Nando
Bayesian inference, Markov chain Monte Carlo simulation, machine learning.
De vito, Saverio
Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures
Dietterich, Thomas G.
Reinforcement learning, machine learning, supervised learning.
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.
Freeman, William T.
Bayesian perception, computer vision, image processing.
Frey, Brendan J.
Iterative decoding, unsupervised learning, graphical models.
Friedman, Nir
Learning of probabilistic models, applications to computational biology.
Grangier, David
Research focusing on Machine Learning, Neural Networks, Kernel Machines, Computer Vision and Speech Processing.
Hansen, Lars Kai
Neural network ensembles, adaptive systems and applications in neuroinformatics.
Heskes, Tom
Learning and generalization in neural networks.
Hinton, Geoffrey E.
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.
Honavar, Vasant
Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning, causal inference, knowledge representation, preference reasoning.
Hughes, Nicholas
Automated Analysis of ECG.
Jaakkola, Tommi S.
Graphical models, variational methods, kernel methods.
Jordan, Michael I.
Graphical models, variational methods, machine learning, reasoning under uncertainty.
Kearns, Michael
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
Koller, Daphne
Probabilistic models for complex uncertain domains.
Lafferty, John D.
Statistical machine learning, text and natural language processing, information retrieval, information theory.
LeCun, Yann
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
Leow, Wee Kheng
Computer vision, computational olfaction.
Lerner, Uri N.
Hybrid and Bayesian networks.
Li, Zhaoping
Non-linear neural dynamics, visual segmentation, sensory processing.
Maass, Wolfgang
Theory of computation, computation in spiking neurons.
MacKay, David
Bayesian theory and inference, error-correcting codes, machine learning.
Malchiodi, Dario
Machine learning, Learning from uncertain data.
McCallum, Andrew
Machine learning, text and information retrieval and extraction, reinforcement learning.
Meila, Marina
Graphical models, learning in high dimensions, tree networks.
Minka, Thomas P.
Machine learning, computer vision, Bayesian methods.
Muresan, Raul C.
Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.
Murphy, Kevin P.
Graphical models, machine learning, reinforcement learning.
Murray-Smith, Roderick
Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.
Neal, Radford
Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.
Oja, Erkki
Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.
Olshausen, Bruno
Visual coding, statistics of images, independent components analysis.
Paccanaro, Alberto
Learning distributed representation of concepts from relational data.
Pearlmutter, Barak
Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.
Peterson, Leif E.
Researcher at Methodist Hospital Research Institute on classification technology and related fields.
Prashant, Joshi
Computational Neuroscientist. Research interests: reservoir computing, computational motor control, computation with spiking neurons.
Rao, Rajesh P. N.
Models of human and computer vision.
Rasmussen, Carl Edward
Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.
Roberts, Stephen
Machine learning and medical data analysis, independent component analysis and information theory.
Rovetta, Stefano
Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.
Roweis, Sam T.
Speech processing, auditory scene analysis, machine learning.
Russell, Stuart
Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.
Rutkowski, Leszek
Neural networks, fuzzy systems, computational intelligence.
Saul, Lawrence K.
Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
Storkey, Amos
Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.
Tipping, Mike
Varied machine learning and data analysis topics, including Bayesian inference, relevance vector machine, probabilistic principal component analysis and visualisation methods.
Tishby, Naftali
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.
Versace, Massimiliano
Neural networks applied to visual perception and computational modeling of mental disorders.
Wainwright, Martin
Statistical signal and image processing, natural image modelling, graphical models.
Wallis, Guy
Object recognition, cognitive neuroscience, interaction between vision and motor movements.
Weiss, Yair
Vision, Bayesian methods, neural computation.
Williams, Christopher K. I.
Gaussian processes, image interpretation, graphical models, pattern recognition.
Winther, Ole
Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.
Wu, Yingnian
Stochastic generative models for complex visual phenomena.
Xiaoguang, Rui
Researcher at University of Science and Technology of China. About image annotation, image retrieval, social network analysis, pattern recognition and machine learning.
Xing, Eric
Statistical learning, machine learning approaches to computational biology, pattern recognition and control.
Zemel, Richard
Unsupervised learning, machine learning, computational models of neural processing.
Zhou, Zhi-Hua
Neural computing, data mining, evolutionary computing, ensemble networks.
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Last update:
February 1, 2017 at 16:05:04 UTC
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