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.
Joshi, Prashant
Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.
Kakade, Sham
Reinforcement learning and conditioning, mathematical models of neural processing.
Kali, Szabolcs
Learning and memory in the brain, hippocampus.
Kappen, Bert
Boltzmann machines, computational neurobiology, online learning.
Kearns, Michael
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
Keysers, Daniel
Pattern recognition and statistical modelling for object recognition.
Koller, Daphne
Probabilistic models for complex uncertain domains.
Lafferty, John D.
Statistical machine learning, text and natural language processing, information retrieval, information theory.
Lawrence, Neil
Probabilistic models, variational methods.
Lawrence, Steve
Information dissemination and retrieval, machine learning and neural networks.
LeCun, Yann
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
Leen, Todd
Online learning, machine learning, learning dynamics.
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.
McCallum, Andrew
Machine learning, text and information retrieval and extraction, reinforcement learning.
Meila, Marina
Graphical models, learning in high dimensions, tree networks.
Results: Previous 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Next
Site
Menu 
