Neurally controlled robotics.
Inference in graphical models, mean field and variational approaches.
Learning and generalization in neural networks.
Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures
Artificial intelligence, generative topographic map, missing data.
Hybrid and Bayesian networks.
Probabilistic models for complex uncertain domains.
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.
Intermediate level structure in vision.
Machine learning and probabilistic graphical models for computer vision and computational molecular biology.