MOOC
Neurorobotics
Lectures in this MOOC (51)
Introduction to sensory learningMOOC: Neuro Robotics
Explores sensor representations and learning rules to understand how complex sensor representations emerge.
Sensory learning with neural networksMOOC: Neuro Robotics
Explores sensory representations, perception, memory, cognitive control, and neural networks.
The visual systemMOOC: Neuro Robotics
Explores perceptrons in neural networks and their analogy with the visual system.
Receptive Field DevelopmentMOOC: Neuro Robotics
Explores receptive fields in neurobiology, from basic concepts to complex formations and neural plasticity.
Modeling the receptive field developmentMOOC: Neuro Robotics
Covers receptive field development, self-organization principles, neuron models, and Hebbian learning.
Analyzing Hebbian Learning RuleMOOC: Neuro Robotics
Explores rate-based Hebbian learning, covariance rules, and weight vector growth in neural networks.
Simple Hebbian learning rules and correlated inputsMOOC: Neuro Robotics
Explains how weight vectors converge to identical values and how correlated input units dominate the activity of the output neuron.
Oja's RuleMOOC: Neuro Robotics
Covers Oja's rule in Neurorobotics, focusing on learning eigenvectors and eigenvalues for capturing maximal variance.
Examples applications of Oja's learning ruleMOOC: Neuro Robotics
Explores examples of applying Oja's learning rule in neural networks.
Principles of Self-OrganizationMOOC: Neuro Robotics
Explores how global order arises from local interactions in neural networks.