Hopfield Model: Memory and Dynamics

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Associative Memory: Magnetic Materials

Explores the dynamics of associative memory in networks of neurons and includes a detour into magnetic materials.

Neuronal Dynamics of Cognition: Associative Memory

Explores associative memory in neuronal networks, neuronal structure, and information processing.

Neuromorphic Computing: Concepts and Hardware Implementations

Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.

Learning of Associations

Delves into associative memory, Hebbian learning, and hierarchical organization in neural networks.

Sensory learning with neural networks

Explores sensory representations, perception, memory, cognitive control, and neural networks.

Nonlinear Supervised Learning

Explores the inductive bias of different nonlinear supervised learning methods and the challenges of hyper-parameter tuning.

Introduction to Systems Neuroscience: Memory Systems Overview

Introduces systems neuroscience, focusing on neural circuits, memory systems, and course logistics.

Brain Intelligence: Continual Learning of Representational Models

Delves into the continual learning of representational models after deployment, highlighting the limitations of current artificial neural networks.

Storage Capacity: Prototypes and Neuronal Dynamics

Explores the storage capacity of associative memory in networks of neurons and the impact of multiple prototypes on error rates.

Statistical Physics of Learning

Offers insights into the statistical physics of learning, exploring the relationship between neural network structure and disordered systems.