Neural Networks for Action Learning: Three-Factor Rules and Dopamine

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (30)

Page 3 of 3

Explores neuroplasticity, brain stimulation techniques, and their applications in various neuro-psychiatric disorders and motor learning.

Neuroscience and AI: Bridging the Gap

Explores the gap between AI and human intelligence through neuroscience-inspired models and algorithms.

Deep Learning Fundamentals

Introduces deep learning fundamentals, covering data representations, neural networks, and convolutional neural networks.

Neural Architectures for Embodied AI and Cognition

Explores neural architectures for embodied AI, cognitive systems, and the integration of computing and robotics.

Understanding Learning Dynamics of Neural Networks

Explores neural network learning dynamics, covering optimization, interference, and continual learning challenges.

Reward-based Learning: Cellular Mechanisms

Explores reward-based learning in neuronal networks and the role of dopamine in synaptic plasticity.

Deep Learning

Covers the fundamentals of deep learning, including data representations, bag of words, data pre-processing, artificial neural networks, and convolutional neural networks.

Computer Vision: Historical Insights and Project Inspirations

Explores the historical development of computer vision and inspires innovative project ideas.

Reinforcement Learning: Policy Gradient and Actor-Critic Methods

Provides an overview of reinforcement learning, focusing on policy gradient and actor-critic methods for deep artificial neural networks.

AI Gamer: D4

Explores reinforcement learning in AI to master games using neural networks.