Spatial Continuum: Field Equations

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (31)

Page 1 of 4

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.

Neuronal Dynamics: Aims and Challenges

Explores the aims and challenges in computational neuroscience, focusing on neuronal dynamics of cognition and mean-field arguments.

Data-Driven Modeling in Neuroscience: Meenakshi Khosla

By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.

Neuroscience and Machine Learning: Understanding Visual Intelligence

Explores the relationship between neuroscience and machine learning in visual intelligence.

Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

Neural Networks: Hierarchical Models and Odor Taxis

Covers neural function, hierarchical models, odor taxis behaviors, and disparate circuit parameters in 18 slides.

Perception: Field Models

Explores computational neuroscience aspects of perception using field models and spatial continuum models.

Sensory learning with neural networks

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

Neuronal Dynamics: Solution Types

Explores solution types in computational neuroscience, focusing on homogeneous and bump solutions in neuronal dynamics.

Spatial Continuum: Cortex

Explores cortical fields, orientation columns, solution types, and perception in computational neuroscience.