Conference presentation on computationally demanding studies of synaptic plasticity on the molecular level. Speaker: Kim "Avrama" Blackwell.
Introduction to modelling of chemical computation in the brain. Speaker: Upi Bhalla
Forms of plasticity on many levels - short-term, long-term, metaplasticity, structural plasticity. With examples related to modelling of biochemical networks. Speaker: Upi Bhalla.
University of Toronto
Introduction to simple abstract models of neurons. Speaker: Geoffrey Hinton.
Introduction to simple spiking neuron models. Author: Zubin Bhuyan, Tezpur University
Talk on theoretical network dynamics in networks of unreliable neurons, and applications in modeling, given at a colloquium at NYU Physics. Speaker: Larry Abbott.
International Centre for Theoretical Sciences
Introduction to stability analysis of neural models. Speaker: Bard Ermentrout
Introduction to the Mathematics chapter of Datalabcc's "Foundations in Data Science" series. Speaker: Barton Poulson.
Datalabcc: Foundations of Data Science. Data science relies on several important aspects of mathematics. In this course, you'll learn what forms of mathematics are most useful for data science, and see some worked examples of how math can solve important data science problems.