Assembly theory came to my attention from a podcast interview https://lexfridman.com/lee-cronin-3/. It seems to be something relevant to our scope of study. Learning can be a selection process of a computational system to fill some functional needs. But, some how such a system tends to become more complex as more is learned. The recent paper…
Read More Complexity and assembly theoryPresented in STATPHYS28 Satellite Meeting – Emergence in Biological Networks Abstract With increasing integration of artificial intelligence in our everyday life, the understanding and accountability of the solutions provided by machines are ever more important. This parallels the study of animal brains and biological neural networks. Instead of tracing out microscopic details of the neural…
Read More Statistical modeling the internal states of a learning machineOffered by Institute of Neuroscience, National Yang Ming Chiao Tung University, this course is intended to provide an overview on the statistical, analytic, and computational tools that are commonly used in the research field of neuroscience. It will focus on characterizing the strength and applicability of various data analytical approaches in some more intuitive than…
Read More Data Analysis in Neuroscience, Spring 2023Ching-I Huang, Chun-Chung Chen, Hsiu-Hau Lin Scientific Reports 12, Article number: 22403 (2022) DOI: 10.1038/s41598-022-27102-0 Evolutionary dynamics is well captured by the replicator equations when the population is infinite and well-mixed. However, the extinction dynamics is modified with finite and structured populations. Experiments on the non-transitive ecosystem containing three populations of bacteria found that the…
Read More Universal scaling of extinction time in stochastic evolutionary dynamics