Inverse Ising techniques to infer underlying mechanisms from data

• 作 者: 曾红丽 Erik Aurell
• 机 构: SchoolofScience,Nordita,KTH-RoyalInstituteofTechnology,FacultyofPhysics
• 出 处: 中国物理B:英文版
• 发表日期: 2020年8期
• 关键词: inverse Ising problem kinetic Ising model statistical genetics fitness reconstru
• 基金项目: the National Natural Science Foundation of China(Grant No.11705097),the Natural Science Foundation of Jiangsu Province of China(Grant No.BK20170895),the Jiangsu Government Scholarship for Overseas Stu

As a problem in data science the inverse Ising(or Potts)problem is to infer the parameters of a Gibbs-Boltzmann distributions of an Ising(or Potts)model from samples drawn from that distribution.The algorithmic and computational interest stems from the fa