17 citations · 63 across the 10 of their papers we have counts for
10 papers
Machine learning for discovering laws of nature
Lizhi Xin, Kevin Xin, Houwen Xin
Based on Darwin's natural selection, we developed "machine scientists" to discover the laws of nature by learning from raw data. "Machine scientists" construct physical theories by…
Machine learning for decision-making under uncertainty
Lizhi Xin, Kevin Xin, Houwen Xin
We live in a world brimming with uncertainty, where we constantly have to make a lot of decisions under incomplete information. We are firm believers that our subjective belief can…
Quantum measurement: a game between observer and nature?
Lizhi Xin, Houwen Xin
What is the observer's role in quantum measurement? Obviously, observers prepare the apparatus, observe and interpret the measured results. Although the observer will have a certai…
Can the observer know the state of Schrodinger's cat without opening the box?
Lizhi Xin, Houwen Xin
In order to know if the Schrodinger's cat is alive or dead without opening the box, observers have to play a game with nature. The observers have to "guess" (with degrees of belief…
Coarse-grained Simulations of Chemical Oscillation in a Lattice Brusselator System
Ting Rao, Zhen Zhang, Zhonghuai Hou +1
Accelerated coarse-graining (CG) algorithms for simulating heterogeneous chemical reactions on surface systems have recently gained much attention. In the present paper, we conside…
Coarse-grained Monte Carlo simulations of the phase transition of Potts model on weighted networks
Chuansheng Shen, Hanshuang Chen, Zhonghuai Hou +1
Developing effective coarse grained (CG) approach is a promising way for studying dynamics on large size networks. In the present work, we have proposed a strength-based CG (\sCG)…