Unsupervised Generative Modeling Using Matrix Product States

Generative modeling, which learns joint probability distribution from data and generates samples according to it, is an important task in machine learning and artificial intelligence. Inspired by probabilistic interpretation of quantum physics, we propose a generative model using matrix product states, which is a tensor network originally proposed for describing (particularly one-dimensional) entangled quantum states. Our model enjoys efficient learning analogous to the density matrix renormalization group method, which allows dynamically adjusting dimensions of the tensors and offers an efficient direct sampling approach for generative tasks. We apply our method to generative modeling of several standard datasets including the Bars and Stripes, random binary patterns and the MNIST handwritten digits to illustrate the abilities, features and drawbacks of our model over popular generative models such as Hopfield model, Boltzmann machines and generative adversarial networks. Our work sheds light on many interesting directions of future exploration on the development of quantum-inspired algorithms for unsupervised machine learning, which are promisingly possible to be realized on quantum devices.Comment: 11 pages, 12 figures (not including the TNs) GitHub Page: https://congzlwag.github.io/UnsupGenModbyMPS

Aging-associated Alteration in the Cardiac MIF-AMPK Cascade in Response to Ischemic Stress

An important role for a macrophage migration inhibitory factor (MIF)-AMP-activated protein kinase (AMPK) signaling pathway in ameliorating myocardial damage following ischemia/reperfusion has been described. An aging-associated reduction in AMPK activity may be associated with a decline in the ability of cardiac cells to activate the MIF-AMPK cascade, thereby resulting in reduced tolerance to ischemic insults. To test this hypothesis, _in vivo_ regional ischemia was induced by occlusion of the left anterior descending (LAD) coronary artery in young (4-6 months) and aged (24-26 months) mice. The ischemic AMPK activation response was impaired in aged hearts compared to young ones (p<0.01). Notably, cardiac MIF expression in aged hearts was lower than in young hearts (p<0.01). Dual staining data clearly demonstrated larger infarct size in aged hearts following ischemia and reperfusion compared to young hearts (p<0.05). Ischemia-induced AMPK activation in MIF knock out (MIF KO) hearts was blunted, leading to greater contractile dysfunction of MIF KO cardiomyocytes during hypoxia than that of wild type (WT) cardiomyocytes. Finally exogenous recombinant MIF significantly reversed the contractile dysfunction of aged cardiomyocytes in response to hypoxia. We conclude that an aging-associated reduction in ischemic AMPK activation contributes to ischemic intolerance in aged hearts