185 citations · 1.3k across the 49 of their papers we have counts for
6 papers · 1 filter
Machine learning spatio-temporal epidemiological model to evaluate Germany-county-level COVID-19 risk
Lingxiao Wang, Tian Xu, Till Hannes Stoecker +3
As the COVID-19 pandemic continues to ravage the world, it is of critical significance to provide a timely risk prediction of the COVID-19 in multi-level. To implement it and evalu…
A fast centrality-meter for heavy-ion collisions at the CBM experiment
Manjunath Omana Kuttan, Jan Steinheimer, Kai Zhou +2
A new method of event characterization based on Deep Learning is presented. The PointNet models can be used for fast, online event-by-event impact parameter determination at the CB…
Identifying the nature of the QCD transition in heavy-ion collisions with deep learning
Yi-Lun Du, Kai Zhou, Jan Steinheimer +5
In this proceeding, we review our recent work using deep convolutional neural network (CNN) to identify the nature of the QCD transition in a hybrid modeling of heavy-ion collision…
Unsupervised Outlier Detection in Heavy-Ion Collisions
Punnathat Thaprasop, Kai Zhou, Jan Steinheimer +1
We present different methods of unsupervised learning which can be used for outlier detection in high energy nuclear collisions. The UrQMD model is used to generate the bulk backgr…
Heavy flavors under extreme conditions in high energy nuclear collisions
Jiaxing Zhao, Kai Zhou, Shile Chen +1
Heavy flavor hadrons have long been considered as a probe of the quark gluon plasma created in high energy nuclear collisions. In this paper we review the heavy flavor properties u…
Continuous-mixture Autoregressive Networks for efficient variational calculation of many-body systems
Lingxiao Wang, Yin Jiang, Lianyi He +1
We develop deep autoregressive networks with multi channels to compute many-body systems with \emph{continuous} spin degrees of freedom directly. As a concrete example, we embed th…