activity
20202026
most citedPhysics-Informed Supervised Residual Learning for Electromagnetic Modeling

54 citations · 95 across the 8 of their papers we have counts for

collaborators

8 papers

physics.geo-ph2026

Feature-based Inversion of 2.5D Controlled Source Electromagnetic Data using Generative Priors

Hongyu Zhou, Haoran Sun, Rui Guo +3

In this study, we investigate feature-based 2.5D controlled source marine electromagnetic (mCSEM) data inversion using generative priors. Two-and-half dimensional modeling using fi…

physics.comp-ph2022

Analysis of Degrees of Freedom in Scattered Fields for Nonlinear Inverse Scattering Problems

Zhichao Lin, Rui Guo, Tao Shan +4

In the study of nonlinear inverse scattering problems (ISPs), the traditional method for estimating the number of degrees of freedom (NDoF) of the scattered field does not consider…

physics.comp-ph2022★ 2 cited

Physics Embedded Machine Learning for Electromagnetic Data Imaging

Rui Guo, Tianyao Huang, Maokun Li +2

Electromagnetic (EM) imaging is widely applied in sensing for security, biomedicine, geophysics, and various industries. It is an ill-posed inverse problem whose solution is usuall…

astro-ph.EP2021★ 11 cited

TESS Timings of 31 Hot Jupiters with Ephemeris Uncertainties

Su-Su Shan, Fan Yang, You-Jun Lu +8

A precise transit ephemeris serves as the premise for follow-up exoplanet observations. We compare TESS Objects of Interest (TOI) transit timings of 262 hot Jupiters with the archi…

astro-ph.EP2021★ 9 cited

An Empirical Bayesian Approach to Limb-darkening in Modeling WASP-121b Transit Light Curves

Fan Yang, Richard J. Long, Ji-Feng Liu +6

We present a novel, iterative method using an empirical Bayesian approach for modeling the limb darkened WASP-121b transit from the TESS light curve. Our method is motivated by the…

physics.comp-ph2021★ 54 cited

Physics-Informed Supervised Residual Learning for Electromagnetic Modeling

Tao Shan, Jinhong Zeng, Xiaoqian Song +4

In this study, physics-informed supervised residual learning (PhiSRL) is proposed to enable an effective, robust, and general deep learning framework for 2D electromagnetic (EM) mo…

astro-ph.GA2020★ 2 cited

Galaxy Optical Variability of Virgo Cluster: New Tracer for Environmental Influences on Galaxies

Fan Yang, Richard J. Long, Su-Su Shan +6

We investigate the relationship between the optical variability of galaxies and their distances from the centre of the Virgo Cluster using Palomar Transient Factory data. We define…

astro-ph.SR2020★ 17 cited

A Catalog of Short Period Spectroscopic and Eclipsing Binaries Identified from the LAMOST & PTF Surveys

Fan Yang, Richard J. Long, Su-Su Shan +7

Binaries play key roles in determining stellar parameters and exploring stellar evolution models. We build a catalog of 88 eclipsing binaries with spectroscopic information, taking…