aboutsummaryrefslogtreecommitdiffstats
path: root/resume-en.tex
diff options
context:
space:
mode:
Diffstat (limited to 'resume-en.tex')
-rw-r--r--resume-en.tex19
1 files changed, 10 insertions, 9 deletions
diff --git a/resume-en.tex b/resume-en.tex
index 2139924..31ef68d 100644
--- a/resume-en.tex
+++ b/resume-en.tex
@@ -219,9 +219,9 @@ company goals.
\small
\item \uline{Li,~W.}, Xu,~H., Ma,~Z., Zhu, R., Hu,~D., Zhu,~Z.
Shan,~C., Zhu, J. \& Wu, X.-P.,
- \enquote{\it EoR Signal Separation Using Convolutional Denoising
- Autoencoder,}
- 2018, Monthly Notices of the Royal Astronomical Society
+ \enquote{\it Deep-learning-based Method to Separate the EoR Signal
+ Using the Convolutional Denoising Autoencoder,}
+ 2018, Monthly Notices of the Royal Astronomical Society Letters
(submitted; SCI; IF=4.96)
\item \uline{Li,~W.}, Xu,~H., Ma,~Z., Hu,~D., Zhu,~Z., Shan,~C.,
Wang,~J., Gu,~J., Lian,~X., Zheng,~Q., Zhu, J. \& Wu, X.-P.,
@@ -234,16 +234,17 @@ company goals.
of 14,251 Radio Galaxies Selected from the Best-Heckman's Sample,}
2018, The Astrophysical Journal Supplement Series
(in revision; SCI; IF=8.96)
- \item Zheng,~Q., Johnston-Hollitt,~M., Duchesne,~S. \& \uline{Li,~W.},
- \enquote{\it Detection of a Double Relic in the Torpedo Cluster:
- SPT-Cl J0245-5302,}
- 2018, Monthly Notices of the Royal Astronomical Society
- (in press; SCI; IF=4.96)
\item Hu,~D., Xu,~H., Kang,~X., \uline{Li,~W.}, Zhu,~Z., Ma,~Z.,
Shan,~C., Zhang,~Z., Gu,~L., Liu,~C. \& Wu,~X.-P.,
\enquote{\it A Study of the Merger History of the Galaxy Group
HCG~62 Based on X-ray Observations and SPH Simulations,}
- 2017, The Astrophysical Journal, (in revision; SCI; IF=5.53)
+ 2017, The Astrophysical Journal
+ (in revision; SCI; IF=5.53)
+ \item Zheng,~Q., Johnston-Hollitt,~M., Duchesne,~S. \& \uline{Li,~W.},
+ \enquote{\it Detection of a Double Relic in the Torpedo Cluster:
+ SPT-Cl J0245-5302,}
+ 2018, Monthly Notices of the Royal Astronomical Society, 479, 730
+ (SCI; IF=4.96)
\item Ma,~Z., Zhu,~J., \uline{Li,~W.} \& Xu,~H.,
\enquote{\it An Approach to Detect Cavities in X-ray Astronomical
Images Using Granular Convolutional Neural Networks,}