papers.Rmd

---
docname: Publications
name: Fan Cheng
address: "Department of Econometrics & Business Statistics,\\tabularnewline Monash University, VIC 3800, Australia."
www: fancheng.me
# phone: +61 3 9905 1385
email: "Fan.Cheng@monash.edu"
twitter: fanchengfc
github: ffancheng
linkedin: fan-cheng
date: "`r format(Sys.time(), '%B %Y')`"
headcolor: "880020"
output: 
  vitae::hyndman 
keep_tex: true
header_includes:
  - \ExecuteBibliographyOptions{useprefix=true}
  - renewcommand{\bibfont}{\normalfont\fontsize{12}{15}\sffamily}
  - \usepackage{hanging}
  - \parindent=0pt
  - \parskip=\medskipamount
  # - \pagenumbering{gobble}
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE)
library(tidyverse)
library(vitae)
source("baretable.R")
```

\thispagestyle{empty}

# Working papers

\hangindent=2em
\hangafter=1
Cheng, F., Hyndman, R. J., & Panagiotelis, A. (2021). Computationally Efficient Learning of Statistical Manifolds. arXiv preprint arXiv:2103.11773. (Under review)

\hangindent=2em
\hangafter=1
Cheng, F., Hyndman, R. J., & Panagiotelis, A. (2022). Distortion-Corrected Kernel Density Estimate on Riemannian Manifolds.