# To be filled by the author(s) at the time of submission
# -------------------------------------------------------

# Title of the article:
#  - For a successful replication, it shoudl be prefixed with "[Re]"
#  - For a failed replication, it should be prefixed with "[¬Re]"
#  - For other article types, no instruction (but please, not too long)
title: "[¬Re] G-Mixup: Graph Data Augmentation for Graph Classification"

# List of authors with name, orcid number, email and affiliation
# Affiliation "*" means contact author
authors:
  - name: Dylan Cordaro
    orcid: 0009-0000-1528-7356
    email: dcordaro@umich.edu
    affiliations: 1,

  - name: Shelby Cox
    orcid: 0000-0003-4378-5103
    email: spcox@umich.edu
    affiliations: 1,*      # * is for contact author
  
  - name: Yiman Ren
    orcid: 0009-0005-9824-3725
    email: yimanren@umich.edu
    affiliations: 1,
  
  - name: Teresa Yu
    orcid: 0000-0002-8943-5013
    email: twyu@umich.edu
    affiliations: 1,

# List of affiliations with code (corresponding to author affiliations), name
# and address. You can also use these affiliations to add text such as "Equal
# contributions" as name (with no address).
affiliations:
  - code:    1
    name:    University of Michigan
    address: Ann Arbor, Michigan, USA
    



# List of keywords (adding the programming language might be a good idea)
keywords: Python, machine learning, graphical neural networks, mixup, graphon, rescience c

# Code URL and DOI (url is mandatory for replication, doi after acceptance)
# You can get a DOI for your code from Zenodo,
#   see https://guides.github.com/activities/citable-code/
code:
  - url: https://github.com/shelbycox/EECS-553-GMixup-Reproduction
  - doi: 
  - swh: https://archive.softwareheritage.org/swh:1:dir:9c61eef8a6a063061f952ef48145dd9389d45281;origin=https://github.com/shelbycox/GMixup-Reproduction;visit=swh:1:snp:1965f2119279ad07199d175e9fef01092c8f91ec;anchor=swh:1:rev:f3d266957c1e5d4dfe10b1795ab3d8117bf74489
# Date URL and DOI (optional if no data)
data:
  - url:
  - doi:

# Information about the original article that has been replicated
replication:
 - cite: 'Han, X., Jiang, Z., Liu, N. &amp; Hu, X.. (2022). G-Mixup: Graph Data Augmentation for Graph Classification. Proceedings of the 39th International Conference on Machine Learning, in Proceedings of Machine Learning Research 162:8230-8248.'
 - bib:  pmlr-v162-han22c
 - url:  https://proceedings.mlr.press/v162/han22c.html
 - doi:  10.48550,

# Don't forget to surround abstract with double quotes
abstract: "We attempt to reproduce results on a novel graph data mixup method called 'G-Mixup'. We investigate both theoretical and experimental claims on the effectiveness of G-Mixup to produce mixed-up synthetic graphs and to improve the performance of graph neural networks. Although we are able to reproduce some of the original paper's experimental results to within 6\\% of their reported values, our results do not provide statistically significantly evidence that G-Mixup improves the performance of GNNs, nor does it perform better than other data augmentation methods."
# Bibliography file (yours)
bibliography: bibliography.bib
  
# Type of the article
# Type can be:
#  * Editorial
#  * Letter
#  * Replication
type: Replication

# Scientific domain of the article (e.g. Computational Neuroscience)
#  (one domain only & try to be not overly specific)
domain: ML Reproducibility Challenge 2022

# Coding language (main one only if several)
language: Python

  
# To be filled by the author(s) after acceptance
# -----------------------------------------------------------------------------

# For example, the URL of the GitHub issue where review actually occured
review: 
  - url: https://openreview.net/forum?id=T54wy0ahGLG&noteId=pvukxfvJGX

contributors:
  - name:
    orcid: 
    role: editor
  - name:
    orcid:
    role: reviewer
  - name:
    orcid:
    role: reviewer

# This information will be provided by the editor
dates:
  - received:  
  - accepted:
  - published: 

# This information will be provided by the editor
article:
  - number: 1 # Article number will be automatically assigned during publication
  - doi:    # DOI from Zenodo
  - url:    # Final PDF URL (Zenodo or rescience website?)

# This information will be provided by the editor
journal:
  - name: "ReScience C"
  - issn: 2430-3658
  - volume: 9
  - issue: 2
