metadata.yaml

# 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] Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"

# List of authors with name, orcid number, email and affiliation
# Affiliation "*" means contact author
authors:
  - name: HATON Romain
    orcid: 
    email: romain.haton@telecom-sudparis.eu
    affiliations: 1 # * is for contact author
    
  - name: AIT ALI YAHIA Rayane
    orcid: 
    email: 
    affiliations: 1
  
  - name: GAUTHIER Vincent
    orcid: 0000-0003-2252-7332
    email: vincent.gauthier@telecom-sudparis.eu
    affiliations: 1 
    
  - name: BOUZEGHOUB Amel
    orcid: 
    email: amel.bouzeghoub@telecom-sudparis.eu
    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:    SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris
    address: Palaiseau, France


# List of keywords (adding the programming language might be a good idea)
keywords: Recurrent neural network, temporal graph, dynamic embeding, Python

# 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/ComplexNetTSP/JODIE
  - doi: 

# Date URL and DOI (optional if no data)
data:
  - url:
  - doi:

# Information about the original article that has been replicated
replication:
 - cite: S. Kumar, X. Zhang and J. Leskovec. Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks. In: Proceedings 
of the 25th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM. 2019. # Full textual citation
 - bib:  kumar2019predicting # Bibtex key (if any) in your bibliography file
 - url:  https://cs.stanford.edu/~srijan/pubs/jodie-kdd2019.pdf # URL to the PDF, try to link to a non-paywall version
 - doi:  https://doi.org/10.1145/3292500.3330895 # Regular digital object identifier

# Don't forget to surround abstract with double quotes
abstract: ""

# Bibliography file (yours)
bibliography: bibliography.bib
  
# Type of the article
# Type can be:
#  * Editorial
#  * Letter
#  * Replication
type: Editorial

# Scientific domain of the article (e.g. Computational Neuroscience)
#  (one domain only & try to be not overly specific)
domain: Machine Learning

# 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: 

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

# This information will be provided by the editor
dates:
  - received:  November 1, 2018
  - accepted:
  - published: 

# This information will be provided by the editor
article:
  - number: # 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: 4
  - issue:  1