To organize research articles that pushes the boundary of machine learning and (graph) neural networks for simulation with the introduction of novel approaches, algorithms, or theoretical insights.
> pip install -r requirements.txt > make run
When the code is ready to be deployed, run make freeze to get a static version of the website in the build folder.
-
Define two command-line variables
GH_TOKENandGH_REF.GH_TOKENis your Github personal access token, and will look likeusername:token.GH_REFis the location of this repo, e.g.,$> export GH_REF=github.com/brownvc/neural-fields-review. -
DO NOT add
GH_TOKENto the Makefile—this is your personal access token and should be kept private. Hence, declare a temporary command line variable usingexport. -
Commit any changes. Any uncommited changes will be OVERWRITTEN!
-
Execute
make deploy. -
That's it.
The repo contains:
- Datastore
sitedata/
Collection of CSV files representing the papers, speakers, workshops, and other important information for the conference.
- Routing
main.py
One file flask-server handles simple data preprocessing and site navigation.
- Templates
templates/
Contains all the pages for the site. See base.html for the master page and components.html for core components.
- Frontend
static/
Contains frontend components like the default css, images, and javascript libs.
- Scripts
scripts/
- Keyword Statistics: The keywords are generated by a JS script (paper_vis_statistics.js line 13-58) running on the front end every time this page is loaded. So yes they will change correspondingly when papers' data is updated.