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This repository contains the source code used for experiments in the paper: #TODO:add doi for paper
The project covers the steps as given in the schematic below:
To clone and run this application, you'll need to follow the below-mentioned steps:
# Clone this repository
$ git clone https://github.com/ashish1610dhiman/learning_norms_with_mcmc_from_pcfg_IJCAI21
# Go into the repository
$ cd learning_norms_with_mcmc_from_pcfg_IJCAI21
# Install depenencies using pip
$ pip install -r requirements.txt
# Or install depenencies in a conda env
$ conda create --name <env_name> --file requirements.txt
├── LICENSE
|
├── README.md <- The top-level README.
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├── *_supp_material.pdf <- Supplemetary material for paper published in IJCAI-21.
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├── data_nc/* <- Folder with dvc files for various experiments with $p_nn$ > 0
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├── data/* <- Folder with dvc files for various experiments with $p_nn$ = 0
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├── src/
│ ├── mcmc_norm_* <- Code files for grammar/Metropolis Hastings Algorithm/convergence
| | and preciscion-recall
│ └── *.py <- Small Helper files
│
├── scripts/ <- Scripts used for variouis instances of the process depicted in
| | schematic above.
│ └── nc_experiments.py <- Binding script used to run various parts of experiment
|
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`. The notebooks with tag 1.5 mark
| the files used for experiment shown in paper.
|
├── params_nc.yaml <- yaml file detailing parameters for experiments used
│
└── requirements.txt <- The requirements file for reproducing the analysis environment
The project uses
There are two data folders in the repository:
'data/*' and 'data_nc/*' for two workstream of the project
#TODO add experiment structure, and notebooks used, and yaml param files
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