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DOI

test

RANGE is a model-agnostic framework that employs an attention-based aggregation-broadcast mechanism to significantly reduce oversquashing effects in message-passing neural networks.

Prerequisites

It is recommended to install the mlcg package (version 0.1.0) in a clean environment by following the official installation instructions available at https://github.com/ClementiGroup/mlcg.

This package provides the core infrastructure used to train and simulate all the models defined in this repository.

Installation

Install the rangemp package inside the newly created environment:

git clone git@github.com:ClementiGroup/range.git range
cd range; pip install .; cd ..

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Public repository of the RANGE architecture.

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