Nature Machine Intelligence'23
This library implements the NVSA functionalities of the paper "A Neuro-vector-symbolic Architecture for Solving Raven's Progressive Matrices". A complete example for solving RAVEN can be found [here]
This module can be installed using pip
, and then simply used by
import nvsa
.
As a prerequisite you should have already installed torch
and numpy
.
To install module from GitHub use one of:
# Install using ssh
pip install git+git@github.com/IBM/neuro-vector-symbolic-architectures.git
# Install using https
pip install git+https://github.com/IBM/neuro-vector-symbolic-architectures.git
If you already have pytorch installed you might want to additionally use --no-dependencies
flag:
# Install using ssh, without dependencies
pip install git+git@github.com/IBM/neuro-vector-symbolic-architectures.git --no-dependencies
# Install using ssh, without dependencies
pip install git+https://github.com/IBM/neuro-vector-symbolic-architectures.git --no-dependencies
This version will automatically reflect any code changes that you make.
# Install from editable local version
pip install -e /path/to/local/neuro-vector-symbolic-architectures
# Also possible without dependencies
pip install -e /path/to/local/neuro-vector-symbolic-architectures --no-dependencies
If you use the work released here for your research, please cite the preprint of this paper:
@article{hersche2022neuro,
title={A Neuro-vector-symbolic Architecture for Solving Raven's Progressive Matrices},
author={Hersche, Michael and Zeqiri, Mustafa and Benini, Luca and Sebastian, Abu and Rahimi, Abbas},
journal={Nat Mach Intell},
year={2023}
}
Our code is licensed under Apache 2.0. Please refer to the LICENSE file for the licensing of our code.