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nicl-nno committed Dec 27, 2024
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.. list-table::
:stub-columns: 1

* - package
- | |pypi| |python|
* - tests
- | |build|
* - docs
- |docs|
* - license
- | |license|
* - support
- | |tg|
* - gitlab
- | |gitlab|
* - funding
- | |ITMO| |NCCR|

.. end-badges
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How to use
==========

All details about first steps with GEFEST might be found in the `quick start guide <https://gefest.readthedocs.io/en/latest/gefest/quickstart.html>`__
and in the `tutorial for novices </docs/tutorials/sample.rst>`__
All details about first steps with GEFEST might be found in the `quick start guide <https://gefest.readthedocs.io/en/latest/gefest/quickstart.html>`__.

Tutorals for more spicific use cases can be found `tutorial section of docs <https://gefest.readthedocs.io/en/latest/tutorials/index.html>`__.

Project Structure
=================
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* Package `cases <https://github.com/ITMO-NSS-team/GEFEST/tree/main/cases>`__ includes several *how-to-use-cases* where you can start to discover how GEFEST works;
* All *unit and integration tests* can be observed in the `test <https://github.com/ITMO-NSS-team/GEFEST/tree/main/test>`__ directory;
* The sources of the documentation are in the `docs <https://github.com/ITMO-NSS-team/GEFEST/tree/main/docs>`__.
* Weights of pretrained DL models can be downloaded from `this repository <https://gitlab.actcognitive.org/itmo-nss-team/gefest-models>`__.

Cases and examples
==================
**Note**: To run the examples below, the old kernel gefest version, which can be installed on python 3.7 with:

.. code-block:: bash
pip install git+https://github.com/aimclub/GEFEST.git@4f9c34c449c0eb65d264476e5145f09b4839cd70
- `Experiments <https://github.com/ITMO-NSS-team/GEFEST-paper-experiments>`__ with various real and synthetic cases
- `Case <https://github.com/ITMO-NSS-team/rbc-traps-generative-design>`__ devoted to the red blood cell traps design.

Migrated examples can be found in cases folder of the main branch.

Current R&D and future plans
============================

Currently, we are working on integration of new types of physical objects with consideration of their internal structure.\n

The major ongoing tasks:

* to make the use of GEFEST more accessible and simple for users
* to integrate three dimensional physical objects
* to implement gradient based approaches for optimization of physical objects
* to improve efficiency of GEFEST's standard sampler

Documentation
=============
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implementation for the development of the high-tech field of
Artificial Intelligence for the period up to 2030 (agreement 70-2021-00187).


Citation
========

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volume={119},
pages={105715},
year={2023},
publisher={Elsevier}
}
publisher={Elsevier}}

@inproceedings{solovev2023ai,
title={AI Framework for Generative Design of Computational Experiments with Structures in Physical Environment},
author={Solovev, Gleb Vitalevich and Kalyuzhnaya, Anna and Hvatov, Alexander and Starodubcev, Nikita and Petrov, Oleg and Nikitin, Nikolay},
booktitle={NeurIPS 2023 AI for Science Workshop},
year={2023}}

.. |build| image:: https://github.com/aimclub/GEFEST/workflows/unit%20tests/badge.svg?branch=main
:alt: Build Status
:target: https://github.com/aimclub/GEFEST/actions

.. |docs| image:: https://readthedocs.org/projects/gefest/badge/?version=latest
:target: https://gefest.readthedocs.io/en/latest/?badge=latest
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.. |tg| image:: https://img.shields.io/badge/Telegram-Group-blue.svg
:target: https://t.me/gefest_helpdesk
:alt: Telegram Chat
:alt: Telegram Chat

.. |ITMO| image:: https://github.com/ITMO-NSS-team/open-source-ops/blob/add_badge/badges/ITMO_badge_rus.svg
:alt: Acknowledgement to ITMO
:target: https://itmo.ru

.. |NCCR| image:: https://github.com/ITMO-NSS-team/open-source-ops/blob/add_badge/badges/NCCR_badge.svg
:alt: Acknowledgement to NCCR
:target: https://actcognitive.org/

.. |gitlab| image:: https://img.shields.io/badge/mirror-GitLab-orange
:alt: GitLab mirror for this repository
:target: https://gitlab.actcognitive.org/itmo-nss-team/GEFEST

.. |pypi| image:: https://img.shields.io/pypi/v/gefest.svg
:alt: PyPI Package Version
:target: https://img.shields.io/pypi/v/gefest

.. |python| image:: https://img.shields.io/pypi/pyversions/gefest.svg
:alt: Supported Python Versions
:target: https://img.shields.io/pypi/pyversions/gefest

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