Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

New citation #276

Merged
merged 1 commit into from
Aug 5, 2024
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
29 changes: 8 additions & 21 deletions README.rst
Original file line number Diff line number Diff line change
Expand Up @@ -167,29 +167,16 @@ GOLEM можно установить с помощью ``pip``:
Цитирование
===========

Если вы используете наш проект в своей работе или исследовании, мы будем признательны за цитирование.
Если вы используете наш проект в своей работе или исследовании, мы будем признательны за цитирование:

@article{nikitin2021automated,
title = {Automated evolutionary approach for the design of composite machine learning pipelines},
author = {Nikolay O. Nikitin and Pavel Vychuzhanin and Mikhail Sarafanov and Iana S. Polonskaia and Ilia Revin and Irina V. Barabanova and Gleb Maximov and Anna V. Kalyuzhnaya and Alexander Boukhanovsky},
journal = {Future Generation Computer Systems},
year = {2021},
issn = {0167-739X},
doi = {https://doi.org/10.1016/j.future.2021.08.022}}
@inproceedings{pinchuk2024golem,
title={GOLEM: Flexible Evolutionary Design of Graph Representations of Physical and Digital Objects},
author={Pinchuk, Maiia and Kirgizov, Grigorii and Yamshchikova, Lyubov and Nikitin, Nikolay and Deeva, Irina and Shakhkyan, Karine and Borisov, Ivan and Zharkov, Kirill and Kalyuzhnaya, Anna},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion},
pages={1668--1675},
year={2024}
}

Публикации, описывающие применение GOLEM для прикладных задач:
==============================================================

В данных публикациях описывается применение алгоритмов GOLEM и основанных на нем решений
для различных прикладных задач.

- Алгоритмы поиска оптимального пайплайна машинного обучения для прогнозирования временных рядов: Sarafanov M., Pokrovskii V., Nikitin N. O. Evolutionary Automated Machine Learning for Multi-Scale Decomposition and Forecasting of Sensor Time Series //2022 IEEE Congress on Evolutionary Computation (CEC). – IEEE, 2022. – С. 01-08.

- Алгоритмы идентификации структуры уравнения для акустических данных: Hvatov A. Data-Driven Approach for the Floquet Propagator Inverse Problem Solution //ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). – IEEE, 2022. – С. 3813-3817.

- Алгоритмы идентификации структуры дифференциальных уравнений в частных производных: Maslyaev M., Hvatov A. Solver-Based Fitness Function for the Data-Driven Evolutionary Discovery of Partial Differential Equations //2022 IEEE Congress on Evolutionary Computation (CEC). – IEEE, 2022. – С. 1-8.

- Алгоритмы структурного обучения сетей: Deeva I., Kalyuzhnaya A. V., Alexander V. Boukhanovsky Adaptive Learning Algorithm for Bayesian Networks Based on Kernel Mixtures Distributions//International Journal of Artificial Intelligence. – 2023. - Т.21. - №. 1. - С. 90.

.. |docs| image:: https://readthedocs.org/projects/thegolem/badge/?version=latest
:target: https://thegolem.readthedocs.io/en/latest/?badge=latest
Expand Down
32 changes: 9 additions & 23 deletions README_en.rst
Original file line number Diff line number Diff line change
Expand Up @@ -167,29 +167,15 @@ Contacts
Citation
========

If you use our project in your work or research, we would appreciate citations.

@article{nikitin2021automated,
title = {Automated evolutionary approach for the design of composite machine learning pipelines},
author = {Nikolay O. Nikitin and Pavel Vychuzhanin and Mikhail Sarafanov and Iana S. Polonskaia and Ilia Revin and Irina V. Barabanova and Gleb Maximov and Anna V. Kalyuzhnaya and Alexander Boukhanovsky},
journal = {Future Generation Computer Systems},
year = {2021},
issn = {0167-739X},
doi = {https://doi.org/10.1016/j.future.2021.08.022}}

Papers that describe applications of GOLEM:
===========================================

There are various cases solved with GOLEM's algorithms:

- Algorithms for time series forecasting pipeline design: Sarafanov M., Pokrovskii V., Nikitin N. O. Evolutionary Automated Machine Learning for Multi-Scale Decomposition and Forecasting of Sensor Time Series //2022 IEEE Congress on Evolutionary Computation (CEC). – IEEE, 2022. – С. 01-08.

- Algorithms for acoustic equation discovery: Hvatov A. Data-Driven Approach for the Floquet Propagator Inverse Problem Solution //ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). – IEEE, 2022. – С. 3813-3817.

- Algorithms for PDE discovery: Maslyaev M., Hvatov A. Solver-Based Fitness Function for the Data-Driven Evolutionary Discovery of Partial Differential Equations //2022 IEEE Congress on Evolutionary Computation (CEC). – IEEE, 2022. – С. 1-8.

- Algorithms for structural learning of Bayesian Networks: Deeva I., Kalyuzhnaya A. V., Alexander V. Boukhanovsky Adaptive Learning Algorithm for Bayesian Networks Based on Kernel Mixtures Distributions//International Journal of Artificial Intelligence. – 2023. - Т.21. - №. 1. - С. 90.

If you use our project in your work or research, we would appreciate citations:

@inproceedings{pinchuk2024golem,
title={GOLEM: Flexible Evolutionary Design of Graph Representations of Physical and Digital Objects},
author={Pinchuk, Maiia and Kirgizov, Grigorii and Yamshchikova, Lyubov and Nikitin, Nikolay and Deeva, Irina and Shakhkyan, Karine and Borisov, Ivan and Zharkov, Kirill and Kalyuzhnaya, Anna},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion},
pages={1668--1675},
year={2024}
}

.. |docs| image:: https://readthedocs.org/projects/thegolem/badge/?version=latest
:target: https://thegolem.readthedocs.io/en/latest/?badge=latest
Expand Down
Loading