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Code for \"Improving Online Continual Learning Performance and Stability With Temporal Ensemble\"\n\nCode for the paper [Improving Online Continual Learning Performance and Stability With Temporal Ensemble](https://arxiv.org/abs/2306.16817), Soutif--Cormerais et. al., CoLLAs 2023.\n\nThe code is based on [Pytorch](https://pytorch.org) and [Avalanche](https://avalanche.continualai.org).\n\n# Installation\n\nInstall pytorch with conda ([Instructions](https://pytorch.org))\n\ninstall the environment and update it using the environment file\n\n```\ncd avalanchev3\nconda env create -f environment.yml\nconda env config vars set PYTHONPATH=online_ema.git_path:avalanchev3_path\n```\n\nChange the data directory DATADIR inside toolkit/dataset.py to match the one on your system\n\nCreate the results dir\n\n# How to use\n\nTo run single experiments, find the appropriate config file in config dir an run\n\n```\npython main_noboundaries.py --config config/experiment_config.yml\n```\n\nAdd the EMA ensembling and parallel evaluation for more efficient continual evaluation\n\n```\npython main_noboundaries.py --config config/experiment_config.yml --mean_evaluation --parallel_evaluation --eval_every 1\n```\n\n# License\n\nPlease check the License file listed in this repository.\n\n# Cite\n\n```\n@inproceedings{soutifcormerais2023improving,\n  title={Improving Online Continual Learning Performance and Stability with Temporal Ensembles},\n  author={Soutif--Cormerais, Albin and Carta, Antonio and Van de Weijer, Joost},\n  booktitle={Conference on Lifelong Learning Agents},\n  pages={828--845},\n  year={2023},\n  organization={PMLR}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falbinsou%2Fonline_ema","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falbinsou%2Fonline_ema","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falbinsou%2Fonline_ema/lists"}