| --- |
| language: |
| - en |
| pipeline_tag: reinforcement-learning |
| --- |
| # Error Amplification Limits ANN-to-SNN Conversion in Continuous Control |
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| Official **model** release for the **ICML 2026** paper [[`arXiv`](https://arxiv.org/pdf/2601.21778)] [[`GitHub`](https://github.com/xuzijie32/ANN2SNN-CRPI)] |
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| # Well-trained ANN Models |
| The models for DDPG/TD3/SAC agents trained on MuJoCo for 3M steps are stored in `./DDPG&TD3&SAC_MuJoCo/models`. |
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| The models for DrQ-v2 agents trained on DMC are stored in `./DrQ-v2_DMC/exp_local`. |
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| # More Details |
| Code is available at this [GitHub repository](https://github.com/xuzijie32/ANN2SNN-CRPI). You can also view our [paper PDF](https://arxiv.org/pdf/2601.21778). |
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| # Citing This |
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| ```bibtex |
| @article{xu2026error, |
| title={Error Amplification Limits ANN-to-SNN Conversion in Continuous Control}, |
| author={Xu, Zijie and Huang, Zihan and Dong, Yiting and Chen, Kang and Liu, Wenxuan and Yu, Zhaofei}, |
| journal={arXiv preprint arXiv:2601.21778}, |
| year={2026} |
| } |
| ``` |
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