Semi-supervised_Invertible_Neural_Operators

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Semi-supervised_Invertible_Neural_Operators

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Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems

Semi-supervised_Invertible_Neural_Operators 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# [Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems](https://link.springer.com/article/10.1007/s00466-023-02298-8)

Article is Open Access and can be downloaded using the provided link:
https://link.springer.com/article/10.1007/s00466-023-02298-8

## Keywords:
- Data-driven surrogates
- Invertible neural networks
- Bayesian inverse problems
- Semi-supervised learning

## Content:
The scripts provided can be used to generate the results in the paper for the antiderivative case as well as the Reaction-diffusion case.

## Dependencies
- Jax 0.4.1
- Pytorch 1.13.1 (only for Dataset generation)

## Google Colab (05/2024)
Link to a Google Colab version for the antiderivative test case:
https://colab.research.google.com/drive/1t2eTwcTaWX5Jn92VR3ny4eIRBVFS2nqE?usp=sharing

## Citation
If this code is relevant for your research, please consider citing:
```
@article{kaltenbach2023invertibleNeuralOperators,
  title={Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems},
  author={Kaltenbach, Sebastian and Perdikaris, Paris and Koutsourelakis, Phaedon-Stelios},
  journal={Computational Mechanics},
  year={2023},
  publisher={Springer},
  doi = "https://doi.org/10.1007/s00466-023-02298-8",
  url = "https://link.springer.com/article/10.1007/s00466-023-02298-8"
}
```

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