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README.md

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Alternatively you can manually install the required libraries (see the contents of the conda-env.yml files) using ```pip```.
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**Hardware setup:** Training the DNN models (self-driving cars and anomaly detectors) on our datasets is computationally expensive.
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Therefore we recommend using a machine powered by a GPU.
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Therefore we recommend using a machine with GPU.
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In our setting, we ran our experiments on a machine equipped with a i9 processor, 32 GB of memory, and an Nvidia GPU GeForce RTX 2080 Ti with 11GB of dedicated memory.
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## Repository Structure
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### Other Artefacts
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We made the following artifacts available as a torrent file [here](https://academictorrents.com/details/221c3c71ac0b09b1bb31698534d50168dc394cc7). The files have a combined size of 25 GB (compressed: 7.93 GB) , and the torrent contains:
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We made the following artifacts available as a torrent [here](https://academictorrents.com/details/221c3c71ac0b09b1bb31698534d50168dc394cc7). The files have a combined size of 25 GB (compressed: 7.93 GB) , and the torrent contains:
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<pre/>
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- Trained SDC Models
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## Reference
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If use our work in your research, or it helps it, or if you simply like it, please cite SelfOracle in your publications.
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If you use our work in your research, or it helps it, or if you simply like it, please cite SelfOracle in your publications.
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Here is an example BibTeX entry:
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```
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## Contacts
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For any questions, feel free to contact Andrea Stocco ([andrea.stocco@usi.ch](mailto:andrea.stocco@usi.ch))
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or Michael Weiss ([michael.weiss@usi.ch](mailto:michael.weiss@usi.ch)).
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or Michael Weiss ([michael.weiss@usi.ch](mailto:michael.weiss@usi.ch)).

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