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Using NGAFID data to predict the safety of flights with SSL.

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NGAFID-SSL: Self-Supervised Learning with General Aviation Data

Team

Name Email
Aidan LaBella [email protected]
Aditya Iyer [email protected]
Charlie Duong [email protected]
Elise Carman [email protected]
Nathan DePiero [email protected]
Justin Long [email protected]

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Installation

$ conda env create --name ngafid-ssl --file ngafid_ssl_environment.yml
$ conda activate ngafid-ssl
$ python run.py

Config file

To change running configurations, pass keyword arguments to the run.py file.

$ python run.py -data ./datasets --dataset-name NGAFID --log-every-n-steps 100 --epochs 100 

To run on CPU use the --disable-cuda option. For 16-bit precision GPU training, use the --fp16_precision flag. This will use Pytorch built in AMP training.

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Using NGAFID data to predict the safety of flights with SSL.

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