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| Format: | Recurso digital |
| Language: | English |
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2025
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| Online Access: | https://doi.org/10.5281/zenodo.15225294 |
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| author | Al Shidi, Qusai Mehta, Piyush |
| author_facet | Al Shidi, Qusai Mehta, Piyush |
| contents | <p>ram_scb_autoencoder<br>==============================</p> <p>An autoencoder model for the RAM-SCB inner magnetosphere model.</p> <p>Project Organization<br>------------</p> <p> ├── README.md <- The top-level README for developers using this project.<br> ├── data<br> │ ├── processed <- The final, canonical data sets for modeling.<br> ├── models <- Trained and serialized models, model predictions, or model summaries<br> ├── src <- Source code for training and visualization</p> <p>Data<br>----</p> <p>dates_*.npy <- the datetime objects of the test,<br>validation and training datasets.<br>log_*.npy <- Inputs into the model (unscaled).<br>lstm_input*.npy <- Inputs into the lstm before sequencing.<br>*_enc.npy <- Data after encoding using the autoencoder.<br>*_enc_oae.npy <- Data after encoding using the orthogonal autoencoder.<br>rope_ae_* <- The outputs of the rope using autoencoder.<br>rope_oae_* <- The outputs of the rope using orthogonal autoencoder.</p> <p>Models<br>------</p> <p>autoencoder_bo_best.keras <- Autoencoder model.<br>autoencoder_ortho_decoder.keras <- Decoder for the orthogonal autoencoder.<br>autoencoder_ortho_encoder.keras <- Encoder for the orthogonal autoencoder.<br>rope_ae_resnet*.keras <- A single LSTM+Resnet model of the ROPE.<br>rope_oae_*.keras <- A single LSTM+ResNet model of the OAE<br>ROPE.</p> <p> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15225294 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | RAM-SCB Autoencoder and Dataset Al Shidi, Qusai Mehta, Piyush <p>ram_scb_autoencoder<br>==============================</p> <p>An autoencoder model for the RAM-SCB inner magnetosphere model.</p> <p>Project Organization<br>------------</p> <p> ├── README.md <- The top-level README for developers using this project.<br> ├── data<br> │ ├── processed <- The final, canonical data sets for modeling.<br> ├── models <- Trained and serialized models, model predictions, or model summaries<br> ├── src <- Source code for training and visualization</p> <p>Data<br>----</p> <p>dates_*.npy <- the datetime objects of the test,<br>validation and training datasets.<br>log_*.npy <- Inputs into the model (unscaled).<br>lstm_input*.npy <- Inputs into the lstm before sequencing.<br>*_enc.npy <- Data after encoding using the autoencoder.<br>*_enc_oae.npy <- Data after encoding using the orthogonal autoencoder.<br>rope_ae_* <- The outputs of the rope using autoencoder.<br>rope_oae_* <- The outputs of the rope using orthogonal autoencoder.</p> <p>Models<br>------</p> <p>autoencoder_bo_best.keras <- Autoencoder model.<br>autoencoder_ortho_decoder.keras <- Decoder for the orthogonal autoencoder.<br>autoencoder_ortho_encoder.keras <- Encoder for the orthogonal autoencoder.<br>rope_ae_resnet*.keras <- A single LSTM+Resnet model of the ROPE.<br>rope_oae_*.keras <- A single LSTM+ResNet model of the OAE<br>ROPE.</p> <p> </p> |
| title | RAM-SCB Autoencoder and Dataset |
| url | https://doi.org/10.5281/zenodo.15225294 |