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README.md
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- [Masked Autoencoder](https://openaccess.thecvf.com/content/CVPR2022/papers/He_Masked_Autoencoders_Are_Scalable_Vision_Learners_CVPR_2022_paper.pdf)
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- Gene-Program Masked Autoencoder
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Training details and adaptations to single-cell data in our project can be found in our paper below. To use the model directly, the same genes must be used in the same order as in the `var.parquet` file. Otherwise, follow the instructions from the repositories below to train a model for custom datasets.
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If you find our work useful, please cite the following paper:
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- [Masked Autoencoder](https://openaccess.thecvf.com/content/CVPR2022/papers/He_Masked_Autoencoders_Are_Scalable_Vision_Learners_CVPR_2022_paper.pdf)
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- Gene-Program Masked Autoencoder
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Finetuned models for the downstream tasks of:
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- Cell Type Prediction
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- Gene Expression Reconstruction
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- Cross-Modality Prediction (RNA->Proteomics)
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- Data Integration
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Training details and adaptations to single-cell data in our project can be found in our paper below. To use the model directly, the same genes must be used in the same order as in the `var.parquet` file. Otherwise, follow the instructions from the repositories below to train a model for custom datasets.
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If you find our work useful, please cite the following paper:
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