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# Model Card for Hierarchical VQ VAE model for analysis of imaging-based ST data

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Pretrained checkpoints trained on Vizgen oncology ST dataset. 

## Model Details

### Model Description

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- **Developed by:** Dig Vijay Kumar Yarlagadda
- **Model type:** VQ-VAE

### Model Sources [optional]

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- **Repository:** https://github.com/digvijayky/hier_vq_vae_st
- **Paper [optional]:** https://openaccess.thecvf.com/content/ICCV2023W/BIC/html/Yarlagadda_Discrete_Representation_Learning_for_Modeling_Imaging-Based_Spatial_Transcriptomics_Data_ICCVW_2023_paper.html

## Uses

Analysis of imaging-based spatial transcriptomics datasets such as MERFISH, SEQFISH and Xenium. 

### Direct Use

Analysis of Vizgen oncology dataset. 

### Downstream Use [optional]

Finetuning on any imaging-based ST data. 

### Out-of-Scope Use

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Analysis of spot-based ST data
Mapping of scRNA-seq to ST data

### Compute Infrastructure

Model is trained on 4 A100 GPUs. 

## Citation [optional]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**APA:**

If you use this checkpoint or model, please cite:

Dig Vijay Kumar Yarlagadda, Joan Massague, Christina S. Leslie. "Discrete Representation Learning for Modeling Imaging-based Spatial Transcriptomics Data". International Conference on Computer Vision, Bioimaging Computing workshop 2023. 