| # Masked Autoencoders are Scalable Learners of Cellular Morphology | |
| Official repo for Recursion's two recently accepted papers: | |
| - Spotlight full-length paper at [CVPR 2024](https://cvpr.thecvf.com/Conferences/2024/AcceptedPapers) -- Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology | |
| - Paper: https://arxiv.org/abs/2404.10242 | |
| - CVPR poster page with video: https://cvpr.thecvf.com/virtual/2024/poster/31565 | |
| - Spotlight workshop paper at [NeurIPS 2023 Generative AI & Biology workshop](https://openreview.net/group?id=NeurIPS.cc/2023/Workshop/GenBio) | |
| - Paper: https://arxiv.org/abs/2309.16064 | |
|  | |
| ## Provided code | |
| See the repo for ingredients required for defining our MAEs. Users seeking to re-implement training will need to stitch together the Encoder and Decoder modules according to their usecase. | |
| Furthermore the baseline Vision Transformer architecture backbone used in this work can be built with the following code snippet from Timm: | |
| ``` | |
| import timm.models.vision_transformer as vit | |
| def vit_base_patch16_256(**kwargs): | |
| default_kwargs = dict( | |
| img_size=256, | |
| in_chans=6, | |
| num_classes=0, | |
| fc_norm=None, | |
| class_token=True, | |
| drop_path_rate=0.1, | |
| init_values=0.0001, | |
| block_fn=vit.ParallelScalingBlock, | |
| qkv_bias=False, | |
| qk_norm=True, | |
| ) | |
| for k, v in kwargs.items(): | |
| default_kwargs[k] = v | |
| return vit.vit_base_patch16_224(**default_kwargs) | |
| ``` | |
| ## Provided models | |
| A publicly available model for research can be found via Nvidia's BioNemo platform, which handles inference and auto-scaling: https://www.rxrx.ai/phenom | |
| We have partnered with Nvidia to host a publicly-available smaller and more flexible version of the MAE phenomics foundation model, called Phenom-Beta. Interested parties can access it directly through the Nvidia BioNemo API: | |
| - https://blogs.nvidia.com/blog/drug-discovery-bionemo-generative-ai/ | |
| - https://www.youtube.com/watch?v=Gch6bX1toB0 | |