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# Masked Autoencoders are Scalable Learners of Cellular Morphology
Official repo for Recursion's accepted spotlight 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
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)
```
Additional code will be released as the date of the workshop gets closer.
## Provided models
Stay tuned...
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