A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...
Abstract: Autoencoders gained popularity in the deep learning revolution given their ability to compress data and provide dimensionality reduction. Although prominent deep learning methods have been ...
Abstract: Image translation with convolutional autoencoders has recently been used as an approach to multimodal change detection (CD) in bitemporal satellite images. A main challenge is the alignment ...
The encoder part of CrossMAE matches exactly with MAE. Therefore, we use the same code for fine-tuning. We also encourage you to try CrossMAE checkpoints in your downstream applications. These models ...
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