TransMorph is a deep learning method for medical image registration that uses Swin Transformer architecture to learn deformation fields between medical images without supervision. The model achieved state-of-the-art results on the MICCAI 2021 Learn2Reg challenge for brain MR registration. The implementation includes Bayesian deep learning components for uncertainty quantification and diffeomorphism constraints for smooth deformations.