A shallow dense Transformer achieves uniform epsilon-approximation of alpha-Holder functions with O(epsilon^{-d/alpha}) parameters and near-minimax generalization error O(n^{-2alpha/(2alpha+d)} log n).
An image is worth 16x16 words: Transformers for image recognition at scale
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SpineContextResUNet achieves Dice scores of 88.17% on VerSe2020 and 88.13% on CTSpine1K while using ~1.7M parameters and running inference on commodity hardware with 8GB RAM.
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Learning Theory of Transformers: Local-to-Global Approximation via Softmax Partition of Unity
A shallow dense Transformer achieves uniform epsilon-approximation of alpha-Holder functions with O(epsilon^{-d/alpha}) parameters and near-minimax generalization error O(n^{-2alpha/(2alpha+d)} log n).
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SpineContextResUNet: A Computationally Efficient Residual UNet for Spine CT Segmentation
SpineContextResUNet achieves Dice scores of 88.17% on VerSe2020 and 88.13% on CTSpine1K while using ~1.7M parameters and running inference on commodity hardware with 8GB RAM.