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Found 3 papers, 2 papers with code
Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model
Current state-of-the-art diffusion models employ U-Net architectures containing convolutional and (qkv) self-attention layers.
Rotation and Translation Invariant Representation Learning with Implicit Neural Representations
In many computer vision applications, images are acquired with arbitrary or random rotations and translations, and in such setups, it is desirable to obtain semantic representations disentangled from the image orientation.
Neural Tangent Kernel Analysis of Deep Narrow Neural Networks
The tremendous recent progress in analyzing the training dynamics of overparameterized neural networks has primarily focused on wide networks and therefore does not sufficiently address the role of depth in deep learning.
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