a)Deep Unsupervised Learning using Nonequilibrium Thermodynamics
b)Attention U-Net: Learning Where to Look for the Pancreas
c)SAGAN: Self-Attention Generative Adversarial Networks
d)BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis
e)Pre-Norm Transformers: On Layer Normalization in the Transformer Architecture
f)DDIM: DENOISING DIFFUSION IMPLICIT MODELS
g)ViT: An Image Is Worth 16X16 Words: Transformers For Image Recognition At Scale
h)IDDPM: Improved Denoising Diffusion Probabilistic Models
i)DDPM: Denoising Diffusion Probabilistic Models
j)Diffusion Models Beat GANs on Image Synthesis
k)GroupNorm: Group Normalization
l)EMA: Weight-averaged consistency targets improve semi-supervised deep learning results
m)CFG: Classifier-Fredd Diffusion Guidance
Student model: https://drive.google.com/file/d/1Ov23itCd3s2dGu7PZeMnz6gK-vtOVpA5/view?usp=share_link
Teacher model: https://drive.google.com/file/d/1EqP4qJkVt3abh0Vzxr-tDwh7zYymwLT9/view?usp=share_link
Use this link to the google colab for inference or download Diffusion_CIFAR10_Inference.ipynb. Download the model before inference
https://colab.research.google.com/drive/1es0CeqwReIfRxv-oJcAKtHNgZiR_N-qR?usp=sharing