GitHub - Bio-MingChen/DL_test: recording the code for learning deep learning by using pytorch

Introduction

On the other hand, I also collected GAN and AAE(Adversarial Autoencoder) code

In the following time, I am going to learn transformer structure and its application in single clel omics and spatial omics

Name		Name	Last commit message	Last commit date
Latest commit History 22 Commits
data		data
images		images
lightning_logs		lightning_logs
.gitignore		.gitignore
Adversarial_Autoencoder.ipynb		Adversarial_Autoencoder.ipynb
Contrastive_Learning.ipynb		Contrastive_Learning.ipynb
GAN_tutorial.ipynb		GAN_tutorial.ipynb
GNN_test.ipynb		GNN_test.ipynb
ML_test1_20250106.ipynb		ML_test1_20250106.ipynb
README.md		README.md
SIMS_transform_based_classifier_code_learning.ipynb		SIMS_transform_based_classifier_code_learning.ipynb
STRAFE_Transformer.ipynb		STRAFE_Transformer.ipynb
TIGON_AE_code_learning.ipynb		TIGON_AE_code_learning.ipynb
Transformer_test.ipynb		Transformer_test.ipynb
VAE_implementation.ipynb		VAE_implementation.ipynb
image-1.png		image-1.png
image-2.png		image-2.png
image-3.png		image-3.png
image.png		image.png
limu_deeplearning.ipynb		limu_deeplearning.ipynb
pyTorch_test2_20250111.ipynb		pyTorch_test2_20250111.ipynb
pyTorch_test3_CNN_20250111.ipynb		pyTorch_test3_CNN_20250111.ipynb
pyTorch_test_autoencoder.ipynb		pyTorch_test_autoencoder.ipynb
pytorch_official_tutorial.ipynb		pytorch_official_tutorial.ipynb
pytorch_official_tutorial2.ipynb		pytorch_official_tutorial2.ipynb
pytorch_tutorial1.ipynb		pytorch_tutorial1.ipynb
pytorch_tutorial2.ipynb		pytorch_tutorial2.ipynb
pytorch_tutorial3.ipynb		pytorch_tutorial3.ipynb
tensorboard_test.py		tensorboard_test.py