1.链接一 C/DNN Explainer

CNN Explainerhttps://poloclub.github.io/cnn-explainer/

2.Scaling Deep Learning Interpretability by Visualizing Activation and Attribution

Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizationshttps://fredhohman.com/summit/

3.Interactively Deciphering Adversarial Attacks on Deep Neural Networks

Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networkshttps://poloclub.github.io/bluff/

4.Visual Analytics in Deep Learning

Visual Analytics in Deep Learning – Visual Analytics in Deep Learninghttps://fredhohman.com/visual-analytics-in-deep-learning/

 

5.GAN Lab

GAN Lab: Play with Generative Adversarial Networks in Your Browser!https://poloclub.github.io/ganlab/

6.Diffusion Explainer:

Diffusion Explainer: Stable Diffusion Explained with Visualizationhttps://poloclub.github.io/diffusion-explainer/

7.

Fred Hohman - ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentationhttps://fredhohman.com/papers/shapeshop

8.Exploring Transformer Models with Interactive Visualization

Dodriohttps://poloclub.github.io/dodrio/

 

 9.Facebook Deep Neural Network Models

ActiVishttps://minsuk.com/research/activis/