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/