Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layers
-
Updated
Sep 9, 2024 - Python
Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layers
Deepfakes with an adversarial twist.
Code for Spectral Norm of Convolutional Layers with Circular and Zero Paddings and Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration
PyTorch Implementation of the CLIP Algorithm
A Wasserstein Generative Adversarial Network that learns the distribution of a Mixture of Gaussian, using weight clipping or spectral normalization
Add a description, image, and links to the lipschitz-regularization topic page so that developers can more easily learn about it.
To associate your repository with the lipschitz-regularization topic, visit your repo's landing page and select "manage topics."