Learning kernels to maximize the power of MMD tests

MMD-GAN: Towards Deeper Understanding of Moment Matching Network

Can We Find Strong Lottery Tickets in Generative Models? - Official Code (Pytorch)

Improving MMD-GAN training with repulsive loss function

MXNet Code For Demystifying Neural Style Transfer (IJCAI 2017)

Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)

Maximum mean discrepancy comparisons for single cell profiling experiments

Fast Inference in Denoising Diffusion Models via MMD Finetuning

Chapter 11: Transfer Learning/Domain Adaptation

Maximum Mean Discrepancy (MMD), Kernel Stein Discrepancy (KSD), and Fisher Divergence

Implicit generative models and related stuff based on the MMD, in PyTorch

[NeurIPS'25] Sequence Modeling with Spectral Mean Flows, in PyTorch

Official PyTorch implementation of JASA paper "Word-Level Maximum Mean Discrepancy Regularization for Word Embedding"

multi-kernel maximum mean discrepancy

Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"

Compute Maximum Mean Discrepancy in R

Enhancing GAN Performance Through Neural Architecture Search and Tensor Decomposition

Pytorch implementation of 'Nonlinear Concept Erasure: A Density Matching Approach' (Saillenfest & Lemberger, 2025), Proceedings of ECAI 2025 - 28th European conference on AI

Framework using UMAP-DBSCAN for unsupervised discovery of multi-modal Hidden Bias Subgroups (HBSs) in AI failure spaces. Implements a scalable Multi-Domain MMD Objective to mitigate latent Acquisition Bias and enhance robustness in clinical Ocular Disease Recognition (ODR).