Scalable Manifold-Regularized Attributed Network Embedding via Maximum Mean Discrepancy
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Updated
May 21, 2021 - Python
Scalable Manifold-Regularized Attributed Network Embedding via Maximum Mean Discrepancy
multi-kernel maximum mean discrepancy
Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"
Maximum Mean Discrepancy (MMD), Kernel Stein Discrepancy (KSD), and Fisher Divergence
Maximum mean discrepancy comparisons for single cell profiling experiments
Fast Inference in Denoising Diffusion Models via MMD Finetuning
Implicit generative models and related stuff based on the MMD, in PyTorch
Chapter 11: Transfer Learning/Domain Adaptation
Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)
MXNet Code For Demystifying Neural Style Transfer (IJCAI 2017)
Improving MMD-GAN training with repulsive loss function
Can We Find Strong Lottery Tickets in Generative Models? - Official Code (Pytorch)
MMD-GAN: Towards Deeper Understanding of Moment Matching Network
Learning kernels to maximize the power of MMD tests
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