MMD, Kernel Trick and Deep Learning

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Lecture on Maximum Mean Discrepancy (MMD)

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Kernel Methods, part 2 - Arthur Gretton - MLSS 2020, Tübingen

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Maximum Mean Discrepancy Kernels for Predictive and Prognostic Modeling of Whole Slide Images

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Arthur Gretton Kernel methods for comparing distributions and training generative models

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Lester Mackey: Kernel Thinning and Stein Thinning

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【ファイノン/Phainon】INTERGALACTIA【崩壊:スターレイルMMD】

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Lecture 8 of kernel methods: Kernel Mean Embeddings

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Neuvillette and Furina go to Liyue

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8.6 David Thompson (Part 6): Nonlinear Dimensionality Reduction: KPCA

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[MMD] Girls' Generation 소녀시대 - 'Run Devil Run' [Motion DL]

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Tutorial on Domain Adaptation

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MLSS 2019 David Blei: Variational Inference: Foundations and Innovations (Part 1)

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Big Data: Arthur Gretton-The Maximum Mean Discrepancy for Training Generative Adversarial Networks

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Earth Mover's Distance and Maximum Mean Discrepancy | Unsupervised Learning for Big Data

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[MMD] Stray Kids Walkin On Water - Leon Kennedy, Albert Wesker Jack Krauser kpop dance Resident Evil

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Maximum Mean Discrepancy @GAN

(19:58)

【MMD || Motion Commission】Hellfire - (Motion DL)

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Statistical Inference for Generative Models with Maximum Mean Discrepancy

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Lester Mackey | Advances in Distribution Compression

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Arthur Gretton - Training Generative Adversarial Networks with MMD Critic

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Two-Sample Tests, Integral Probability Metrics, and GAN Objective - Dougal J. Sutherland

(30:33)

MMD GAN

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Kernel-based Detection of Anomalous Structures over Large Networks

(49:39)

Comparing Manifold Data Distributions by Diffusion Kernels and Neural Networks, Xiuyuan Cheng@Duke

(59:17)

Aude Genevay: Bridging the gap between optimal transport and MMD with Sinkhorn divergences

(35:41)

A Kernel Two-Sample Test For Functional Data

(25:25)

Mikkel Lykkegaard - Derivative-Free Thinning (DaFT) with Stochastic Kernel Embeddings

(21:24)

Feng Liu, Learning Deep Kernels for Non-Parametric Two-Sample Tests

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