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PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems.

, , , , and . ACSSC, page 2219-2223. IEEE, (2019)

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Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors., , and . TAG-ML, volume 196 of Proceedings of Machine Learning Research, page 161-171. PMLR, (2022)Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples., , and . UAI, volume 124 of Proceedings of Machine Learning Research, page 350-359. AUAI Press, (2020)Random Walks, Conductance, and Resistance for the Connection Graph Laplacian., , , , , and . SIAM J. Matrix Anal. Appl., 45 (3): 1541-1572 (2024)Operator analysis and diffusion based embeddings for heterogeneous data fusion., , and . IGARSS, page 1249-1252. IEEE, (2014)PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems., , , , and . ACSSC, page 2219-2223. IEEE, (2019)Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders., , , , and . CoRR, (2022)Diffusion Nets., , , and . CoRR, (2015)All You Need is Resistance: On the Equivalence of Effective Resistance and Certain Optimal Transport Problems on Graphs., , and . CoRR, (2024)Diffusion Variational Autoencoders., , , and . CoRR, (2019)Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems., , , , and . CoRR, (2024)