An evaluation metric for generative models using hierarchical clustering
Gustavo Sutter P. Carvalho
2020 Long Presentation
in
Affinity Workshop: LXAI Research @ NeurIPS 2020
in
Affinity Workshop: LXAI Research @ NeurIPS 2020
Abstract
We present a novel metric for generative modeling evaluation that uses divergence between dendrograms computed from training and generated data. Our approach, which borrows theoretical foundations from clustering analysis, is validated by sampling from real datasets and also on samples generated by a GAN during training, with results comparable to state-of-the-art metrics.
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