Mode collapse
In machine learning, mode collapse is a failure mode observed in generative models, originally noted in Generative Adversarial Networks (GANs). It occurs when the model produces outputs that are less diverse than expected, effectively "collapsing" to generate only a few modes of the data distribution while ignoring others. This phenomenon undermines the goal of generative models to capture the full diversity of the training data.
Mode collapse - Wikipedia Jump to content From Wikipedia, the free encyclopedia Failure of a generative model to generate diverse samples Not to be confused with Model collapse . In machine learning , mode collapse is a failure mode observed in generative models , originally noted in Generative Adversarial Networks (GANs) . It occurs when the model produces outputs that are less diverse than expected, effectively "collapsing" to generate only a few modes of the data distribution while ignoring others. This phenomenon undermines the goal of generative models to capture the full diversity of the
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