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Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More
[article]
2021
arXiv
pre-print
Joint Energy-based Model (JEM) of Grathwohl et al. shows that a standard softmax classifier can be reinterpreted as an energy-based model (EBM) for the joint distribution p(x,y); the resulting model can be optimized to improve calibration, robustness, and out-of-distribution detection, while generating samples rivaling the quality of recent GAN-based approaches. However, the softmax classifier that JEM exploits is inherently discriminative and its latent feature space is not well formulated as
arXiv:2101.00122v4
fatcat:kpahcnlfljcercpuf6hkxfcnri