GEM-FI uses energy-gated evidential mixtures plus Fisher regularization to raise accuracy, calibration, and OOD detection on CIFAR benchmarks while keeping single-pass inference.
MNIST contains 60,000 training and 10,000 test grayscale images of size 28×28 , and CIFAR-10 consists of 50,000 training and 10,000 test RGB images of size 32×32
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GEM-FI: Gated Evidential Mixtures with Fisher Modulation
GEM-FI uses energy-gated evidential mixtures plus Fisher regularization to raise accuracy, calibration, and OOD detection on CIFAR benchmarks while keeping single-pass inference.