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Parallelizing Autoregressive Generation with Variational State Space Models
The MNIST and CIFAR datasets are used to evaluate the proposed Variational State Space Model (VSSM) for autoregressive generation. -
Split CIFAR
The dataset used in this paper for Continual Learning, Catastrophic Forgetting and PCA-OGD. -
Learning Multiple Layers of Features from Tiny Images
The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.
