<ul data-eligibleForWebStory="false"><li>mGRADE is a hybrid-memory system that combines a temporal 1D-convolution with learnable spacings and a minimal gated recurrent unit.</li><li>It aims to address the challenge of modeling short- and long-range dynamics on edge devices with tight memory constraints.</li><li>mGRADE effectively separates and preserves multi-scale temporal features, outperforming pure convolutional and recurrent models on various tasks.</li><li>The design of mGRADE allows for efficient memory usage, making it promising for memory-constrained multi-scale temporal processing at the edge.</li></ul>

mGRADE: Minimal Recurrent Gating Meets Delay Convolutions for Lightweight Sequence Modeling

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