Comparative Analysis of Liquid Neural Networks and LSTM for Sequential Pattern Recognition: Robustness, Efficiency, and Clinical Utility

In three linesComparative study of Liquid Neural Networks (LNN/CfC) vs LSTM across four sequential modalities (N-MNIST, QuickDraw, IAM, PhysioNet Sepsis-3). LNNs model hidden state evolution as continuous differential equations. Results: LNNs outperform LSTM in parameter efficiency and robustness to missing data, especially in clinical environments.

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