APA (7th ed.) Citation

Tandale, S. B., & Stoffel, M. (2023). Recurrent and convolutional neural networks in structural dynamics: A modified attention steered encoder–decoder architecture versus LSTM versus GRU versus TCN topologies to predict the response of shock wave-loaded plates. Computational mechanics, 72(4), 765-786. https://doi.org/10.1007/s00466-023-02317-8

Chicago Style (17th ed.) Citation

Tandale, Saurabh Balkrishna, and Marcus Stoffel. "Recurrent and Convolutional Neural Networks in Structural Dynamics: A Modified Attention Steered Encoder–decoder Architecture Versus LSTM Versus GRU Versus TCN Topologies to Predict the Response of Shock Wave-loaded Plates." Computational Mechanics 72, no. 4 (2023): 765-786. https://doi.org/10.1007/s00466-023-02317-8.

MLA (9th ed.) Citation

Tandale, Saurabh Balkrishna, and Marcus Stoffel. "Recurrent and Convolutional Neural Networks in Structural Dynamics: A Modified Attention Steered Encoder–decoder Architecture Versus LSTM Versus GRU Versus TCN Topologies to Predict the Response of Shock Wave-loaded Plates." Computational Mechanics, vol. 72, no. 4, 2023, pp. 765-786, https://doi.org/10.1007/s00466-023-02317-8.