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A Comparative Study of Sparsity Promoting Techniques in Neural Network for Modeling Non-Linear Dynamics., , , , and . IEEE Access, (2023)Deep neural network enabled corrective source term approach to hybrid analysis and modeling., , , and . CoRR, (2021)Physics guided neural networks for modelling of non-linear dynamics., , , and . Neural Networks, (2022)On the effectiveness of signal decomposition, feature extraction and selection on lung sound classification., , , and . CoRR, (2020)A non-intrusive reduced order modeling framework for quasi-geostrophic turbulence., , , , and . CoRR, (2019)Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution., , and . CoRR, (2021)Sparse deep neural networks for modeling aluminum electrolysis dynamics., , , and . Appl. Soft Comput., (February 2023)Computationally and Memory-Efficient Robust Predictive Analytics Using Big Data., and . CoRR, (2024)Data-driven recovery of hidden physics in reduced order modeling of fluid flows, , , and . Physics of Fluids, 32 (3): 036602-- (March 2020)Comparing Deep Reinforcement Learning Algorithms' Ability to Safely Navigate Challenging Waters., , , , and . Frontiers Robotics AI, (2021)