Attitude deviation prediction of shield tunneling machine using Time-Aware LSTM networks

Dropout: a simple way to prevent neural networks from overfitting

Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky et al. · 2014 · 34.3K citations

Computing, Computer Science, Artificial Intelligence +12

Learning long-term dependencies with gradient descent is difficult

Yoshua Bengio, P. Simard, Paolo Frasconi · IEEE Transactions on Neural Networks · 1994 · 8.5K citations

Computing, Computer Science, Machine Learning +9

Patient Subtyping via Time-Aware LSTM Networks

İnci M. Baytaş, Cao Xiao, Xi Zhang et al. · 2017 · 634 citations

Computing, Biomedical Informatics, Health Informatics +15

Neural Networks in Civil Engineering. I: Principles and Understanding

Ian Flood, Nabil Kartam · Journal of Computing in Civil Engineering · 1994 · 582 citations

Computing, Civil Engineering, Computer Science +12

Dynamic prediction for attitude and position in shield tunneling: A deep learning method

Cheng Zhou, Xu Hengcheng, Lieyun Ding et al. · Automation in Construction · 2019 · 190 citations

Computing, Computational Engineering, Computer Science +10