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Found 6 papers, 3 papers with code
Cross Attention Augmented Transducer Networks for Simultaneous Translation
This paper proposes a novel architecture, Cross Attention Augmented Transducer (CAAT), for simultaneous translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensing
Compared with widely used semantic segmentation networks, including SegNet, PSPNet, DeepLabV3+, UNet, and ResUnet, our proposed model CldNet with an accuracy of 80. 89+-2. 18% is state-of-the-art in identifying cloud types and has increased by 32%, 46%, 22%, 2%, and 39%, respectively.
Physics-constrained robust learning of open-form PDEs from limited and noisy data
The embedding phase integrates the initially identified PDE from the discovering process as a physical constraint into the predictive model for robust training.
DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning
The working mechanisms of complex natural systems tend to abide by concise and profound partial differential equations (PDEs).
Model-based Reinforcement Learning
reinforcement-learning
+1
AutoKE: An automatic knowledge embedding framework for scientific machine learning
Imposing physical constraints on neural networks as a method of knowledge embedding has achieved great progress in solving physical problems described by governing equations.
The USTC-NELSLIP Systems for Simultaneous Speech Translation Task at IWSLT 2021
This paper describes USTC-NELSLIP's submissions to the IWSLT2021 Simultaneous Speech Translation task.
