1a and b, due to previously reported good performance with scattering problems47. The model is trained for 5 × 105 epochs using the ADAM optimizer50 with a learning rate set to 5 × 10−4. The final residual of the fields predicted by the neural network are of the order of...
2. Related Work Deep external learning for CSR Supervised methods use an external dataset to train a deep NN for CSR, with a focus on architecture design. One popular design is the physics- aware CNNs that incorporate CS models via deep unrolling, often implemented b...
Experimental results show consistent improvements on classification tasks and promising results on reinforcement learning tasks. Furthermore, we observe faster convergence rates of the meta-training process. Finally, we present an analysis that explains better generalization performance with the meta-trained ...
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