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GitHub6mon
QAZalo/module_train/basic_model/model_architecture_dl/model_one_sequence_learning.py at master · trangtv57/QAZalo - GitHub
from module_train.basic_model.model_architecture_dl.sub_layer.cnn_feature_extract import CNNFeatureExtract1D, CNNFeatureExtract2D from ...
GitHub6mon
GitHub - aktasumitt/Sequence-to-Sequence_Model: I create sequence to sequence model with Bahdanau attention and custom sequnce dataset.
In this project, I aimed to train a seq2seq model using basic Encoder-Decoder architecture with Bahdanau Attention and with custom sequence Dataset. You can train the model by setting Just "TRAIN" to ...
IEEE6y
A Sequence-to-Sequence Deep Learning Architecture Based on Bidirectional GRU for Type Recognition and Time Location of Combined Power Quality Disturbance - IEEE Xplore
In this paper, a sequence-to-sequence deep learning architecture based on the bidirectional gated recurrent unit (Bi-GRU) for type recognition and time location of combined power quality disturbance ...
marktechpost1y
Megalodon: A Deep Learning Architecture for Efficient Sequence Modeling with Unlimited Context Length - MarkTechPost
Researchers from Meta, the University of Southern California, Carnegie Mellon University, and the University of California San Diego have introduced MEGALODON, a model designed to efficiently handle ...
IEEE6y
A Sequence-to-Sequence Deep Learning Architecture Based on Bidirectional GRU for Type Recognition and Time Location of Combined Power Quality Disturbance
In this paper, a sequence-to-sequence deep learning architecture based on the bidirectional gated recurrent unit (Bi-GRU) for type recognition and time location of combined power quality disturbance ...