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GitHub1y
What is the difference between variable importance for the encoder and decoder in TFTExplainer? · Issue #2370 · unit8co/darts - GitHub
I am not completely sure from the documentation how to interpret the results of the TFTExplainer. When I pass a certain series to the explainer and plot variable selection, I get a graph of variable ...
NHK4y
8K 120-Hz Video Real-Time Encoder and Decoder | Broadcast Technology | NHK STRL - NHK | 日本放送協会
In this paper, we introduce the world’s first 8K 120-Hz video real-time encoder and decoder that complies with ARIB STD-B32 1) . We evaluated the coding efficiency and demonstrated that 8K 120 ...
IEEE6mon
FSAM: Fine-tuning SAM encoder and decoder for Medical Image Segmentation - IEEE Xplore
Recently, the Segment Anything Model (SAM), a large pre-training model, has achieved excellent results on natural image segmentation tasks and received extensive attention. However, SAM on medical ...
GitHub6y
Encoder-decoder networks: an autoencoder/GAN variant trained by comparing the latent representations of the original and generated inputs - GitHub
The encoder-decoder network works by encoding an input, X, into a vector E(X), decoding the vector back into the input space, D(E(X), then finally re-encoding the result back into a vector, E(D(E(X))) ...
IEEE2y
Revalidating the Encoder-Decoder Depths and Activation Function to Find Optimum Vanilla Transformer Model - IEEE Xplore
The initial transformer model has 6 stacks of identical encoder-decoder layers with an attention mechanism whose aim is to push limitations of common recurrent ... However, statistically, there is no ...
marktechpost1y
Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures - MarkTechPost
The encoder processes the input data to form a context, which the decoder then uses to produce the output. This architecture is common in both RNN-based and transformer-based models. Attention ...