Pangaea extracts k-mer histograms and tetra-nucleotide frequencies (TNFs; Methods) of co-barcoded reads and represents them in low-dimensional latent space by Variational Autoencoder (VAE; Methods; Supplementary
We present a novel approach for analyzing financial time series data using a Long Short-Term Memory Autoencoder (LSTMAE), a deep learning method. Our primary objective is to uncover intricate relationships among different stock indices, leading to the ex
2.2 Attention-based Encoder-Decoder Networks An encoder-decoder is a popular framework in deep learning, especially in sequence-to-sequence modelling. The key idea is to encode the input sequences into the hidden state sequence and then the hidden state sequence is converted into a fix-length ve...
Operational flood control systems depend on reliable and accurate forecasts with a suitable lead time to take necessary actions against flooding. This study proposed a Long Short-Term Memory based Encoder-Decoder (LSTM-ED) model for multi-step-ahead flood forecasting for the first time. The Shihme...
We present a novel approach for analyzing financial time series data using a Long Short-Term Memory Autoencoder (LSTMAE), a deep learning method. Our primary objective is to uncover intricate relationships among different stock indices, leading to the ex
The second group are methods based on machine learning, such as first-order neural ordinary differential equations (ODEs), encoder–decoder LSTM, physics-constrained and artificial neural networks (PC+ANN), or artificial neural networks methods (ANN). The last group consists of other, more unique...
salt - Salt that is used by hashid encoder/decoder, should be constant and shared across all nodes in the cluster. Do not change this parameter once used in production, or you will have collisions in the alphanumeric IDs. Good way to generate salt on Linux: dd if=/dev/random bs=1 co...
this authToken, followed by the object that this authToken is meant to shared, followed by if it's locked, then a dispatch function responsible for this authToken (many authTokens might have the same dispatcher responsible for it), followed by an optional encoder and decoder for custom ...
In addition, when the transformer is used for time series data prediction, the self-attention mechanism of the decoder accumu- lates errors layer by layer. Chaos can easily be generated, and the prediction effect in many cases is even worse than that of replacing the decoder part with a ...
25 applied deep learning to irregular and regularly missing data reconstruction. They developed a model structure based on an encoder-decoder U-Net convolutional neural network, using randomly sampled data as input and corresponding complete data as output. The training data consisted of carefully ...