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Found 5 papers, 1 papers with code
BSSAD: Towards A Novel Bayesian State-Space Approach for Anomaly Detection in Multivariate Time Series
The design of our approach combines the strength of Bayesian state-space algorithms in predicting the next state and the effectiveness of recurrent neural networks and autoencoders in understanding the relationship between the data to achieve high accuracy in detecting anomalies.
WaveNets: Wavelet Channel Attention Networks
Next, we test wavelet transform as a standalone channel compression method.
GHM Wavelet Transform for Deep Image Super Resolution
All single-level wavelets report similar results indicating that the convolutional neural network is invariant to choice of wavelet in a single-level filter approach.
Neighborhood Random Walk Graph Sampling for Regularized Bayesian Graph Convolutional Neural Networks
The Graph Neural Network (GNN) has proven to be a very useful tool in a variety of graph learning tasks including node classification, link prediction, and edge classification.
A Comparative Study of Transformer-Based Language Models on Extractive Question Answering
Question Answering (QA) is a task in natural language processing that has seen considerable growth after the advent of transformers.
