Label-efficient time series representation learning: A review
Label-efficient time series representation learning, which aims to learn effective
representations with limited labeled data, is crucial for deploying deep learning models in …
representations with limited labeled data, is crucial for deploying deep learning models in …
Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review
Cancer remains one of the most challenging diseases to treat in the medical field. Machine
learning has enabled in-depth analysis of rich multi-omics profiles and medical imaging for …
learning has enabled in-depth analysis of rich multi-omics profiles and medical imaging for …
Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics
Most sequencing-based spatial transcriptomics (ST) technologies do not achieve single-cell
resolution where each captured location (spot) may contain a mixture of cells from …
resolution where each captured location (spot) may contain a mixture of cells from …
Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models
S Meng, A Chen, C Wang, M Zheng… - 2024 4th …, 2024 - ieeexplore.ieee.org
Accurate exchange rate prediction is fundamental to financial stability and international
trade, positioning it as a critical focus in economic and financial research. Traditional …
trade, positioning it as a critical focus in economic and financial research. Traditional …