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Found 3 papers, 3 papers with code
SwitchTab: Switched Autoencoders Are Effective Tabular Learners
Self-supervised representation learning methods have achieved significant success in computer vision and natural language processing, where data samples exhibit explicit spatial or semantic dependencies.
Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification
Deep learning models achieve state-of-the art results in predicting blood glucose trajectories, with a wide range of architectures being proposed.
Machine learning approach to force reconstruction in photoelastic materials
Photoelastic techniques have a long tradition in both qualitative and quantitative analysis of the stresses in granular materials.
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