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Found 3 papers, 2 papers with code
Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
Transformer-based architectures achieved breakthrough performance in natural language processing and computer vision, yet they remain inferior to simpler linear baselines in multivariate long-term forecasting.
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift
Our key idea is that the model should be adjusted with a higher magnitude of gradients when it does not generalize to the test dataset with a distribution shift.
Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias
Self-training is a well-known approach for semi-supervised learning.
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