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Found 4 papers, 2 papers with code
GPN: A Joint Structural Learning Framework for Graph Neural Networks
To the best of our knowledge, our method is the first GNN-based bilevel optimization framework for resolving this task.
Adversarial Sparse Transformer for Time Series Forecasting
Specifically, AST adopts a Sparse Transformer as the generator to learn a sparse attention map for time series forecasting, and uses a discriminator to improve the prediction performance from sequence level.
Multivariate Time Series Forecasting
Probabilistic Time Series Forecasting
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RetroXpert: Decompose Retrosynthesis Prediction like a Chemist
Retrosynthesis is the process of recursively decomposing target molecules into available building blocks.
Adaptive Regularization of Labels
In addition, label regularization techniques such as label smoothing and label disturbance have also been proposed with the motivation of adding a stochastic perturbation to labels.
