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Found 5 papers, 3 papers with code
Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask
Time Series Representation Learning (TSRL) focuses on generating informative representations for various Time Series (TS) modeling tasks.
DISCOUNT: Distributional Counterfactual Explanation With Optimal Transport
This paper extends the concept of CEs to a distributional context, broadening the scope from individual data points to entire input and output distributions, named Distributional Counterfactual Explanation (DCE).
SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
This study addresses the challenge of inaccurate gradients in computing the empirical Fisher Information Matrix during neural network pruning.
Weighted Sum-Rate Maximization With Causal Inference for Latent Interference Estimation
Specifically, with the possibility of power policy shifting in the hidden network, computing an iterating direction based only on the observed interference inherently implies that counterfactual is ignored in decision making.
Gaussian Mixture Model Based Distributionally Robust Optimal Power Flow With CVaR Constraints
This paper proposes a distributionally robust optimal power flow (OPF) model for transmission grids with wind power generation.
