DeepIFSAC combines feature and sample attention with CutMix augmentation and contrastive learning to impute missing tabular values, ranking first on average against 11 baselines in extensive benchmarks.
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DeepIFSAC: Deep Imputation of Missing Values Using Feature and Sample Attention within Contrastive Framework
DeepIFSAC combines feature and sample attention with CutMix augmentation and contrastive learning to impute missing tabular values, ranking first on average against 11 baselines in extensive benchmarks.