Counterfactual Explanations for Deep Two-Sample Testing
arXiv 2606.04009•aa31048720c624be8595eb15f92acb04eb864f0fa72bc0b55c06af33b637a72d
Expected-ShortfallMRI-analysisValue-at-Riskalternating-power-iterationautoencodersbayesian-reinforcement-learningcounterfactual-explanationscoupled-gradient-descentdeep-learningdiffusion-autoencoderfalse-discovery-ratefeature-selectionfinancial-riskflatness-generalizationforecast-reconciliationhomogeneous-networksknockoffsmachine-learningmaximum-mean-discrepancyoptimization-theorypseudospectral-analysis","anomaly-detection","time-series-anomalstatistical-testingstochastic-shortest-pathtensor-PCAtime-series-forecasting
Paper metadata
- arXiv ID
- 2606.04009
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- aa31048720c624be8595eb15f92acb04eb864f0fa72bc0b55c06af33b637a72d
- Enrichment time
- 2026-06-04T07:24:02Z
- AI-assisted enrichment
- Yes
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