A Simpson Based Estimation Approach for the Overlapping Coefficient of k>=2 Normal Distributions https://arxiv.org/abs/2603.02282 #stat.ME
Topological Causal Effects https://arxiv.org/abs/2603.02289 #stat.ME #stat.ML #cs.LG
Implications of the Pessimistic Lower Limit on the Drake Equation https://arxiv.org/abs/2603.02372 #physics.space-ph #physics.pop-ph #stat.OT #stat.AP
Fisher-Geometric Diffusion in Stochastic Gradient Descent: Optimal Rates, Oracle Complexity, and Information-Theoretic Limits https://arxiv.org/abs/2603.02417 #stat.ML #math.OC #cs.LG
Contributions of geolocated weather and building related data for insurance assessment of flood risks https://arxiv.org/abs/2603.02418 #stat.AP
On the misuse of time-dependent models in assessing mask usage and excess mortality https://arxiv.org/abs/2603.02424 #stat.AP
Leveraging Sparsity to Improve No-U-Turn Sampling Efficiency for Hierarchical Bayesian Models https://arxiv.org/abs/2603.02437 #stat.CO #stat.ME
Conformal Graph Prediction with Z-Gromov Wasserstein Distances https://arxiv.org/abs/2603.02460 #stat.ML #cs.LG
CCMnet: A Software Package for Network Generation with Congruence Class Models https://arxiv.org/abs/2603.02467 #stat.CO
Transportable inference using target population summary statistics under covariate shift https://arxiv.org/abs/2603.02474 #stat.ME
How to recover a permutation group amidst errors https://arxiv.org/abs/2602.23505 #math.ST #math.GR #stat.TH
Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary-Variable-Guided Generative Models https://arxiv.org/abs/2602.23518 #stat.ML #cs.LG
Partition Function Estimation under Bounded f-Divergence https://arxiv.org/abs/2602.23535 #stat.ML #cs.LG
Moment Matters: Mean and Variance Causal Graph Discovery from Heteroscedastic Observational Data https://arxiv.org/abs/2602.23602 #stat.ML #cs.LG
Fairness under Graph Uncertainty: Achieving Interventional Fairness with Partially Known Causal Graphs over Clusters of Variables https://arxiv.org/abs/2602.23611 #stat.ML #cs.LG
Stress-Testing Assumptions: A Guide to Bayesian Sensitivity Analyses in Causal Inference https://arxiv.org/abs/2602.23640 #stat.ME
Predictive Hotspot Mapping for Data-driven Crime Prediction https://arxiv.org/abs/2602.23750 #stat.AP #cs.LG
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