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Nested Sampling: A Critical and Comprehensive Theoretical Guide

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arXiv:2606. 17916v1 Announce Type: cross Abstract: The nested sampling (NS) technique has gained widespread attention, particularly in cosmology and astronomy, due to its ability to efficiently explore high-likelihood regions - a feature akin to an implicit likelihood optimization that underlies its success.

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Authors: Luca Martino, Fernando Llorente
Released: 2026-06-17 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Nested Sampling: A Critical and Comprehensive Theoretical Guide overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", experiment "Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe", experiment "Follow-up to #354: cascading chunk-binding — does A→B, B→C, C→D propagate the full chain on a recipient trained only to emit A?". Matching terms: under, implement, full, trained, position. Source: arxiv stat.ML (Machine Learning).
arXiv: 2606.17916

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