Quantitative Target Convergence and Uniform-in-Time Propagation of Chaos for Langevin-Regularized SVGD
arXiv 2608.28827•e00429f88278041d965a07998f4d78d9b01e6a0fb713f635548e303c9033766d
arXivcausal-representation-learningdistribution-shiftfairnessmachine-learning-researchnon-securityoptimal-transportresearch-feedstatistical-machine-learning
Paper metadata
- arXiv ID
- 2608.28827
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
The PDF link points to arxiv.org. Baitaphish does not expose a private stored PDF.
Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- e00429f88278041d965a07998f4d78d9b01e6a0fb713f635548e303c9033766d
- Enrichment time
- 2026-09-01T07:23:49Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.