Beyond Distance: Quantifying Point Cloud Dynamics with Persistent Homology and Dynamic Optimal Transport
arXiv 2603.15683•4030cd4457c84e44d50831d83a0a5d491c617c380717d284b8fe34be72c046af
Lipschitz optimization (HALO)adaptive design of experimentsconditional distributional effectscovariate shiftdeep adaptive designdistributional robustnessdoubly robust estimationentropy metricsfeature selectionglobal optimizationhypergraphshypothesis testingk-NNnon-orthogonal embeddingsoptimal transportpartial-label learningpermutation-free testspersistent homologypoint cloudsrepresentation learningsafe screeningsparse sensingtopological data analysistransformer policytransformers
Paper metadata
- arXiv ID
- 2603.15683
- 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
- 4030cd4457c84e44d50831d83a0a5d491c617c380717d284b8fe34be72c046af
- Enrichment time
- 2026-03-18T07:23:57Z
- AI-assisted enrichment
- Yes
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