Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
This academic paper explores the mathematical unification of decision trees and diffusion models. It provides a theoretical framework for bridging traditional machine learning structures with modern generative modeling techniques.
Why it matters
It represents a significant theoretical advancement in machine learning, potentially leading to more efficient or interpretable generative AI architectures.
Focus to learn more arXiv-issued DOI via DataCite Submission history From: Sai Niranjan Ramachandran [ view email ] [v1] Fri, 1 May 2026 05:19:54 UTC (8,277 KB) [v2] Thu, 21 May 2026 04:49:57 UTC (8,277 KB) Full-text links: Access Paper: View a PDF of the paper titled Trees to Flows and Back: Unifying Decision Trees and Diffusion Models, by Sai Niranjan Ramachandran and Suvrit Sra View PDF TeX Source view license Current browse context: cs.LG < prev | next > new | recent | 2026-05 Change to browse by: cond-mat cond-mat.stat-mech cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) IArxiv recommender toggle IArxiv Recommender ( What is IArxiv? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
The content is a technical abstract from an academic repository with no political or social commentary.
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