{"slug": "an-introduction-to-bayesian-and-frequentist-simulation-based-inference-with", "title": "An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning", "summary": "A new paper on arXiv (submitted July 23, 2026) provides an overview of Bayesian and frequentist simulation-based inference (SBI) with machine learning, covering methods such as neural posterior estimation and neural likelihood estimation for parameter estimation, Empirical Bayes, and unfolding tasks. The authors also discuss validation of inference results and limitations of SBI with machine learning.", "body_md": "# Computer Science > Machine Learning\n\n[Submitted on 23 Jul 2026]\n\n# Title:An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning\n\n[View PDF](/pdf/2607.21702)\n\nAbstract:Simulation-based inference (SBI) with machine learning is an increasingly important tool for solving inverse problems in science and engineering, including parameter inference and the inversion of detector effects. We provide an overview of the Bayesian and frequentist statistical frameworks, describe how machine-learning-based SBI methods, such as neural posterior estimation and neural likelihood estimation, can be used for parameter estimation within these frameworks, and show that the same methods can also be applied to Empirical Bayes or unfolding tasks. We also discuss how to validate inference results and the limitations of SBI with machine learning.\n\n### Current browse context:\n\ncs.LG\n\nChange to browse by:\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))\nIArxiv Recommender\n\n*(*[What is IArxiv?](https://iarxiv.org/about))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/an-introduction-to-bayesian-and-frequentist-simulation-based-inference-with", "canonical_source": "https://arxiv.org/abs/2607.21702", "published_at": "2026-07-27 04:00:00+00:00", "updated_at": "2026-07-27 04:09:11.828530+00:00", "lang": "en", "topics": ["machine-learning", "artificial-intelligence", "neural-networks", "ai-research"], "entities": ["arXiv"], "alternates": {"html": "https://wpnews.pro/news/an-introduction-to-bayesian-and-frequentist-simulation-based-inference-with", "markdown": "https://wpnews.pro/news/an-introduction-to-bayesian-and-frequentist-simulation-based-inference-with.md", "text": "https://wpnews.pro/news/an-introduction-to-bayesian-and-frequentist-simulation-based-inference-with.txt", "jsonld": "https://wpnews.pro/news/an-introduction-to-bayesian-and-frequentist-simulation-based-inference-with.jsonld"}}