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We present the formalization of Doob's martingale convergence theorems in the mathlib library for the Lean theorem prover. These theorems give conditions under which (sub)martingales converge, almost everywhere or in $L^1$. In order to…

Logic in Computer Science · Computer Science 2022-12-13 Kexing Ying , Rémy Degenne

This article is about the formalization of synthetic differential geometry with the Lean proof assistant and the mathematical library mathlib. The main result we prove and formalize is a Taylor theorem for functions of several variables,…

Logic in Computer Science · Computer Science 2026-04-01 Riccardo Brasca , Gabriella Clemente

There is a scalability gap between probabilistic and non-probabilistic verification. Probabilistic model checking tools are based either on explicit engines or on (Multi-Terminal) Binary Decision Diagrams. These structures are complemented…

Logic in Computer Science · Computer Science 2019-09-20 Elizabeth Polgreen , Martin Brain , Martin Fraenzle , Alessandro Abate

This paper presents a formalisation of pGCL in Isabelle/HOL. Using a shallow embedding, we demonstrate close integration with existing automation support. We demonstrate the facility with which the model can be extended to incorporate…

Logic in Computer Science · Computer Science 2012-11-28 David Cock

In this work, we present two results: The first result is the formalization of Tutte's theorem in Lean, a key theorem concerning matchings in graph theory. As this formalization is ready to be integrated in Lean's mathlib, it provides a…

Logic in Computer Science · Computer Science 2025-04-28 Pim Otte

The continuous functional calculus is perhaps the most fundamental construction in the theory of operator algebras, especially $C^{*}$-algebras. Here we document our formalization of the continuous functional calculus in Lean, which…

Operator Algebras · Mathematics 2025-01-28 Anatole Dedecker , Jireh Loreaux

This paper describes mathlib, a community-driven effort to build a unified library of mathematics formalized in the Lean proof assistant. Among proof assistant libraries, it is distinguished by its dependently typed foundations, focus on…

Logic in Computer Science · Computer Science 2020-01-28 The mathlib Community

Verifying mathematical proofs is difficult, but can be automated with the assistance of a computer. Autoformalization is the task of automatically translating natural language mathematics into a formal language that can be verified by a…

Computation and Language · Computer Science 2024-07-11 Nilay Patel , Rahul Saha , Jeffrey Flanigan

We formalize Hall's Marriage Theorem in the Lean theorem prover for inclusion in mathlib, which is a community-driven effort to build a unified mathematics library for Lean. One goal of the mathlib project is to contain all of the topics of…

Combinatorics · Mathematics 2021-01-05 Alena Gusakov , Bhavik Mehta , Kyle A. Miller

We describe a proof of the Central Limit Theorem that has been formally verified in the Isabelle proof assistant. Our formalization builds upon and extends Isabelle's libraries for analysis and measure-theoretic probability. The proof of…

Mathematical Software · Computer Science 2017-02-02 Jeremy Avigad , Johannes Hölzl , Luke Serafin

How difficult are interactive theorem provers to use? We respond by reviewing the formalization of Hilbert's tenth problem in Isabelle/HOL carried out by an undergraduate research group at Jacobs University Bremen. We argue that, as…

Logic in Computer Science · Computer Science 2021-06-24 Jonas Bayer , Marco David , Abhik Pal , Benedikt Stock

This article presents a Bayesian inferential method where the likelihood for a model is unknown but where data can easily be simulated from the model. We discretize simulated (continuous) data to estimate the implicit likelihood in a…

The aim of this note is to construct a probability measure on the space of trajectories in a continuous time Markov chain having a finite state diagram, or more generally which admits a global bound on its degree and rates. Our approach is…

Probability · Mathematics 2021-05-25 Michael J. Catanzaro , Vladimir Y. Chernyak , John R. Klein

We report on a formalization of the change of variables formula in integrals, in the mathlib library for Lean. Our version of this theorem is extremely general, and builds on developments in linear algebra, analysis, measure theory and…

Logic in Computer Science · Computer Science 2022-07-27 Sébastien Gouëzel

We study the induced measure obtained from a 1-step Markov measure, supported by a topological Markov chain, after the mapping of the original alphabet onto another one. We give sufficient conditions for the induced measure to be a Gibbs…

Dynamical Systems · Mathematics 2007-05-23 J. -R. Chazottes , E. Ugalde

A celebrated result by A. Ionescu Tulcea provides a construction of a probability measure on a product space given a sequence of regular conditional probabilities. We study how the perturbations of the latter in the total variation metric…

Probability · Mathematics 2014-07-23 Alessandro Abate , Frank Redig , Ilya Tkachev

We formally verify an algorithm for approximate policy iteration on Factored Markov Decision Processes using the interactive theorem prover Isabelle/HOL. Next, we show how the formalized algorithm can be refined to an executable, verified…

Artificial Intelligence · Computer Science 2024-06-12 Maximilian Schäffeler , Mohammad Abdulaziz

Verification of infinite-state Markov chains is still a challenge despite several fruitful numerical or statistical approaches. For decisive Markov chains, there is a simple numerical algorithm that frames the reachability probability as…

Logic in Computer Science · Computer Science 2024-09-30 Benoît Barbot , Patricia Bouyer , Serge Haddad

The paper offers a mathematical formalization of the Turing test. This formalization makes it possible to establish the conditions under which some Turing machine will pass the Turing test and the conditions under which every Turing machine…

Artificial Intelligence · Computer Science 2010-05-28 Evgeny Chutchev

Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounded by the ease with which they can be probed analytically.…

Machine Learning · Computer Science 2023-12-18 Eddie Seabrook , Laurenz Wiskott
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