English
Related papers

Related papers: A systematic way of analysing proofs in probabilit…

200 papers

We prove an equidistribution theorem a la Bader-Muchnik for operator-valued measures associated with boundary representations in the context of discrete groups of isometries of CAT(-1) spaces thanks to an equidistribution theorem of T.…

Group Theory · Mathematics 2016-07-27 Adrien Boyer

We derive new explicit bounds for the total variation distance between two convolution products of $n$ probability distributions, one of which having identical convolution factors. Approximations by finite signed measures of arbitrary order…

Probability · Mathematics 2008-11-06 Bero Roos

We study monads resulting from the combination of nondeterministic and probabilistic behaviour with the possibility of termination, which is essential in program semantics. Our main contributions are presentation results for the monads,…

Logic in Computer Science · Computer Science 2021-04-22 Matteo Mio , Ralph Sarkis , Valeria Vignudelli

The notion of probability plays a crucial role in quantum mechanics. It appears in quantum mechanics as the Born rule. In modern mathematics which describes quantum mechanics, however, probability theory means nothing other than measure…

Quantum Physics · Physics 2018-05-04 Kohtaro Tadaki

Reynold's parametricity theory captures the property that parametrically polymorphic functions behave uniformly: they produce related results on related instantiations. In dependently-typed programming languages, such relations and…

Logic in Computer Science · Computer Science 2017-07-13 Abhishek Anand , Greg Morrisett

We propose a new approach for deriving probabilistic inequalities based on bounding likelihood ratios. We demonstrate that this approach is more general and powerful than the classical method frequently used for deriving concentration…

Probability · Mathematics 2013-11-21 Xinjia Chen

To solve the probability problem of the Many Worlds Interpretation of Quantum Mechanics, D.Wallace has presented a formal proof of the Born rule via decision theory, as proposed by D.Deutsch. The idea is to get subjective probabilities from…

Quantum Physics · Physics 2018-08-07 André L. G. Mandolesi

Several approaches exist to data-mining big corpora of formal proofs. Some of these approaches are based on statistical machine learning, and some -- on theory exploration. However, most are developed for either untyped or simply-typed…

Programming Languages · Computer Science 2017-05-23 Ekaterina Komendantskaya , Jonathan Heras

Resolution and superposition are common techniques which have seen widespread use with propositional and first-order logic in modern theorem provers. In these cases, resolution proof production is a key feature of such tools; however, the…

Logic in Computer Science · Computer Science 2018-04-19 Jan Gorzny , Ezequiel Postan , Bruno Woltzenlogel Paleo

Viewing formal mathematical proofs as logical terms provides a powerful and elegant basis for analyzing how human experts tend to structure proofs and how proofs can be structured by automated methods. We pursue this approach by (1)…

Logic in Computer Science · Computer Science 2025-06-12 Christoph Wernhard , Zsolt Zombori

While model checking has often been considered as a practical alternative to building formal proofs, we argue here that the theory of sequent calculus proofs can be used to provide an appealing foundation for model checking. Since the…

Logic in Computer Science · Computer Science 2017-01-19 Quentin Heath , Dale Miller

Reasoning under uncertainty is a fundamental challenge in Artificial Intelligence. As with most of these challenges, there is a harsh dilemma between the expressive power of the language used, and the tractability of the computational…

Artificial Intelligence · Computer Science 2025-05-08 Luise Ge , Brendan Juba , Kris Nilsson

We study generalizations of Reifenberg's Theorem for measures in $\mathbb R^n$ under assumptions on the Jones' $\beta$-numbers, which appropriately measure how close the support is to being contained in a subspace. Our main results, which…

Classical Analysis and ODEs · Mathematics 2025-03-25 Nick Edelen , Aaron Naber , Daniele Valtorta

We give new proofs for the hardness amplification of efficiently samplable predicates and of weakly verifiable puzzles which generalize to new settings. More concretely, in the first part of the paper, we give a new proof of Yao's XOR-Lemma…

Cryptography and Security · Computer Science 2010-12-30 Thomas Holenstein , Grant Schoenebeck

We design an expansion of Belnap--Dunn logic with belief and plausibility functions that allow non-trivial reasoning with inconsistent and incomplete probabilistic information. We also formalise reasoning with non-standard probabilities and…

We utilize quantum superposition principle to establish the improvable upper and lower bounds on the stronger uncertainty relation, i.e., the "weighted-like" sum of the variances of observables. Our bounds include some free parameters which…

Quantum Physics · Physics 2017-04-17 Jun Zhang , Yang Zhang , Chang-shui Yu

Little effort has been devoted to studying generalised notions or models of (un)predictability, yet is an important concept throughout physics and plays a central role in quantum information theory, where key results rely on the supposed…

Quantum Physics · Physics 2020-01-27 Alastair A. Abbott , Cristian S. Calude , Karl Svozil

The uncountability of $\mathbb{R}$ is one of its most basic properties, known far outside of mathematics. Cantor's 1874 proof of the uncountability of $\mathbb{R}$ even appears in the very first paper on set theory, i.e. a historical…

Logic · Mathematics 2023-06-26 Sam Sanders

We demonstrate and develop dyadic-probabilistic methods in connection with non-homogeneous bilinear operators, namely singular integrals and square functions. We develop the full non-homogeneous theory of bilinear singular integrals using a…

Classical Analysis and ODEs · Mathematics 2018-10-19 Henri Martikainen , Emil Vuorinen

We develop a new method for generating prediction sets that combines the flexibility of conformal methods with an estimate of the conditional distribution $P_{Y \mid X}$. Existing methods, such as conformalized quantile regression and…

Machine Learning · Statistics 2024-10-10 Vincent Plassier , Alexander Fishkov , Mohsen Guizani , Maxim Panov , Eric Moulines