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Prediction-powered inference is a framework for performing valid statistical inference when an experimental dataset is supplemented with predictions from a machine-learning system. The framework yields simple algorithms for computing…

Machine Learning · Statistics 2023-11-10 Anastasios N. Angelopoulos , Stephen Bates , Clara Fannjiang , Michael I. Jordan , Tijana Zrnic

Computer simulation of the time evolution in a classical system is a standard numerical method, used in numerous scientific articles in Natural Science. Almost all the simulations are performed by discrete Molecular Dynamics (MD). The…

Classical Physics · Physics 2023-05-18 S. Toxvaerd

A functional equation for the motivic integral corresponding to the Milnor number of an arc is derived using the Denef-Loeser formula for the change of variables. Its solution is a function of five auxiliary parameters, it is unique up to…

Algebraic Geometry · Mathematics 2012-08-22 E. Gorsky

Experimental science usually relies on laboratory procedures that, after finitely many steps, terminate with numerical reports on physical quantities. This paper argues that such procedures can be understood as algorithmic once the…

History and Philosophy of Physics · Physics 2026-05-06 Isaac Pérez Castillo

This paper considers the computational power of constant size, dynamic Bayesian networks. Although discrete dynamic Bayesian networks are no more powerful than hidden Markov models, dynamic Bayesian networks with continuous random variables…

Artificial Intelligence · Computer Science 2017-08-28 Joshua Brulé

We develop a theory of linear Mahler systems in several variables from the perspective of transcendence and algebraic independence, which also includes the possibility of dealing with several systems associated with sufficiently independent…

Number Theory · Mathematics 2020-12-16 Boris Adamczewski , Colin Faverjon

Because contemporary large software systems are pervasively inconsistent, it is not safe to reason about them using classical logic. The goal of Direct Logic is to be a minimal fix to classical mathematical logic that meets the requirements…

Logic in Computer Science · Computer Science 2015-03-03 Carl Hewitt

Current algorithms for context-free parsing inflict a trade-off between ease of understanding, ease of implementation, theoretical complexity, and practical performance. No algorithm achieves all of these properties simultaneously. Might et…

Programming Languages · Computer Science 2016-04-19 Michael D. Adams , Celeste Hollenbeck , Matthew Might

Quantum computing takes fully advantage of the superposition principle to increase greatly (even exponentially) the speed of calculations, relative to the classical approach. The Deutsch-Jozsa algorithm is the simplest quantum algorithm…

Quantum Physics · Physics 2008-10-14 Neda Amin , Patrick Labelle

We introduce a set of eight universal Rules of Inference by which computer programs with known properties (axioms) are transformed into new programs with known properties (theorems). Axioms are presented to formalize a segment of Number…

Logic in Computer Science · Computer Science 2007-05-23 Charlie Volkstorf

We investigate the modal logic of stepwise removal of objects, both for its intrinsic interest as a logic of quantification without replacement, and as a pilot study to better understand the complexity jumps between dynamic epistemic logics…

Logic in Computer Science · Computer Science 2021-03-10 Johan van Benthem , Krzysztof Mierzewski , Francesca Zaffora Blando

Motion Magnification (MM) is a collection of relative recent techniques within the realm of Image Processing. The main motivation of introducing these techniques in to support the human visual system to capture relevant displacements of an…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Nadaniela Egidi , Josephin Giacomini , Paolo Leonesi , Pierluigi Maponi , Federico Mearelli , Edin Trebovic

A key component of mathematical reasoning is the ability to formulate interesting conjectures about a problem domain at hand. In this paper, we give a brief overview of a theory exploration system called QuickSpec, which is able to…

Logic in Computer Science · Computer Science 2021-09-09 Moa Johansson , Nicholas Smallbone

Quantum mechanics---the theory describing the fundamental workings of nature---is famously counterintuitive: it predicts that a particle can be in two places at the same time, and that two remote particles can be inextricably and…

Quantum theory promises computational speed-ups over classical approaches. The celebrated Gottesman-Knill Theorem implies that the full power of quantum computation resides in the specific resource of "magic" states -- the secret sauce to…

Quantum Physics · Physics 2025-02-11 Xingjian Zhang , Zhaokai Pan , Guoding Liu

A fundamental question is whether Turing machines can model all reasoning processes. We introduce an existence principle stating that the perception of the physical existence of any Turing program can serve as a physical causation for the…

Artificial Intelligence · Computer Science 2016-08-17 Kurt Ammon

How can we explain the predictions of a black-box model? In this paper, we use influence functions -- a classic technique from robust statistics -- to trace a model's prediction through the learning algorithm and back to its training data,…

Machine Learning · Statistics 2021-01-01 Pang Wei Koh , Percy Liang

The proposed system of integer functions is logically fully independent from the traditional mathematical analysis of the real functions, but there is a well-defined mutual correspondence between the two disciplines. The system of integer…

General Mathematics · Mathematics 2017-10-03 Jozsef Peredy

Induction lies at the heart of mathematics and computer science. However, automated theorem proving of inductive problems is still limited in its power. In this abstract, we first summarize our progress in automating inductive theorem…

Logic in Computer Science · Computer Science 2019-03-27 Yutaka Nagashima

Parameterized complexity theory has lead to a wide range of algorithmic breakthroughs within the last decades, but the practicability of these methods for real-world problems is still not well understood. We investigate the practicability…

Data Structures and Algorithms · Computer Science 2018-06-28 Max Bannach , Sebastian Berndt