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Related papers: KF, PKF, and Reinhardt's Program

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In this paper, we show how a construction of an implicit complexity model can be implemented using concepts coming from the core of von Neumann algebras. Namely, our aim is to gain an understanding of classical computation in terms of the…

Computational Complexity · Computer Science 2009-12-31 Marco Pedicini , Mario Piazza

There is a way of assigning a realizability notion to each degree of incomputability. In our setting, we make use of Weihrauch degrees (degrees of incomputability/discontinuity of partial multi-valued functions) to obtain Lifschitz-like…

Logic · Mathematics 2025-05-07 Takayuki Kihara

With view to applications, we establish a correspondence between two problems: (i) the problem of finding continuous positive definite extensions of functions $F$ which are defined on open bounded domains $\Omega$ in $\mathbb{R}$, on the…

Functional Analysis · Mathematics 2015-06-19 Palle Jorgensen , Feng Tian

A unification of the set of quasiprobability representations using the mathematical theory of frames was recently developed for quantum systems with finite-dimensional Hilbert spaces, in which it was proven that such representations require…

Quantum Physics · Physics 2010-10-18 Christopher Ferrie , Ryan Morris , Joseph Emerson

Large Language Models (LLMs) demonstrate impressive mathematical reasoning abilities, but their solutions frequently contain errors that cannot be automatically checked. Formal theorem proving systems such as Lean 4 offer automated…

Artificial Intelligence · Computer Science 2026-03-18 Sumanth Varambally , Thomas Voice , Yanchao Sun , Zhifeng Chen , Rose Yu , Ke Ye

We go on in the program of investigating the removal of divergences of a generical quantum gauge field theory, in the context of the Batalin-Vilkovisky formalism. We extend to open gauge-algebrae a recently formulated algorithm, based on…

High Energy Physics - Theory · Physics 2010-04-06 Damiano Anselmi

We present a semi-automated framework to construct and reason about programs in a deeply-embedded while-language. The while-language we consider is a simple computation model that can simulate (and be simulated by) Turing Machines with a…

Logic in Computer Science · Computer Science 2025-04-22 Kevin Kappelmann , Fabian Huch , Lukas Stevens , Mohammad Abdulaziz

The formalism of abstracted quantum mechanics is applied in a model of the generalized Liar Paradox. Here, the Liar Paradox, a consistently testable configuration of logical truth properties, is considered a dynamic conceptual entity in the…

Quantum Physics · Physics 2010-04-16 Diederik Aerts , Jan Broekaert , Bart D'Hooghe

Ackermann's function can be expressed using an iterative algorithm, which essentially takes the form of a term rewriting system. Although the termination of this algorithm is far from obvious, its equivalence to the traditional recursive…

Logic in Computer Science · Computer Science 2022-10-14 Lawrence C Paulson

The classical PCP theorem is arguably the most important achievement of classical complexity theory in the past quarter century. In recent years, researchers in quantum computational complexity have tried to identify approaches and develop…

Quantum Physics · Physics 2013-10-01 Dorit Aharonov , Itai Arad , Thomas Vidick

Knowledge tracing (KT) plays a crucial role in computer-aided education and intelligent tutoring systems, aiming to assess students' knowledge proficiency by predicting their future performance on new questions based on their past response…

Computers and Society · Computer Science 2024-06-03 Jiajun Cui , Minghe Yu , Bo Jiang , Aimin Zhou , Jianyong Wang , Wei Zhang

Counterfactual explanations are a prominent example of post-hoc interpretability methods in the explainable Artificial Intelligence research domain. They provide individuals with alternative scenarios and a set of recommendations to achieve…

Artificial Intelligence · Computer Science 2021-01-20 Andrea Ferrario , Michele Loi

In preparing the paper "Some extensions of Hilbert-Kunz multiplicity", we had occasion to perform an intricate set of computations pertaining to a single illustrative example. In the end, we have decided not to include the computations in…

Commutative Algebra · Mathematics 2016-05-09 Neil Epstein , Yongwei Yao

An extended analysis is given of the program, originally suggested by Deutsch, of solving the probability problem in the Everett interpretation by means of decision theory. Deutsch's own proof is discussed, and alternatives are presented…

Quantum Physics · Physics 2007-05-23 David Wallace

The purpose of this note is to point out a simple consequence of some earlier work of the authors, "Hard Sard: Quantitative implicit function and extension theorems for Lipschitz maps". For $f$, a Lipschitz function from a Euclidean space…

Metric Geometry · Mathematics 2012-06-26 Jonas Azzam , Raanan Schul

This work is motivated by a question at the heart of unsupervised learning approaches: Assume we are collecting a number K of (subjective) opinions about some event E from K different agents. Can we infer E from them? Prima facie this seems…

Information Theory · Computer Science 2018-05-15 Janis Nötzel , Walter Swetly

This is a short text covering some topics on the Foundations of Quantum Theory and it includes some comments on the recent Nature article by D. Frauchiger and R. Renner. The so-called "paradox" is simply due to a misunderstanding on the…

Quantum Physics · Physics 2019-01-15 Daniel V. Tausk

Since the dawn of quantum theory, coherence was attributed as a key to understand the weirdness of fundamental concepts like the wave-particle duality and the Stern-Gerlach experiment. Recently, based on a resource theory approach, the…

In this contribution, kernel approximations are applied as ansatz functions within the Deep Ritz method. This allows to approximate weak solutions of elliptic partial differential equations with weak enforcement of boundary conditions using…

Numerical Analysis · Mathematics 2024-10-07 Hendrik Kleikamp , Tizian Wenzel

We present a general framework for evaluating image counterfactuals. The power and flexibility of deep generative models make them valuable tools for learning mechanisms in structural causal models. However, their flexibility makes…

Computer Vision and Pattern Recognition · Computer Science 2023-03-03 Miguel Monteiro , Fabio De Sousa Ribeiro , Nick Pawlowski , Daniel C. Castro , Ben Glocker
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