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Thanks to the locality principle, separation logics support modular, scalable analysis of large codebases by relying on local axioms and frame rules to focus only on the heap fragments required for verification. However, depending on the…

Logic in Computer Science · Computer Science 2026-05-21 Roberto Bruni , Lorenzo Gazzella , Roberta Gori

Let $G$ be a locally compact group with left regular representation $\lambda_{G}.$ We say that $G$ admits a frame of translates if there exist a countable set $\Gamma\subset G$ and $\varphi\in L^{2}(G)$ such that $(\lambda_{G}(x)…

Representation Theory · Mathematics 2018-02-09 Hartmut Fuhr , Vignon Oussa

In cognitive science and AI, a longstanding question is whether machines learn representations that align with those of the human mind. While current models show promise, it remains an open question whether this alignment is superficial or…

Neurons and Cognition · Quantitative Biology 2025-10-27 Craig Sanders , Billy Dickson , Sahaj Singh Maini , Robert Nosofsky , Zoran Tiganj

Formal properties represent a cornerstone of the system-correctness proofs based on formal verification techniques such as model checking. Formalizing requirements into temporal properties may be very complex and error prone, due not only…

Logic in Computer Science · Computer Science 2017-09-08 Stefano Tonetta

In theoretical ecology, models describing the spatial dispersal and the temporal evolution of species having non-overlapping generations are often based on integrodifference equations. For various such applications the environment has an…

Dynamical Systems · Mathematics 2022-05-12 Huy Huy , Peter E. Kloeden , Christian Pötzsche

The Homeomorphic Embedding relation has been amply used for defining termination criteria of symbolic methods for program analysis, transformation, and verification. However, homeomorphic embedding has never been investigated in the context…

Programming Languages · Computer Science 2018-11-29 María Alpuente , Angel Cuenca-Ortega , Santiago Escobar , José Meseguer

Fuzzy closure spaces are an extension of classical closure spaces in topology, where the concept of closure is defined in terms of fuzzy sets. This article introduces interior operators and neighborhood systems in fuzzy closure spaces.…

General Topology · Mathematics 2025-09-16 Albin James , T. P. Johnson

Successor-style representations have many advantages for reinforcement learning: for example, they can help an agent generalize from past experience to new goals, and they have been proposed as explanations of behavioral and neural data…

Machine Learning · Computer Science 2021-03-17 Kianté Brantley , Soroush Mehri , Geoffrey J. Gordon

Undoing computations of a concurrent system is beneficial in many situations, e.g., in reversible debugging of multi-threaded programs and in recovery from errors due to optimistic execution in parallel discrete event simulation. A number…

Logic in Computer Science · Computer Science 2024-02-13 Ivan Lanese , Iain Phillips , Irek Ulidowski

We present the notions of positively complete theory and general forms of amalgamation in the framework of positive logic. We explore the fundamental properties of positively complete theories and study the behaviour of companion theories…

Logic · Mathematics 2019-11-15 Mohammed Belkasmi

We introduce a framework that allows for the construction of sequent systems for expressive description logics extending ALC. Our framework not only covers a wide array of common description logics, but also allows for sequent systems to be…

Logic in Computer Science · Computer Science 2022-06-22 Tim Lyon , Jonas Karge

It is proposed that to the usual probability theory, three definitions and a new theorem are added, the resulting theory allows one to displace the central role usually given to the notion of conditional probability. When a mapping $\phi$…

Probability · Mathematics 2008-11-04 Albert Tarantola

Characteristic formulae give a complete logical description of the behaviour of processes modulo some chosen notion of behavioural semantics. They allow one to reduce equivalence or preorder checking to model checking, and are exactly the…

Logic in Computer Science · Computer Science 2026-03-27 Luca Aceto , Antonis Achilleos , Aggeliki Chalki , Anna Ingolfsdottir

We study feature interactions in the context of feature attribution methods for post-hoc interpretability. In interpretability research, getting to grips with feature interactions is increasingly recognised as an important challenge,…

Computation and Language · Computer Science 2023-06-22 Jaap Jumelet , Willem Zuidema

Within a global physical theory, a notion of locality allows us to find and justify information-processing primitives, like non-signalling between distant agents. Here we propose exploring the opposite direction: to take agents as the basic…

Quantum Physics · Physics 2018-05-31 Lea Kraemer , Lidia del Rio

In a recent article, Dieks has proposed a way to implement the modal interpretation of (nonrelativistic) quantum theory in relativistic quantum field theory. We show that his proposal fails to yield a well-defined prescription for which…

Quantum Physics · Physics 2009-11-06 Rob Clifton

Motivated by the definition of the smooth manifold structure on a suitable mapping space, we consider the general problem of how to transfer local properties from a smooth space to an associated mapping space. This leads to the notion of…

Differential Geometry · Mathematics 2013-01-24 Andrew Stacey

Results of measurements give legitimacy to a physical theory. What if acquiring these results in the first place necessitates what the same theory considers to be an interaction? In this note, we assume that theories account for…

Quantum Physics · Physics 2019-05-01 Arne Hansen , Stefan Wolf

Learning linear temporal logic (LTL) formulas from examples labeled as positive or negative has found applications in inferring descriptions of system behavior. We summarize two methods to learn LTL formulas from examples in two different…

Logic in Computer Science · Computer Science 2022-12-05 Jean-Raphaël Gaglione , Rajarshi Roy , Nasim Baharisangari , Daniel Neider , Zhe Xu , Ufuk Topcu

The internal representations learned by deep networks are often sensitive to architecture-specific choices, raising questions about the stability, alignment, and transferability of learned structure across models. In this paper, we…

Machine Learning · Computer Science 2025-08-06 Saleh Nikooroo , Thomas Engel