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In this letter I stress the role of causal reversibility (time-symmetry), together with causality and locality, in the justification of the quantum formalism. Firstly, in the algebraic quantum formalism, I show that the assumption of…

Quantum Physics · Physics 2011-10-27 Francois David

In this paper we examine a number of models that generate random fractals. The models are studied using the tools of computational complexity theory from the perspective of parallel computation. Diffusion limited aggregation and several…

Condensed Matter · Physics 2009-10-28 J. Machta , R. Greenlaw

Free categorical constructions characterise quantum computing as the combination of two copies of a reversible classical model, glued by the complementarity equations of classical structures. This recipe effectively constructs a…

Programming Languages · Computer Science 2025-11-25 Jacques Carette , Chris Heunen , Robin Kaarsgaard , Amr Sabry

We introduce Residue Hyperdimensional Computing, a computing framework that unifies residue number systems with an algebra defined over random, high-dimensional vectors. We show how residue numbers can be represented as high-dimensional…

Neural and Evolutionary Computing · Computer Science 2023-11-09 Christopher J. Kymn , Denis Kleyko , E. Paxon Frady , Connor Bybee , Pentti Kanerva , Friedrich T. Sommer , Bruno A. Olshausen

Abstract argumentation framework (\AFname) is a unifying framework able to encompass a variety of nonmonotonic reasoning approaches, logic programming and computational argumentation. Yet, efficient approaches for most of the decision and…

Artificial Intelligence · Computer Science 2014-11-19 Federico Cerutti , Ilias Tachmazidis , Mauro Vallati , Sotirios Batsakis , Massimiliano Giacomin , Grigoris Antoniou

We present a new adaptive parallel algorithm for the challenging problem of multi-dimensional numerical integration on massively parallel architectures. Adaptive algorithms have demonstrated the best performance, but efficient many-core…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-24 Ioannis Sakiotis , Kamesh Arumugam , Marc Paterno , Desh Ranjan , Balša Terzić , Mohammad Zubair

Structural causal models are the basic modelling unit in Pearl's causal theory; in principle they allow us to solve counterfactuals, which are at the top rung of the ladder of causation. But they often contain latent variables that limit…

Artificial Intelligence · Computer Science 2021-11-23 Marco Zaffalon , Alessandro Antonucci , Rafael Cabañas

Despite efforts to better understand the constraints that operate on single-step parallel (aka "package", "multiple") revision, very little work has been carried out on how to extend the model to the iterated case. A recent paper by…

Artificial Intelligence · Computer Science 2025-05-21 Jake Chandler , Richard Booth

Locks are a classic data structure for concurrent programming. We introduce a type system to ensure that names of the asynchronous pi-calculus are used as locks. Our calculus also features a construct to deallocate a lock once we know that…

Logic in Computer Science · Computer Science 2023-09-15 Daniel Hirschkoff , Enguerrand Prebet

In his article "Powerlist: A Structure for Parallel Recursion" Jayadev Misra wrote: "Many data parallel algorithms - Fast Fourier Transform, Batcher's sorting schemes and prefix sum - exhibit recursive structure. We propose a data…

Computational Geometry · Computer Science 2011-09-06 Roman Gitlin

We introduce a Curry-Howard correspondence for a large class of intermediate logics characterized by intuitionistic proofs with non-nested applications of rules for classical disjunctive tautologies (1-depth intermediate proofs). The…

Logic in Computer Science · Computer Science 2020-04-22 Federico Aschieri , Agata Ciabattoni , Francesco A. Genco

In this work, we consider causal inference in various high-dimensional treatment settings, including for single multi-valued treatments and vector treatments with binary or continuous components, when the number of treatments can be…

Statistics Theory · Mathematics 2026-02-26 Patrick Kramer , Edward H. Kennedy , Isaac M. Opper

We initiate the study of computable presentations of real and complex C*-algebras under the program of effective metric structure theory. With the group situation as a model, we develop corresponding notions of recursive presentations and…

Logic · Mathematics 2023-04-17 Alec Fox

We develop a category-theoretic criterion for determining the equivalence of causal models having different but homomorphic directed acyclic graphs over discrete variables. Following Jacobs et al. (2019), we define a causal model as a…

Machine Learning · Computer Science 2022-01-19 Jun Otsuka , Hayato Saigo

The SL synchronous programming model is a relaxation of the Esterel synchronous model where the reaction to the absence of a signal within an instant can only happen at the next instant. In previous work, we have revisited the SL…

Logic in Computer Science · Computer Science 2011-11-09 Roberto Amadio

We present a new method for causal discovery in linear structural equation models. We propose a simple ``trick'' based on statistical testing in linear models that can distinguish between ancestors and non-ancestors of any given variable.…

Methodology · Statistics 2023-03-15 Christoph Schultheiss , Peter Bühlmann

A posteriori error estimator is derived for an elliptic interface problem in the fictitious domain formulation with distributed Lagrange multiplier considering a discontinuous Lagrange multiplier finite element space. A posteriori error…

Numerical Analysis · Mathematics 2024-07-02 Najwa Alshehri , Daniele Boffi , Lucia Gastaldi

Psi-calculi is a parametric framework for extensions of the pi-calculus with data terms and arbitrary logics. In this framework there is no direct way to represent action priorities, where an action can execute only if all other enabled…

Logic in Computer Science · Computer Science 2014-08-08 Johannes Åman Pohjola , Joachim Parrow

Causal inference using observational text data is becoming increasingly popular in many research areas. This paper presents the Bayesian Topic Regression (BTR) model that uses both text and numerical information to model an outcome…

Machine Learning · Statistics 2021-09-14 Maximilian Ahrens , Julian Ashwin , Jan-Peter Calliess , Vu Nguyen

While extensive guidance exists for ensuring the reproducibility of one's own study, there is little discussion regarding the reproduction and replication of external studies within one's own research. To initiate this discussion, drawing…

Machine Learning · Computer Science 2024-01-10 Milton S. Gomez , Tom Beucler