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A fundamental challenge in the empirical sciences involves uncovering causal structure through observation and experimentation. Causal discovery entails linking the conditional independence (CI) invariances in observational data to their…

Machine Learning · Statistics 2025-11-04 Zihan Zhou , Muhammad Qasim Elahi , Murat Kocaoglu

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

In 2011, Rideau and Winskel introduced concurrent games and strategies as event structures, generalizing prior work on causal formulations of games. In this paper we give a detailed, self-contained and slightly-updated account of the…

Logic · Mathematics 2019-03-14 Simon Castellan , Pierre Clairambault , Silvain Rideau , Glynn Winskel

The aim in many sciences is to understand the mechanisms that underlie the observed distribution of variables, starting from a set of initial hypotheses. Causal discovery allows us to infer mechanisms as sets of cause and effect…

Machine Learning · Computer Science 2025-03-05 Ashka Shah , Adela DePavia , Nathaniel Hudson , Ian Foster , Rick Stevens

Document-level Event Causality Identification (DECI) aims to identify causal relations between two events in documents. Recent research tends to use pre-trained language models to generate the event causal relations. Whereas, these methods…

Computation and Language · Computer Science 2024-03-19 Baiyan Zhang , Qin Chen , Jie Zhou , Jian Jin , Liang He

In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests of the Standard Model and in searches for physics beyond it. Performing kinematic reconstruction in collider events with many…

High Energy Physics - Phenomenology · Physics 2025-02-13 Callum Birch-Sykes , Brian Le , Yvonne Peters , Ethan Simpson , Zihan Zhang

Through recognizing causal subgraphs, causal graph learning (CGL) has risen to be a promising approach for improving the generalizability of graph neural networks under out-of-distribution (OOD) scenarios. However, the empirical successes…

Machine Learning · Computer Science 2025-07-02 Yujia Yin , Tianyi Qu , Zihao Wang , Yifan Chen

We present a domain-specific embedded language (DSEL) in Haskell that supports the philosophical study and practical explanation of causation. The language provides constructs for modeling situations comprised of events and functions for…

Programming Languages · Computer Science 2011-09-06 Eric Walkingshaw , Martin Erwig

The notion of events has occupied a central role in modeling and has an influence in computer science and philosophy. Recent developments in diagrammatic modeling have made it possible to examine conceptual representation of events. This…

Artificial Intelligence · Computer Science 2017-04-28 Sabah Al-Fedaghi

We define a bi-directional embedding between hypersequent calculi and a subclass of systems of rules (2-systems). In addition to showing that the two proof frameworks have the same expressive power, the embedding allows for the recovery of…

Logic · Mathematics 2018-05-15 Agata Ciabattoni , Francesco A. Genco

A series of works has established rewriting as an essential tool in order to prove coherence properties of algebraic structures, such as MacLane's coherence theorem for monoidal categories, based on the observation that, under reasonable…

Category Theory · Mathematics 2025-07-30 Samuel Mimram

We present two rewriting systems that define labelled explicit substitution lambda-calculi. Our work is motivated by the close correspondence between Levy's labelled lambda-calculus and paths in proof-nets, which played an important role in…

Logic in Computer Science · Computer Science 2010-03-30 Maribel Fernández , Nikolaos Siafakas

This paper is an expository contribution reporting on published work. It focusses on an approach followed in the rewriting community to formalize the concept of strategy. Based on rewriting concepts, several definitions of strategy are…

Logic in Computer Science · Computer Science 2013-03-05 Hélène Kirchner

There has been a great deal of research on graphs defined on algebraic structures in the last two decades. In this paper we begin an exploration of hypergraphs defined on algebraic structures, especially groups, to investigate whether this…

Combinatorics · Mathematics 2023-03-02 Peter J. Cameron , Aparna Lakshmanan S. , Midhuna V. Ajith

Scientific discovery catalyzes human intellectual advances, driven by the cycle of hypothesis generation, experimental design, evaluation, and assumption refinement. Central to this process is causal inference, uncovering the mechanisms…

Machine Learning · Computer Science 2025-09-26 Ivaxi Sheth , Sahar Abdelnabi , Mario Fritz

Abstracting from a low level to a more explanatory high level of description, and ideally while preserving causal structure, is fundamental to scientific practice, to causal inference problems, and to robust, efficient and interpretable AI.…

Logic in Computer Science · Computer Science 2026-02-19 Robin Lorenz , Sean Tull

Event extraction involves the detection and extraction of both the event triggers and corresponding event arguments. Existing systems often decompose event extraction into multiple subtasks, without considering their possible interactions.…

Computation and Language · Computer Science 2022-10-18 Huiling You , David Samuel , Samia Touileb , Lilja Øvrelid

Texts present coherent stories that have a particular theme or overall setting, for example science fiction or western. In this paper, we present a text generation method called {\it rewriting} that edits existing human-authored narratives…

Computation and Language · Computer Science 2016-10-21 Rik Koncel-Kedziorski , Ioannis Konstas , Luke Zettlemoyer , Hannaneh Hajishirzi

We address the problem of cyclic termgraph rewriting. We propose a new framework where rewrite rules are tuples of the form $(L,R,\tau,\sigma)$ such that $L$ and $R$ are termgraphs representing the left-hand and the right-hand sides of the…

Logic in Computer Science · Computer Science 2008-11-21 Dominique Duval , Rachid Echahed , Frédéric Prost

Probabilistic programming is becoming increasingly popular thanks to its ability to specify problems with a certain degree of uncertainty. In this work, we focus on term rewriting, a well-known computational formalism. In particular, we…

Programming Languages · Computer Science 2025-03-20 Germán Vidal
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