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Effective and reliable evaluation is essential for advancing empirical machine learning. However, the increasing accessibility of generalist models and the progress towards ever more complex, high-level tasks make systematic evaluation more…

Machine Learning · Computer Science 2025-02-10 Felix Leeb , Zhijing Jin , Bernhard Schölkopf

In this paper, we continue our research on the algorithmic aspects of Halpern and Pearl's causes and explanations in the structural-model approach. To this end, we present new characterizations of weak causes for certain classes of causal…

Artificial Intelligence · Computer Science 2013-01-07 Thomas Eiter , Thomas Lukasiewicz

A condensed introduction to the basic concepts of causal perturbation theory is given. Causal perturbation theory is a mathematically rigorous approach to renormalization theory, which makes it possible to put the theoretical setup of…

High Energy Physics - Theory · Physics 2009-02-19 Andreas Aste

Recent developments in the formalisation of quantum causal structures have made it possible to test and compare hypotheses about causal structure empirically, rather than being a-priori assumptions. Such differences in causal structure may…

Quantum Physics · Physics 2026-05-28 Declan Maguire , Fabio Costa

Causal reasoning is essential to science, yet quantum theory challenges it. Quantum correlations violating Bell inequalities defy satisfactory causal explanations within the framework of classical causal models. What is more, a theory…

Quantum Physics · Physics 2021-03-05 Jonathan Barrett , Robin Lorenz , Ognyan Oreshkov

We introduce a formalism for the evaluation of counterfactual queries in the framework of quantum causal models, generalising Pearl's semantics for counterfactuals in classical causal models, thus completing the last rung in the quantum…

Quantum Physics · Physics 2024-09-18 Ardra Kooderi Suresh , Markus Frembs , Eric G. Cavalcanti

Causal nonseparability refers to processes where events take place in a coherent superposition of different causal orders. These may be the key resource for experimental violations of causal inequalities and have been recently identified as…

Quantum Physics · Physics 2019-12-16 Márcio M. Taddei , Ranieri V. Nery , Leandro Aolita

Heckerman (1993) defined causal independence in terms of a set of temporal conditional independence statements. These statements formalized certain types of causal interaction where (1) the effect is independent of the order that causes are…

Artificial Intelligence · Computer Science 2015-05-19 David Heckerman , John S. Breese

The complete reason behind a decision is a Boolean formula that characterizes why the decision was made. This recently introduced notion has a number of applications, which include generating explanations, detecting decision bias and…

Artificial Intelligence · Computer Science 2022-03-22 Adnan Darwiche , Chunxi Ji

Causal discovery and causal effect estimation are two fundamental tasks in causal inference. While many methods have been developed for each task individually, statistical challenges arise when applying these methods jointly: estimating…

Methodology · Statistics 2024-08-21 Paula Gradu , Tijana Zrnic , Yixin Wang , Michael I. Jordan

Could cosmic structure have formed by the action of causal physics within the standard hot big bang, or was a prior period of inflation required? Recently there has been some discussion of whether causal sources could reproduce the pattern…

Astrophysics · Physics 2008-11-26 Neil Turok

In [4], we introduced an extension of team semantics (causal teams) which assigns an interpretation to interventionist counterfactuals and causal notions based on them (as e.g. in Pearl's and Woodward's manipulationist approaches to…

Logic in Computer Science · Computer Science 2023-05-23 Fausto Barbero , Gabriel Sandu

In this paper we introduce a notion of counterfactual causality in the Halpern and Pearl sense that is compositional with respect to the interleaving of transition systems. The formal framework for reasoning on what caused the violation of…

Logic in Computer Science · Computer Science 2016-08-30 Georgiana Caltais , Stefan Leue , Mohammad Reza Mousavi

In a causal world the direction of the time arrow dictates how past causal events in a variable $X$ produce future effects in $Y$. $X$ is said to cause an effect in $Y$, if the predictability (uncertainty) about the future states of $Y$…

Chaotic Dynamics · Physics 2018-07-24 Ezequiel Bianco-Martinez , Murilo S. Baptista

We present several philosophical ideas emerging from the studies of complex systems. We make a brief introduction to the basic concepts of complex systems, for then defining "abstraction levels". These are useful for representing…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Carlos Gershenson

Not much has been written about the role of triggers in the literature on causal reasoning, causal modeling, or philosophy. In this paper, we focus on describing triggers and causes in the metaphysical sense and on characterizations that…

Machine Learning · Computer Science 2025-04-03 Kateřina Hlaváčková-Schindler , Rainer Wöß , Vera Pecorino , Philip Schindler

The study of biases, such as gender or racial biases, is an important topic in the social and behavioural sciences. However, the literature does not always clearly define the concept. Definitions of bias are often ambiguous or not provided…

Digital Libraries · Computer Science 2024-07-22 V. A. Traag , L. Waltman

In this review paper, we consider the fundamental nature of time and causality, most particularly, in the context of the theories of special and general relativity. We also discuss the issue of closed timelike curves in the context of…

General Relativity and Quantum Cosmology · Physics 2009-04-15 Orfeu Bertolami , Francisco S. N. Lobo

We propose a decision theoretic framework that allows a decision maker to express its causal model of the world. We extend the model of Savage (1972) by allowing the decision maker (DM) to choose policy interventions prior to choosing acts…

Theoretical Economics · Economics 2024-07-23 Pablo Schenone

LLM-based social simulations can generate believable community interactions, enabling ``policy wind tunnels'' where governance interventions are tested before deployment. But believability is not causality. Claims like ``intervention $A$…

Computation and Language · Computer Science 2026-04-17 Agam Goyal , Yian Wang , Eshwar Chandrasekharan , Hari Sundaram