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We consider the effective field theory of gravity around black holes, and show that the coefficients of the dimension-8 operators are tightly constrained by causality considerations. Those constraints are consistent with -- but tighter than…

General Relativity and Quantum Cosmology · Physics 2024-01-22 Claudia de Rham , Andrew J. Tolley , Jun Zhang

We study the estimation of causal parameters when not all confounders are observed and instead negative controls are available. Recent work has shown how these can enable identification and efficient estimation via two so-called bridge…

Machine Learning · Statistics 2022-10-11 Nathan Kallus , Xiaojie Mao , Masatoshi Uehara

We subject the methodology used to derive the effective dynamics of topological defects to a critical reappraisal, using the two-dimensional kink as an illustrative example. Special care is taken on how the zero modes should be handled in…

High Energy Physics - Theory · Physics 2009-10-30 Jordi Paris , Jaume Roca

This is a comprehensive review on fault-tolerant topological quantum computation with the surface codes. The basic concepts and useful tools underlying fault-tolerant quantum computation, such as universal quantum computation, stabilizer…

Quantum Physics · Physics 2015-04-08 Keisuke Fujii

A causal rate distortion function with a general fidelity criterion is formulated on abstract alphabets and a coding theorem is derived. Existence of the minimizing kernel is shown using the topology of weak convergence of probability…

Information Theory · Computer Science 2012-02-07 Photios A. Stavrou , Charalambos D. Charalambous , Christos K. Kourtellaris

A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type. Recent literature has explored representation learning to achieve this goal. In this work, we discuss the…

Machine Learning · Statistics 2021-02-25 Serge Assaad , Shuxi Zeng , Chenyang Tao , Shounak Datta , Nikhil Mehta , Ricardo Henao , Fan Li , Lawrence Carin

We propose a method to distinguish causal influence from hidden confounding in the following scenario: given a target variable Y, potential causal drivers X, and a large number of background features, we propose a novel criterion for…

Machine Learning · Statistics 2022-02-07 You-Lin Chen , Lenon Minorics , Dominik Janzing

When estimating causal effects from observational studies, researchers often need to adjust for many covariates to deconfound the non-causal relationship between exposure and outcome, among which many covariates are discrete. The behavior…

Statistics Theory · Mathematics 2024-05-07 Zhenghao Zeng , Sivaraman Balakrishnan , Yanjun Han , Edward H. Kennedy

The potential role of cosmic topological defects has raised interest in the astrophysical community for many years now. In this set of notes, we give an introduction to the subject of cosmic topological defects and some of their possible…

Astrophysics · Physics 2009-11-07 Alejandro Gangui

Despite the success of machine learning applications in science, industry, and society in general, many approaches are known to be non-robust, often relying on spurious correlations to make predictions. Spuriousness occurs when some…

Computer Vision and Pattern Recognition · Computer Science 2021-06-04 Chun-Hao Chang , George Alexandru Adam , Anna Goldenberg

We present a detailed study of a simple scalar field model that yields non-singular cosmological solutions. We study both the qualitative dynamics of the homogeneous and isotropic background and the evolution of inhomogeneous linear…

Astrophysics · Physics 2009-11-10 Laura E. Allen , David Wands

Identifying effects of actions (treatments) on outcome variables from observational data and causal assumptions is a fundamental problem in causal inference. This identification is made difficult by the presence of confounders which can be…

Methodology · Statistics 2012-03-19 Ilya Shpitser , Tyler VanderWeele , James M. Robins

Matter and quasi-matter bounce scenarios are studied for an F(R) gravity model with holonomy corrections and a Lagrange multiplier, with a scale factor $a(t) = \left(a_0t^2 + 1 \right)^n$, where the Hubble parameter squared has a linear and…

General Relativity and Quantum Cosmology · Physics 2020-01-29 Emilio Elizalde , S. D. Odintsov , Tanmoy Paul

Causal decomposition has provided a powerful tool to analyze health disparity problems, by assessing the proportion of disparity caused by each mediator. However, most of these methods lack \emph{policy implications}, as they fail to…

Methodology · Statistics 2023-02-21 Xinwei Sun , Xiangyu Zheng , Jim Weinstein

The effects of a boundary on the circuit complexity are studied in two dimensional theories. The analysis is performed in the holographic realization of a conformal field theory with a boundary by employing different proposals for the dual…

High Energy Physics - Theory · Physics 2021-04-15 Paolo Braccia , Aldo L. Cotrone , Erik Tonni

The linear cosmological perturbation theory of an almost homogeneous and isotropic perfect fluid universe is reconsidered and formally simplified by introducing new covariant and gauge-invariant variables with physical interpretations on…

General Relativity and Quantum Cosmology · Physics 2011-07-19 Winfried Zimdahl

Approximate Bayesian Computation (ABC) is typically used when the likelihood is either unavailable or intractable but where data can be simulated under different parameter settings using a forward model. Despite the recent interest in ABC,…

Methodology · Statistics 2019-12-24 Rafael Izbicki , Ann B. Lee , Taylor Pospisil

In the absence of a theory of everything, modern physicists need to rely on other predictive tools and turned to Effective Field Theories (EFTs) in a number of fields, including but not limited to statistical mechanics, condensed matter,…

High Energy Physics - Theory · Physics 2023-08-17 Victor Pozsgay

We explore the constraints imposed on higher curvature corrections of the Lovelock type due to causality restrictions in the boundary of asymptotically AdS space-time. In the framework of AdS/CFT, this is related to positivity of the energy…

High Energy Physics - Theory · Physics 2014-11-20 Xian O. Camanho , Jose D. Edelstein

We present Causal Posterior Estimation (CPE), a novel method for Bayesian inference in simulator models, i.e., models where the evaluation of the likelihood function is intractable or too computationally expensive, but where one can…

Machine Learning · Computer Science 2025-05-28 Simon Dirmeier , Antonietta Mira
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