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Related papers: Why trust a theory? Some further remarks (part 1)

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This is an invited contribution to the Special Issue of "Foundations of Physics" titled "Forty Years Of String Theory: Reflecting On the Foundations". I have been asked to assess string theory as an outsider, and to compare it with the…

High Energy Physics - Theory · Physics 2015-05-30 Carlo Rovelli

Bayesian probability theory is used as a framework to develop a formalism for the scientific method based on principles of inductive reasoning. The formalism allows for precise definitions of the key concepts in theories of physics and also…

Data Analysis, Statistics and Probability · Physics 2011-09-12 Roberto C. Alamino

Explaining predictions from Bayesian networks, for example to physicians, is non-trivial. Various explanation methods for Bayesian network inference have appeared in literature, focusing on different aspects of the underlying reasoning.…

Artificial Intelligence · Computer Science 2021-10-05 Raphaela Butz , Renée Schulz , Arjen Hommersom , Marko van Eekelen

Our laws of nature and our cosmos appear to be delicately fine-tuned for life to emerge, in a way that seems hard to attribute to chance. In view of this, some have taken the opportunity to revive the scholastic Argument from Design,…

History and Philosophy of Physics · Physics 2015-05-22 Klaas Landsman

This paper introduces and reviews some of the principles and methods used in Bayesian reliability. It specifically discusses methods used in the analysis of success/no-success data and then reminds the reader of a simple Monte Carlo…

Methodology · Statistics 2024-06-10 Carsten H. Botts

In the book "String Theory and the Scientific Method", Richard Dawid describes a few of the many non-empirical arguments that motivate theoretical physicists' confidence in a theory, taking string theory as case study. I argue that…

History and Philosophy of Physics · Physics 2016-09-08 Carlo Rovelli

This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal method for summarising uncertainty and making estimates and predictions using probability statements conditional on observed data and an…

Methodology · Statistics 2010-02-11 Christian P. Robert , Jean-Michel Marin , Judith Rousseau

Research at the intersection of machine learning and the social sciences has provided critical new insights into social behavior. At the same time, a variety of critiques have been raised ranging from technical issues with the data used and…

Computers and Society · Computer Science 2020-01-16 Jason Radford , Kenneth Joseph

These notes on string theory are based on a series of talks I gave during my graduate studies. As the talks, this introductory essay is intended for young students and non-string theory physicists.

High Energy Physics - Theory · Physics 2007-05-23 Oswaldo Zapata

This paper presents a plausible reasoning system to illustrate some broad issues in knowledge representation: dualities between different reasoning forms, the difficulty of unifying complementary reasoning styles, and the approximate nature…

Artificial Intelligence · Computer Science 2013-03-26 Wray L. Buntine

This is the written version of a short talk given at the University of Leipzig in December 1998. It reviews some general aspects of string theory from the viewpoint of the search for an unifying theory. Here, special emphasis lies on the…

High Energy Physics - Theory · Physics 2007-05-23 M. Rudolph

Discovering causal relationships is a hard task, often hindered by the need for intervention, and often requiring large amounts of data to resolve statistical uncertainty. However, humans quickly arrive at useful causal relationships. One…

Machine Learning · Statistics 2011-12-01 Pedro A. Ortega

In the classical literature on infinite series there are various tests to determine if a given infinite series converges, diverges, or oscillates. But unfortunately, for very many infinite series all the existing tests can fail to provide…

Statistics Theory · Mathematics 2018-04-13 Sucharita Roy , Sourabh Bhattacharya

A polemical article evaluating string theory from the point of view of a quantum field theorist working in a mathematics department. Comments to the author are encouraged.

Physics and Society · Physics 2007-05-23 Peter Woit

We critically assess the twin prospects of describing the observed universe in string theory, and using cosmological experiments to probe string theory. For the purposes of this short review, we focus on the limitations imposed by our…

High Energy Physics - Theory · Physics 2015-05-30 C. P. Burgess , Liam McAllister

This is a non-standard paper, containing some problems in set theory I have in various degrees been interested in. Sometimes with a discussion on what I have to say; sometimes, of what makes them interesting to me, sometimes the problems…

Logic · Mathematics 2007-05-23 Saharon Shelah

Bayesian probability theory is used to analyze the oft-made assumption that humans are typical observers in the universe. Some theoretical calculations make the {\it selection fallacy} that we are randomly chosen from a class of objects by…

High Energy Physics - Theory · Physics 2008-11-26 James B. Hartle , Mark Srednicki

We argue here about the relevance and the ultimate unity of the Bayesian approach in a neutral and agnostic manner. Our main theme is that Bayesian data analysis is an effective tool for handling complex models, as proven by the increasing…

Methodology · Statistics 2010-03-26 Christian P. Robert

Theoretical physics is the search for simple and universal mathematical descriptions of the natural world. In contrast, much of modern biology is an exploration of the complexity and diversity of life. For many, this contrast is prima facie…

Biological Physics · Physics 2024-01-23 William Bialek

We develop the theory and practice of an approach to modelling and probabilistic inference in causal networks that is suitable when application-specific or analysis-specific constraints should inform such inference or when little or no data…

Artificial Intelligence · Computer Science 2017-05-16 Paul Beaumont , Michael Huth