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It is commonly-accepted wisdom that more information is better, and that information should never be ignored. Here we argue, using both a Bayesian and a non-Bayesian analysis, that in some situations you are better off ignoring information…

Artificial Intelligence · Computer Science 2014-07-29 Peter D. Grunwald , Joseph Y. Halpern

In this work a quantum analogue of Bayesian inference is considered. Based on the notion of instrument, we propose a quantum analogue of Bayes' rule, which elaborates how a prior normal state updates under observations. Besides, we…

Quantum Physics · Physics 2023-01-10 Huayu Liu

By studying the present cosmological data, particularly on CMB, SNeIA and LSS, we find that the future fate of the universe, for simple linear models of the dark energy equation-of-state, can vary between the extremes of (I) a divergence of…

Astrophysics · Physics 2010-04-05 Paul H. Frampton , Tomo Takahashi

As observers of the universe we are physical systems within it. If the universe is very large in space and/or time, the probability becomes significant that the data on which we base predictions is replicated at other locations in…

High Energy Physics - Theory · Physics 2015-05-18 Mark Srednicki , James Hartle

We use an argument by Page to exhibit a paradox in the global description of the multiverse: the overwhelming majority of observers arise from quantum fluctuations and not by conventional evolution. Unless we are extremely atypical, this…

High Energy Physics - Theory · Physics 2010-10-27 Raphael Bousso , Ben Freivogel

Recently it was found, in a broad class of models, that the dark energy density may change its sign during the evolution of the universe. This may lead to a global collapse of the universe within the time t_c ~ 10^{10}-10^{11} years. Our…

Astrophysics · Physics 2009-09-29 Renata Kallosh , Jan Kratochvil , Andrei Linde , Eric V. Linder , Marina Shmakova

The Drake equation has been used many times to estimate the number of observable civilizations in the Galaxy. However, the uncertainty of the outcome is so great that any individual result is of limited use, as predictions can range from a…

Popular Physics · Physics 2023-07-19 Alex De Visscher

In the absence of a fundamental theory that precisely predicts values for observable parameters, anthropic reasoning attempts to constrain probability distributions over those parameters in order to facilitate the extraction of testable…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-29 Feraz Azhar

The Peaks Over Threshold (POT) method is the most popular statistical method for the analysis of univariate extremes. Even though there is a rich applied literature on Bayesian inference for the POT, the asymptotic theory for such proposals…

Statistics Theory · Mathematics 2025-04-01 Clément Dombry , Simone A. Padoan , Stefano Rizzelli

For a flat universe presently dominated by smooth energy, either cosmological constant (LCDM) or quintessence (QCDM), we calculate the asymptotic collapsed mass fraction as function of the present ratio of smooth energy to matter energy…

Astrophysics · Physics 2009-10-31 Sidney Bludman , Matts Roos

One of the presuppositions of science since the times of Galileo, Newton, Laplace, and Descartes has been the predictability of the world. This idea has strongly influenced scientific and technological models. However, in recent decades,…

Adaptation and Self-Organizing Systems · Physics 2011-12-19 Carlos Gershenson

For a Bayesian, real-time forecasting with the posterior predictive distribution can be challenging for a variety of time series models. First, estimating the parameters of a time series model can be difficult with sample-based approaches…

Applications · Statistics 2022-08-08 Taylor R. Brown

Two 2025 publications, "AI 2027" (Kokotajlo et al., 2025) and "If Anyone Builds It, Everyone Dies" (Yudkowsky & Soares, 2025), assert that superintelligent artificial intelligence will almost certainly destroy or render humanity obsolete…

Computers and Society · Computer Science 2025-12-05 Mohamed El Louadi

This paper investigates anthropic bounds on the vacuum energy $\Lambda$. We first consider the possibility of cosmic observers existing at any random time (including the future) for constant $\Lambda$, and take into account the suppression…

General Relativity and Quantum Cosmology · Physics 2009-01-22 L. Mersini-Houghton , F. Adams

The goal of the article is to explore what is the most probable type of simulation in which humanity lives (if any) and how this affects simulation termination risks. We firstly explore the question of what kind of simulation in which…

Other Computer Science · Computer Science 2019-05-16 Alexey Turchin , Michael Batin , David Denkenberger , Roman Yampolskiy

We explore the notion of uncertainty in the context of modern abstractive summarization models, using the tools of Bayesian Deep Learning. Our approach approximates Bayesian inference by first extending state-of-the-art summarization models…

Computation and Language · Computer Science 2022-05-04 Alexios Gidiotis , Grigorios Tsoumakas

Life appears to have emerged relatively quickly on the Earth, a fact sometimes used to justify a high rate of spontaneous abiogenesis ($\lambda$) among Earth-like worlds. Conditioned upon a single datum - the time of earliest evidence for…

Earth and Planetary Astrophysics · Physics 2018-12-26 Jingjing Chen , David Kipping

The future evolution of the universe suggested by the cosmological model proposed earlier at this meeting by the authors is explored. The fundamental role played by the positive "cosmological constant" is emphasized. Dyson's 1979 paper…

General Physics · Physics 2007-05-23 H. Pierre Noyes , James Lindesay

We demonstrate that the principle of maximum relative entropy (ME), used judiciously, can ease the specification of priors in model selection problems. The resulting effect is that models that make sharp predictions are disfavoured,…

Data Analysis, Statistics and Probability · Physics 2009-12-07 Brendon J. Brewer , Matthew J. Francis

Bayesian nonparametric methods are a popular choice for analysing survival data due to their ability to flexibly model the distribution of survival times. These methods typically employ a nonparametric prior on the survival function that is…

Methodology · Statistics 2022-02-22 Edwin Fong , Brieuc Lehmann
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