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In this work, we investigate an optimization problem over adapted couplings between pairs of real valued random variables, possibly describing random times. We relate those couplings to a specific class of causal transport plans between…

Probability · Mathematics 2022-10-18 Rémi Lassalle

In this paper we obtain some possibilistic variants of the probabilistic laws of large numbers, different from those obtained by other authors, but very natural extensions of the corresponding ones in probability theory. Our results are…

Probability · Mathematics 2020-09-15 Sorin G. Gal

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

In this paper we deal with a new approach to probabilistic reasoning in a logical framework. Nearly almost all logics of probability that have been proposed in the literature are based on classical two-valued logic. After making clear the…

Artificial Intelligence · Computer Science 2013-02-21 Petr Hajek , Lluis Godo , Francesc Esteva

Probabilistic frames are a generalization of finite frames into the Wasserstein space of probability measures with finite second moment. We introduce new probabilistic definitions of duality, analysis, and synthesis and investigate their…

Functional Analysis · Mathematics 2017-05-03 Clare Wickman , Kasso Okoudjou

These lecture notes highlight the mathematical and computational structure relating to the formulation of, and development of algorithms for, the Bayesian approach to inverse problems in differential equations. This approach is fundamental…

Probability · Mathematics 2015-07-03 Masoumeh Dashti , Andrew M. Stuart

Traditionally, the MaxEnt workshops start by a tutorial day. This paper summarizes my talk during 2001'th workshop at John Hopkins University. The main idea in this talk is to show how the Bayesian inference can naturally give us all the…

Data Analysis, Statistics and Probability · Physics 2009-11-07 Ali Mohammad-Djafari

This paper examines some methods and ideas underlying the author's successful probabilistic learning systems(PLS), which have proven uniquely effective and efficient in generalization learning or induction. While the emerging principles are…

Artificial Intelligence · Computer Science 2013-04-15 Larry Rendell

If a person looks at WHITE paper through BLUE glasses, the paper will become BLUE in the eye of the person. Likewise, in the current study of big data which play the same role as the white paper being looked at, various statistical methods…

Data Analysis, Statistics and Probability · Physics 2014-12-23 J. P. Huang

Data clustering, including problems such as finding network communities, can be put into a systematic framework by means of a Bayesian approach. The application of Bayesian approaches to real problems can be, however, quite challenging. In…

Data Analysis, Statistics and Probability · Physics 2008-09-28 Alexei Vazquez

Archetypal analysis represents a set of observations as convex combinations of pure patterns, or archetypes. The original geometric formulation of finding archetypes by approximating the convex hull of the observations assumes them to be…

Machine Learning · Statistics 2014-04-08 Sohan Seth , Manuel J. A. Eugster

In the Bayesian approach to probability theory, probability quantifies a degree of belief for a single trial, without any a priori connection to limiting frequencies. In this paper we show that, despite being prescribed by a fundamental…

Quantum Physics · Physics 2009-11-07 Carlton M. Caves , Christopher A. Fuchs , Ruediger Schack

In this short essay, we show how computer experiments, and especially visualization, allowed for the investigation and discovery of phenomena which would have passed unnoticed. We shall also highlight the importance of interactivity between…

History and Overview · Mathematics 2022-03-22 J. -R. Chazottes , M. Monticelli

These lectures deal with the problem of inductive inference, that is, the problem of reasoning under conditions of incomplete information. Is there a general method for handling uncertainty? Or, at least, are there rules that could in…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Ariel Caticha

In a variety of scientific applications we wish to characterize a physical system using measurements or observations. This often requires us to solve an inverse problem, which usually has non-unique solutions so uncertainty must be…

Geophysics · Physics 2022-05-19 Xin Zhang , Muhammad Atif Nawaz , Xuebin Zhao , Andrew Curtis

It is often claimed that Bayesian methods, in particular Bayes factor methods for hypothesis testing, can deal with optional stopping. We first give an overview, using elementary probability theory, of three different mathematical meanings…

Statistics Theory · Mathematics 2021-03-24 Allard Hendriksen , Rianne de Heide , Peter Grünwald

This project brings music to sight. Music can be a visual masterpiece. Some people naturally experience a visualization of audio - a condition called synesthesia. The type of synesthesia explored is when sounds create colors in the 'mind's…

Multimedia · Computer Science 2020-12-16 Matthew Joseph Adiletta , Oliver Thomas

The availability heuristic is a strategy that people use to make quick decisions but often lead to systematic errors. We propose three ways that visualization could facilitate unbiased decision-making. First, visualizations can alter the…

Human-Computer Interaction · Computer Science 2016-10-11 Evanthia Dimara , Pierre Dragicevic , Anastasia Bezerianos

Visual question answering (VQA) demands simultaneous comprehension of both the image visual content and natural language questions. In some cases, the reasoning needs the help of common sense or general knowledge which usually appear in the…

Computer Vision and Pattern Recognition · Computer Science 2018-11-30 Hui Li , Peng Wang , Chunhua Shen , Anton van den Hengel

Probability theory can be modified in essentially one way while maintaining consistency with the basic Bayesian framework. This modification results in copies of standard probability theory for real, complex or quaternion probabilities.…

High Energy Physics - Theory · Physics 2007-05-23 Saul Youssef