This is the first part of a three-note study which starts from an analysis of "probabilities of probabilities" to arrive at old and new state-assignment methods in classical and quantum mechanics. In this note, probability-like parameters appearing in some statistical models, and their prior distributions, are reinterpreted through the notion of 'circumstance'. The idea is basically Laplace's and Jaynes', and rests on a theorem from probability theory which shows that a set of propositions can be uniquely parametrised by probability distributions. This parametrisation is invariant with respect to changes in the probabilities of the propositions themselves
Bayesian personalism models learning from experience as the updating of an agent's credence function...
Understanding the core content of quantum mechanics requires us to disentangle the hidden logical re...
An approach to induction is presented, based on the idea of analysing the context of a given problem...
The discipline usually called `probability theory' can be seen as the theory which describes and set...
Probability-like parameters appearing in some statistical models, and their prior distributions, are...
Quantum mechanics is basically a mathematical recipe on how to construct physical models. Historical...
This paper offers examples of concrete numerical applications of Bayesian quantum-state-assignment m...
Purpose – The purpose of this paper is to explore extant distinctions between plausibility and prob...
In the Bayesian approach to quantum mechanics, probabilities--and thus quantum states--represent an ...
Is quantum mechanics about ‘states’? Or is it basically another kind of probability theory? It is ar...
The conspicuous similarities between interpretive strategies in classical statistical mechanics and ...
Is quantum mechanics about ‘states’? Or is it basically another kind of probability theory? It is ar...
We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is...
Everettian quantum mechanics faces the challenge of how to make sense of probability and probabilist...
In classical physics, probabilistic or statistical knowledge has been always related to ignorance or...
Bayesian personalism models learning from experience as the updating of an agent's credence function...
Understanding the core content of quantum mechanics requires us to disentangle the hidden logical re...
An approach to induction is presented, based on the idea of analysing the context of a given problem...
The discipline usually called `probability theory' can be seen as the theory which describes and set...
Probability-like parameters appearing in some statistical models, and their prior distributions, are...
Quantum mechanics is basically a mathematical recipe on how to construct physical models. Historical...
This paper offers examples of concrete numerical applications of Bayesian quantum-state-assignment m...
Purpose – The purpose of this paper is to explore extant distinctions between plausibility and prob...
In the Bayesian approach to quantum mechanics, probabilities--and thus quantum states--represent an ...
Is quantum mechanics about ‘states’? Or is it basically another kind of probability theory? It is ar...
The conspicuous similarities between interpretive strategies in classical statistical mechanics and ...
Is quantum mechanics about ‘states’? Or is it basically another kind of probability theory? It is ar...
We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is...
Everettian quantum mechanics faces the challenge of how to make sense of probability and probabilist...
In classical physics, probabilistic or statistical knowledge has been always related to ignorance or...
Bayesian personalism models learning from experience as the updating of an agent's credence function...
Understanding the core content of quantum mechanics requires us to disentangle the hidden logical re...
An approach to induction is presented, based on the idea of analysing the context of a given problem...