For reaction-diffusion processes without exclusion, in which the particles can exist in the same site of a one-dimensional lattice, we study all the integrable models which can be obtained by imposing a boundary condition on the master equation of the asymmetric diffusion process. The annihilation process is also added. The Bethe ansatz solution and the exact N-particle conditional probabilitie...

Three-valued accounts of conditionals frequently promise (a) to conform to the probabilistic view that conditionals are evaluated by conditional probabilities, and (b) to yield a plausible account of compounds of conditionals. However, McGee (1981) shows that probabilistic validity, the conception of validity most naturally associated with the probabilistic view, cannot be characterized by a fi...

Recent research into seasonal climate prediction has focused on combining multiple atmospheric general circulation models (GCMs) to develop multimodel ensembles. A new approach to combining multiple GCMs is proposed by analyzing the skill levels of candidate models contingent on the relevant predictor(s) state. To demonstrate this approach, historical simulations of winter (December–February, D...

Probabilistic databases compute the success probabilities of queries. We introduce the problem of learning the parameters of the probabilistic database ProbLog. Given the observed success probabilities of a set of queries, we compute the probabilities attached to facts that have a low approximation error on the training data as well as on unseen examples. Assuming Gaussian error terms on the ob...

Random Boolean networks (RBNs) were proposed as a model of genetic regulatory networks by Kauffman in 1969. This paper addresses the stability of cycles of RBNs and Boolean networks. In particular we define the error probabilities of cycle states as the probability of leaving a cycle after a randomly occurring error. Therefore, we introduce the weight distributions, which are usually used to an...

The threshold region mean squared error (MSE) performance of the Capon-MVDR algorithm is predicted via an adaptation of an interval error based method referred to herein as the method of interval errors (MIE). MIE requires good approximations of two quantities: (i) interval error probabilities, and (ii) the algorithm asymptotic (SNR→ ∞) MSE performance. Exact pairwise error probabilities for th...

We propose a novel confidence measure based on the marginalization of jointly estimated error cause probabilities. Conventional confidence measures directly score the reliability of recognition results. In contrast, our method first calculates joint confidence and error cause probabilities and then sums them with respect to the error cause patterns to obtain the marginal confidence probability....

1 Introduction Suppose that n individuals, labeled 1,..., n 9 wish to assign consensual probabilities to a sequence of events E u ..., E k which partition some set of possibilities. Let their subjective assignments be registered in an n x k matrix P = (Pij), where py denotes the subjective probability assigned by individual / to event Ej. The question of how to aggregate the probabilities in P ...