Stable count distribution

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

The Antarctic Wind Atlas provides a high-resolution assessment of wind resource statistics across Antarctica. As climate concerns and the logistic costs of fuel in Antarctica rise, many research stations are looking to expand their renewable energy portfolios. Wind energy is a particularly promising option, with tens of wind turbines already operating on the continent. However, identifying suitable locations for these projects remains difficult due to the lack of reliable wind statistics. Utilizing 15 years

Social Learning is a decentralized decision-making paradigm in which spatially dispersed agents collect streaming observations regulated by one of a finite number of models (the hypotheses). The agents are interested in assigning probability scores (the beliefs) to the possible hypotheses. To this end, the agents exchange their beliefs according to a certain communication graph. It has been shown that, under reasonable conditions on the identifiability of the decision model and the network connectivity, eac

Using (2712.4 +/- 14.3) x 10(6) psi(3686) events collected by the BESIII detector operating at the BEPCII collider, we present the first observations of the decays chi(cJ) (J = 0, 1, 2) -> p (p) over bar eta pi(0). Their decay branching fractions are determined to be B(chi(c0) -> p (p) over bar eta pi(0)) = (2.42 +/- 0.07 +/- 0.19) x 10(-4), B(chi(c1) -> p (p) over bar eta pi(0)) = (1.95 +/- 0.05 +/- 0.12) x 10(-4), and B(chi(c2) -> p (p) over bar eta pi(0)) = (1.33 +/- 0.05 +/- 0.08) x 10(-4), where the fi

Learning with identical train and test distributions has been extensively investigated both practically and theoretically. Much remains to be understood, however, in statistical learning under distribution shifts. This paper focuses on a distribution shift setting where train and test distributions can be related by classes of (data) transformation maps. We initiate a theoretical study for this framework, investigating learning scenarios where the target class of transformations is either known or unknown.

Using a data sample of 106 million psi(3686) events collected with the BESIII detector operated at the BEPCII storage ring, we study for the first time the decays chi(cJ) -> phi(KSK +/-)-K-0 pi(-/+) and chi(cJ) -> phi K+K-pi(0) in the E1 radiative transiti ...

We report on the outcomes of a lysimeter experiment aimed at the measurement of travel time distributions of water and certain nonreactive solutes under non-stationary conditions to examine the kinematics of age mixing. In order to simulate the release of a compound in a receiving water body, it is common in hydrology to attribute a travel time probability distribution to each particle, which reflects the response of a catchment unit to a solute input. Hence, the concentration measured at a control section

The subject of the present thesis is an optimal prediction problem concerning the ultimate maximum of a stable Lévy process over a finite interval of time. Such "optimal prediction" problems are of both theoretical and practical interest, in particular the ...

We describe a new family of scaling functions, the (α, τ)-fractional splines, which generate valid multiresolution analyses. These functions are characterized by two real parameters: α, which controls the width of the scaling functions; and τ, which specifies their position with respect to the grid (shift parameter). This new family is complete in the sense that it is closed under convolutions and correlations. We give the explicit time and Fourier domain expressions of these fractional splines. We prove th

Stable count distribution

Chat with Graph Search

Antarctic Wind Atlas: Gradient-Boosting based Quantile Mapping on 15 years of Climatological Reanalysis

Performance Evaluation of Social Learning

Measurement of the Branching Fraction for the Decay Χcj → p(p)over-barηπ0

Transformation-invariant Learning and Theoretical Guarantees for Ood Generalization

Study of chi(cJ) decaying into phi K*(892)(K)over-bar

Non-stationarity of solute travel time distribution observed in a controlled hydrologic transport volume

An optimal prediction problem in financial modelling

A Complete Family of Scaling Functions: The (α, τ)-Fractional Splines