Results 201 to 210 of about 26,939 (224)

Inference of a continuous auto-regressive model for the forecasting of nonstationary stochastic processes deriving from energy demand in electrical networks

Proceedings of 8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications (MELECON 96), 2002
This paper discusses the application of Hilbertian auto regressive models to medium term forecasting of electric energy demand, that is, one week-ahead prediction. These models are aimed at predicting whole future trajectories of continuous stochastic processes and can be useful in order to forecast not only the aggregate figures of energy demand (e.g.,
Cavallini A., Mazzanti G., Montanari G. C.   +2 more
openaire   +2 more sources

Stochastic models for semantic parsing, multi-faceted topic discovery, and causal event inference: Perspectives from natural language processing

2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011
In this talk I will address three important problems in Natural Language Processing with direct relevance to Image Understanding: Semantic Parsing, Multi-Faceted Topic Discovery, and Causal Event Inference.
openaire   +1 more source

Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes

Journal of Computational Physics, 2022
David J Warne, Thomas P Prescott, Ruth E Baker   +2 more
exaly  

Semiparametric and Nonparametric Inference from Irregular Observations on Continuous Time Stochastic Processes

1991
J. M. Stoyanov, P. M. Robinson
openaire   +1 more source

Innovation Representation of Stochastic Processes With Application to Causal Inference

IEEE Transactions on Information Theory, 2020
Amichai Painsky, Saharon Rosset, Meir Feder   +2 more
exaly  

Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis

Journal of Computational Physics, 2021
Agnieszka Borowska, Diana Giurghita, Dirk Husmeier   +2 more
exaly  

Parametric inference for stochastic differential equations driven by a mixed fractional Brownian motion with random effects based on discrete observations

Stochastic Analysis and Applications, 2022
B L S Prakasa Rao
exaly  

Statistical Inference from Stochastic Processes

1988
openaire   +1 more source

Bayesian inference for non-Gaussian Ornstein-Uhlenbeck stochastic volatility processes

Journal of the Royal Statistical Society Series B: Statistical Methodology, 2004
Omiros Papaspiliopoulos, Petros Dellaportas   +1 more
exaly  

Analyzing Social Networks as Stochastic Processes

Journal of the American Statistical Association, 1980
Stanley Wasserman
exaly   +2 more sources