Milena Cuellar ‘Parameter estimation’ Wokingham UK Parameter estimation Abstract” target= “_blank
Milena Cuellar ‘Parameter estimation’, Wokingham, UK. Abstract.
Observational constraints on future climate: distinguishing robust from modeldependent statements o
Observational constraints on future climate: distinguishing robust from model-dependent statements of uncertainty in climate forecasting. Contribution to the IPCC Workshop on Communicating Uncertainty and Risk, County Kildare, Ireland.
CATS members gave various presentations at the EGU st General Assembly Nice France See
CATS members gave various presentations at the EGU 1st General Assembly 2004, Nice, France. See CATS at EGU 2004. WCRP (World Climate Research Programme) Feedback Workshop
Milena Cuellar ‘Parameter estimation of chaotic time series’ London Parameter estimation of chaoti
Milena Cuellar ‘Parameter estimation of chaotic time series’, London. Abstract.
Milena Cuellar ‘Performance of MCMC techniques on surrogate data’ Oxford Performance of MCMC techn
Milena Cuellar ‘Performance of MCMC techniques on surrogate data’, Oxford. Abstract.
Anna Andrianova ‘Ensemble random analog prediction method, testing ERAP using fake weather data’ Sta
Anna Andrianova ‘Ensemble random analog prediction method and testing ERAP using fake weather data’, Statistics Seminar Series, LSE, London. Abstract.
Leonard Smith Kevin Judd, Mark Roulston ‘Indistinguishable States: a unified approach to the analysi
Leonard Smith, Kevin Judd and Mark Roulston ‘Indistinguishable States: a unified approach to the analysis and prediction of dynamical systems given imperfect nonlinear models’, Joint Mathematics Meetings, 15-18 January 2003, Baltimore, Maryland, USA.
AGU Fall Meeting San Francisco USA
AGU Fall Meeting 2002, San Francisco, USA.
_Palmer__DevelopmentOfAEuropeanMultimodel_Artzeit_pubid” target= “_blank” rel=”noopener noreferrer”
DEMETER 2002, Paris.
Milena Cuellar ‘Bayesian Inference for Deterministic Systems’ Oxford Bayesian inference for determ
Milena Cuellar ‘Bayesian Inference for Deterministic Systems’, Oxford. Abstract.
