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Approximate Bayesian Inference
| Approximate Bayesian Inference |
| Autore | Alquier Pierre |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (508 p.) |
| Soggetto topico |
Mathematics and Science
Research and information: general |
| Soggetto non controllato |
approximate Bayesian computation
Approximate Bayesian Computation approximate Bayesian computation (ABC) Bayesian inference Bayesian sampling Bayesian statistics Bethe free energy bifurcation complex systems control variates data imputation data streams deep learning differential evolution differential privacy (DP) discrete state space dynamical systems Edward-Sokal coupling entropy ergodicity expectation-propagation factor graphs fixed-form variational Bayes Gaussian generalisation bounds Gibbs posterior gradient descent greedy algorithm Hamilton Monte Carlo hyperparameters integrated nested laplace approximation Kullback-Leibler divergence Langevin dynamics Langevin Monte Carlo Laplace approximations machine learning Markov chain Markov chain Monte Carlo Markov Chain Monte Carlo Markov kernels MCMC MCMC-SAEM mean-field message passing meta-learning Monte Carlo integration network modeling network variability neural networks no free lunch theorems non-reversible dynamics online learning online optimization PAC-Bayes PAC-Bayes theory particle flow principal curves priors probably approximately correct regret bounds Riemann Manifold Hamiltonian Monte Carlo robustness sequential learning sequential Monte Carlo Sequential Monte Carlo sleeping experts sparse vector technique (SVT) statistical learning theory statistical mechanics Stiefel manifold stochastic gradients stochastic volatility thinning variable flow variational approximations variational Bayes variational free energy variational inference variational message passing |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576874903321 |
Alquier Pierre
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Overcoming Data Scarcity in Earth Science
| Overcoming Data Scarcity in Earth Science |
| Autore | Etcheverry Venturini Lorena |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (94 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
3D-Var
arthropod vector attribute reduction climate extreme indices (CEIs) ClimPACT core attribute data assimilation data imputation data quality data scarcity Dataset Licensedatabase decision trees earth-science data ensemble learning environmental modeling environmental observations Expert Team on Climate Change Detection and Indices (ETCCDI) Expert Team on Sector-specific Climate Indices (ET-SCI) geophysical monitoring GLDAS invasive species k-Nearest Neighbors machine learning magnetotelluric monitoring microhabitat missing data multi-class classification processing remote sensing rough set theory rule extraction soil texture calculator species distribution modeling statistical methods support vector machines water quality |
| ISBN | 3-03928-211-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404080803321 |
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Etcheverry Venturini Lorena
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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