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Advances in Mathematical Sciences : AWM Research Symposium, Houston, TX, April 2019 / Bahar Acu ... [et al.] editors
| Advances in Mathematical Sciences : AWM Research Symposium, Houston, TX, April 2019 / Bahar Acu ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xiii, 369 p. : ill. ; 24 cm |
| Soggetto topico |
13-XX - Commutative algebra [MSC 2020]
35-XX - Partial differential equations [MSC 2020] 65-XX - Numerical analysis [MSC 2020] 05-XX - Combinatorics [MSC 2020] 60-XX - Probability theory and stochastic processes [MSC 2020] 54-XX - General topology [MSC 2020] 00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020] 97-XX - Mathematics education [MSC 2020] |
| Soggetto non controllato |
Algebraic Combinatorics
Algebraic biology Braid Groups Combinatorics Data science Education research Ensemble Kalman filter Higher order elliptic problems Math education Noncommutative algebra Parameter Estimation Patricle methods Periodic parameters Professional development Quantum symmetry School and district support Sequential Monte Carlo Student enrichment programs Symplectic and contact topology Uncertainty Quantification |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0248597 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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An Introduction to Sequential Monte Carlo / Nicolas Chopin, Omiros Papaspiliopoulos
| An Introduction to Sequential Monte Carlo / Nicolas Chopin, Omiros Papaspiliopoulos |
| Autore | Chopin, Nicolas |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xxvi, 559 p. : ill. ; 24 cm |
| Altri autori (Persone) | Papaspiliopoulos, Omiros |
| Soggetto topico |
65C05 - Monte Carlo methods [MSC 2020]
62-XX - Statistics [MSC 2020] 62M05 - Markov processes: estimation; hidden Markov models [MSC 2020] 62L12 - Sequential estimation [MSC 2020] |
| Soggetto non controllato |
Bayesian Inference
Data-driven science, modeling and theory building Feynman-Kac models Hidden Markov models Markov Chain Monte Carlo Particle filter Sequential Monte Carlo Sequential learning State-space models |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0248680 |
Chopin, Nicolas
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| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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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 electronic resource (508 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
bifurcation
dynamical systems Edward–Sokal coupling mean-field Kullback–Leibler divergence variational inference Bayesian statistics machine learning variational approximations PAC-Bayes expectation-propagation Markov chain Monte Carlo Langevin Monte Carlo sequential Monte Carlo Laplace approximations approximate Bayesian computation Gibbs posterior MCMC stochastic gradients neural networks Approximate Bayesian Computation differential evolution Markov kernels discrete state space ergodicity Markov chain probably approximately correct variational Bayes Bayesian inference Markov Chain Monte Carlo Sequential Monte Carlo Riemann Manifold Hamiltonian Monte Carlo integrated nested laplace approximation fixed-form variational Bayes stochastic volatility network modeling network variability Stiefel manifold MCMC-SAEM data imputation Bethe free energy factor graphs message passing variational free energy variational message passing approximate Bayesian computation (ABC) differential privacy (DP) sparse vector technique (SVT) Gaussian particle flow variable flow Langevin dynamics Hamilton Monte Carlo non-reversible dynamics control variates thinning meta-learning hyperparameters priors online learning online optimization gradient descent statistical learning theory PAC–Bayes theory deep learning generalisation bounds Bayesian sampling Monte Carlo integration PAC-Bayes theory no free lunch theorems sequential learning principal curves data streams regret bounds greedy algorithm sleeping experts entropy robustness statistical mechanics complex systems |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576874903321 |
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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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Bayesian Inference of State Space Models : Kalman Filtering and Beyond / Kostas Triantafyllopoulos
| Bayesian Inference of State Space Models : Kalman Filtering and Beyond / Kostas Triantafyllopoulos |
| Autore | Triantafyllopoulos, Kostas |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | xv, 495 p. : ill. ; 24 cm |
| Soggetto non controllato |
Bayesian estimation
Bayesian forecasting Control theory Dynamic models Financial Time Series Non Gaussian time series Sequential Monte Carlo State space in dynamic systems State-space models Stochastic volatility Systems stability Volatility models |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0274587 |
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Triantafyllopoulos, Kostas
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| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Monte Carlo and quasi-Monte Carlo methods : MCQMC 2018, Rennes, France, July 1–6 / Bruno Tuffin, Pierre L'Ecuyer editors
| Monte Carlo and quasi-Monte Carlo methods : MCQMC 2018, Rennes, France, July 1–6 / Bruno Tuffin, Pierre L'Ecuyer editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 539 p. : ill. ; 24 cm |
| Soggetto topico |
65-XX - Numerical analysis [MSC 2020]
65C05 - Monte Carlo methods [MSC 2020] 00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020] |
| Soggetto non controllato |
Bayesian computation
Computational complexity Cubature Discrepancy Graphical Rendering Importance Sampling Lattice Rules Markov Chain Monte Carlo Monte Carlo Multilevel Monte Carlo Probabilistic Numerics Quadrature Quasi-Monte Carlo Sequential Monte Carlo Simulation Stochastic Computation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0249520 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Monte Carlo and quasi-Monte Carlo methods : MCQMC 2016, Stanford, CA, August 14-19 / Art B. Owen, Peter W. Glynn editors
| Monte Carlo and quasi-Monte Carlo methods : MCQMC 2016, Stanford, CA, August 14-19 / Art B. Owen, Peter W. Glynn editors |
| Pubbl/distr/stampa | Cham, : Springer, 2018 |
| Descrizione fisica | xi, 479 p. : ill. ; 24 cm |
| Soggetto topico |
68Uxx - Computing methodologies and applications [MSC 2020]
91Gxx - Actuarial science and mathematical finance [MSC 2020] 65Nxx - Numerical methods for partial differential equations, boundary value problems [MSC 2020] 65Y20 - Complexity and performance of numerical algorithms [MSC 2020] 65D32 - Numerical quadrature and cubature formulas [MSC 2020] 52C07 - Lattices and convex bodies in $n$ dimensions (aspects of discrete geometry) [MSC 2020] 65Cxx - Probabilistic methods, stochastic differential equations [MSC 2020] 68Q17 - Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.) [MSC 2020] 65Rxx - Numerical methods for integral equations, integral transforms [MSC 2020] |
| Soggetto non controllato |
Bayesian computation
Computational complexity Cubature Discrepancy Graphical Rendering Importance Sampling Lattice Rules Markov Chain Monte Carlo Monte Carlo Multilevel Monte Carlo Probabilistic Numerics Quadrature Quasi-Monte Carlo Sequential Monte Carlo Simulation Stochastic Computation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0124877 |
| Cham, : Springer, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Monte Carlo Methods / Adrian Barbu, Song-Chun Zhu
| Monte Carlo Methods / Adrian Barbu, Song-Chun Zhu |
| Autore | Barbu, Adrian |
| Pubbl/distr/stampa | Singapore, : Springer, 2020 |
| Descrizione fisica | xvi, 422 p. : ill. ; 24 cm |
| Altri autori (Persone) | Zhu, Song-Chun |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
65-XX - Numerical analysis [MSC 2020] 65C05 - Monte Carlo methods [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62-XX - Statistics [MSC 2020] 62J12 - Generalized linear models (logistic models) [MSC 2020] 62J10 - Analysis of variance and covariance (ANOVA) [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] 62G08 - Nonparametric regression and quantile regression [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Computer Graphics Computer vision Data Driven Markov Chain Monte Carlo Energy Landscape Mapping Gibbs Sampler Hamiltonian Monte Carlo Langevin Monte Carlo Machine learning Markov Chain Monte Carlo Metropolis-Hastings Monte Carlo Methods Sequential Monte Carlo Stochastic Gradient Descent Swendsen-Wang Cuts |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0250212 |
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Barbu, Adrian
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| Singapore, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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