Statistical Analysis Techniques in Particle Physics - Fits, Density Estimation and Supervised Learning, Narsky
Автор: Hvitfeldt Emil, Silge Julia Название: Supervised Machine Learning for Text Analysis in R ISBN: 0367554186 ISBN-13(EAN): 9780367554187 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is designed to provide practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate text into their modeling pipelines. We assume that the reader is somewhat familiar with R, predictive modeling concepts for non-text data, and the tidyverse family of packages.
Автор: Hvitfeldt Emil, Silge Julia Название: Supervised Machine Learning for Text Analysis in R ISBN: 0367554194 ISBN-13(EAN): 9780367554194 Издательство: Taylor&Francis Рейтинг: Цена: 7961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is designed to provide practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate text into their modeling pipelines. We assume that the reader is somewhat familiar with R, predictive modeling concepts for non-text data, and the tidyverse family of packages.
Название: Combinatorial Methods in Density Estimation ISBN: 1461265274 ISBN-13(EAN): 9781461265276 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths.
Автор: P.P.B. Eggermont; V.N. LaRiccia Название: Maximum Penalized Likelihood Estimation ISBN: 1441929282 ISBN-13(EAN): 9781441929280 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints.
Описание: This thesis presents analytical theoretical studies on the interplay between charge density waves (CDW) and superconductivity (SC) in the actively studied transition-metal dichalcogenide 1T-TiSe2. It begins by reapproaching a years-long debate over the nature of the phase transition to the commensurate CDW (CCDW) state and the role played by the intrinsic tendency towards excitonic condensation in this system. A Ginzburg-Landau phenomenological theory was subsequently developed to understand the experimentally observed transition from commensurate to incommensurate CDW (ICDW) order with doping or pressure, and the emergence of a superconducting dome that coexists with ICDW. Finally, to characterize microscopically the effects of the interplay between CDW and SC, the spectrum of CDW fluctuations beyond mean-field was studied in detail. In the aggregate, the work reported here provides an encompassing understanding of what are possibly key microscopic underpinnings of the CDW and SC physics in TiSe2.
Автор: Luo Название: Properties of QCD Matter at High Baryon Density ISBN: 9811944407 ISBN-13(EAN): 9789811944406 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book highlights the discussions by renown researchers on questions emerged during transition from the relativistic heavy-ion collider (RHIC) to the future electron ion collider (EIC). Over the past two decades, the RHIC has provided a vast amount of data over a wide range of the center of mass energies. What are the scientific priorities, after RHIC is shut down and turned to the future EIC? What should be the future focuses of the high-energy nuclear collisions? What are thermodynamic properties of quantum chromodynamics (QCD) at large baryon density? Where is the phase boundary between quark-gluon-plasma and hadronic matter at high baryon density? How does one make connections from thermodynamics learned in high-energy nuclear collisions to astrophysical topics, to name few, the inner structure of compact stars, and perhaps more interestingly, the dynamical processes of the merging of neutron stars? While most particle physicists are interested in Dark Matter, we should focus on the issues of Visible Matter! Multiple heavy-ion accelerator complexes are under construction: NICA at JINR (4 ~ 11 GeV), FAIR at GSI (2 ~ 4.9 GeV SIS100), HIAF at IMP (2 ~ 4 GeV). In addition, the heavy-ion collision has been actively discussed at the J-PARC. The book is a collective work of top researchers from the field where some of the above-mentioned basic questions will be addressed. We believe that answering those questions will certainly advance our understanding of the phase transition in early universe as well as its evolution that leads to today's world of nature.
Описание: This volume records the proceedings of a Forum on The Fundamentals of Electron Density, Density Matrix and Density Functional Theory in Atoms, Molecules and the Solid State held at the Coseners` House, Abingdon-on-Thames, Oxon.
Автор: Viraht Sahni Название: Quantal Density Functional Theory ISBN: 3642074197 ISBN-13(EAN): 9783642074196 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Density functional theory is an important and widely used tool in many-body physics that has found applications in atomic, molecular, solid-state and nuclear physics.
Автор: Maria Schuld; Francesco Petruccione Название: Supervised Learning with Quantum Computers ISBN: 303007188X ISBN-13(EAN): 9783030071882 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.
Автор: Silverman, Bernard. W. Название: Density Estimation for Statistics and Data Analysis ISBN: 0412246201 ISBN-13(EAN): 9780412246203 Издательство: Taylor&Francis Рейтинг: Цена: 20671.00 р. Наличие на складе: Нет в наличии.
Автор: Scrucca, Luca Fraley, Chris Murphy, T. Brendan Adrian E., Raftery Название: Model-based clustering, classification, and density estimation using mclust in r ISBN: 1032234954 ISBN-13(EAN): 9781032234953 Издательство: Taylor&Francis Рейтинг: Цена: 8114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling.
Автор: P.P.B. Eggermont; V.N. LaRiccia Название: Maximum Penalized Likelihood Estimation ISBN: 0387952683 ISBN-13(EAN): 9780387952680 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints such as unimodality and log-concavity. This book focuses on convexity and convex optimization, as applied to maximum penalized likelihood estimation.
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