LEADER 04981nam 22006375 450 001 9910257446503321 005 20200630213422.0 010 $a3-540-38541-X 024 7 $a10.1007/3-540-09727-9 035 $a(CKB)1000000000778457 035 $a(SSID)ssj0000323907 035 $a(PQKBManifestationID)12116212 035 $a(PQKBTitleCode)TC0000323907 035 $a(PQKBWorkID)10304191 035 $a(PQKB)11253116 035 $a(DE-He213)978-3-540-38541-7 035 $a(PPN)155225154 035 $a(EXLCZ)991000000000778457 100 $a20121227d1980 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aImaging Processes and Coherence in Physics$b[electronic resource] $eProceedings of a workshop, Held at the Centre de Physique, Les Houches, France, March 1979 /$fedited by M. Schlenker, M. Fink, J.-P. Goedgebuer, C. Malgrange, J.-C. Vienot, R. H. Wade 205 $a1st ed. 1980. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1980. 225 1 $aLecture Notes in Physics,$x0075-8450 ;$v112 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-09727-9 327 $aLasers sources -- Lasers as stable frequency sources -- Electron sources -- Intense sources of thermal neutrons for research -- X-ray sources -- Ultrasonic waves and optics -- Imaging processes and coherence in optics -- Propagation of neutron beams -- Coherence of illumination in electron microscopy -- Propagation of sound and ultrasound in non-homogeneous media -- Classical apples and quantum potatoes -- Outline of a coherent theory of skiing -- Wave-matter interactions : A general survey -- Basic X-ray interactions with matter -- Scattering experiments in ultrasonic spectroscopy -- Acousto-optical interactions -- H.F. phonon transmission as a probe of condensed matter -- Infrared detectors infrared imaging systems -- The elastic scattering of fast electrons -- Inelastic electron scattering -- Interaction of thermal neutrons with matter -- Structure information retrieval from solution X-ray and neutron scattering experiments -- Guided waves propagation and integrated optics -- Prospects for long-wavelength X-ray microscopy and diffraction -- Kinematical and dynamical diffraction theories -- Dynamical theory of X-ray propagation in distorted crystals -- Polarization phenomena in X-ray diffraction -- Perfect crystal neutron optics -- Coherent approach to neutron beam polarization -- X-ray and neutron interferometry -- X-ray topography : Principles -- Examples of X-ray topographic results -- Neutron topography -- Crystal diffraction optics for x-rays and neutrons -- Electron imaging techniques -- Speckle and intensity interferometry. Applications to astronomy -- Electron holography -- Prospects of X-ray holography -- Imageing by means of channelled particles -- Neutron optics using non-perfect crystals -- Ultrasonic real-time reconstruction imaging -- What can be done with high voltage electron microscopy? -- Transfer functions and electron microscope image formation -- Acoustic microscopy -- Use of coded apertures in gamma-imaging techniques -- Principles and techniques of acoustical imaging -- NMR imaging -- Nuclear scattering radiography -- Computerized tomography scanners -- Recording materials and transducers in optics -- Some applications in hybrid image processing -- X-ray image detectors -- Electron detectors -- Image processing of regular biological objects -- Cathodoluminescence topography -- Image processing in electron microscopy : Non-periodic objects -- Interpretation of X-Ray topography -- ?Coherence is beautiful?. 410 0$aLecture Notes in Physics,$x0075-8450 ;$v112 606 $aOptics 606 $aElectrodynamics 606 $aLasers 606 $aPhotonics 606 $aClassical Electrodynamics$3https://scigraph.springernature.com/ontologies/product-market-codes/P21070 606 $aOptics, Lasers, Photonics, Optical Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/P31030 615 0$aOptics. 615 0$aElectrodynamics. 615 0$aLasers. 615 0$aPhotonics. 615 14$aClassical Electrodynamics. 615 24$aOptics, Lasers, Photonics, Optical Devices. 676 $a535.2 676 $a537.6 702 $aSchlenker$b M$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFink$b M$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGoedgebuer$b J.-P$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMalgrange$b C$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVienot$b J.-C$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWade$b R. H$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910257446503321 996 $aImaging processes and coherence in physics$91118622 997 $aUNINA LEADER 04037nam 22005535 450 001 9910861088903321 005 20260323115143.0 010 $a3-031-53282-1 024 7 $a10.1007/978-3-031-53282-5 035 $a(CKB)32027758500041 035 $a(MiAaPQ)EBC31342491 035 $a(Au-PeEL)EBL31342491 035 $a(DE-He213)978-3-031-53282-5 035 $a(OCoLC)1434170237 035 $a(EXLCZ)9932027758500041 100 $a20240514d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProbability and Statistics for Machine Learning $eA Textbook /$fby Charu C. Aggarwal 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (530 pages) 225 0 $aMathematics and Statistics Series 311 08$a3-031-53281-3 327 $aChapter. 1. Probability and Statistics: An Introduction -- Chapter. 2. Summarizing and Visualizing Data -- Chapter. 3. Probability Basics and Random Variables -- Chapter. 4. Probability Distributions -- Chapter. 5. Hypothesis Testing and Confidence Intervals -- Chapter. 6. Reconstructing Probability Distributions from Data -- Chapter. 7. Regression -- Chapter. 8. Classification: A Probabilistic View -- Chapter. 9. Unsupervised Learning: A Probabilistic View -- Chapter. 10. Discrete State Markov Processes -- Chapter. 11. Probabilistic Inequalities and Extreme Value Analysis -- Bibliography -- Index. 330 $aThis book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories: 1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its relationship to machine learning. The fundamentals of probability and statistics are covered in Chapters 2 through 5. 2. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters. 3. Advanced topics: Chapter 10 is devoted to discrete-state Markov processes. It explores the application of probability and statistics to a temporal and sequential setting, although the applications extend to more complex settings such as graphical data. Chapter 11 covers a number of probabilistic inequalities and approximations. The style of writing promotes the learning of probability and statistics simultaneously with a probabilistic perspective on the modeling of machine learning applications. The book contains over 200 worked examples in order to elucidate key concepts. Exercises are included both within the text of the chapters and at the end of the chapters. The book is written for a broad audience, including graduate students, researchers, and practitioners. 606 $aMachine learning 606 $aMachine Learning 606 $aProbabilitats$2thub 606 $aEstadística$2thub 606 $aAprenentatge automàtic$2thub 608 $aLlibres electrònics$2thub 615 0$aMachine learning. 615 14$aMachine Learning. 615 7$aProbabilitats 615 7$aEstadística 615 7$aAprenentatge automàtic 676 $a006.31 700 $aAggarwal$b Charu C$0518673 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910861088903321 996 $aProbability and Statistics for Machine Learning$94163262 997 $aUNINA