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Stochastic population growth in spatially heterogeneous environments
Classical ecological theory predicts that environmental stochasticity increases extinction risk by reducing the average per-capita growth rate of populations. To understand the interactive effects of ...
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Identifying and Categorizing Anomalies in Retinal Imaging Data
The identification and quantification of markers in medical images is critical for diagnosis, prognosis and management of patients in clinical practice. Supervised- or weakly supervised training enabl...
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Analysis for Computer Scientists
Foundations, Methods, and Algorithms...
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Massless Spectra of Three Generation U(N) Heterotic String Vacua
We provide the methods to compute the complete massless spectra of a class of recently introduced supersymmetric E8 x E8 heterotic string models which invoke vector bundles with U(N) structure group o...
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Algorithmic Graph Theory and Sage
...
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Intelligent Human Computer Interaction
9th International Conference, IHCI 2017, Evry, France, December 11-13, 2017, Proceedings...
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Data Parallel C++
Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL...
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Signal Computing
Digital Signals in the Software Domain...
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Pre-main sequence binaries with aligned disks ?
We present the results of a study performed with the goal to investigate whether low-mass pre-main sequence binary stars are formed by multiple fragmentation or via stellar capture. If binaries form p...
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Problems in Classical Electromagnetism
157 Exercises with Solutions...
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Pro TBB
C++ Parallel Programming with Threading Building Blocks...
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International Symposium on Mathematics, Quantum Theory, and Cryptography
Proceedings of MQC 2019...
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Software for Exascale Computing - SPPEXA 2016-2019
...
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Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018
Selected Papers from the ICOSAHOM Conference, London, UK, July 9-13, 2018...
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Russia's Turn to the East
Domestic Policymaking and Regional Cooperation...
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Optimizing HPC Applications with Intel Cluster Tools
Hunting Petaflops...
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Minimum Variance Estimation of a Sparse Vector within the Linear Gaussian Model: An RKHS Approach
We consider minimum variance estimation within the sparse linear Gaussian model (SLGM). A sparse vector is to be estimated from a linearly transformed version embedded in Gaussian noise. Our analysis ...
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Developing Graphics Frameworks with Python and OpenGL
...
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Enhanced Living Environments
Algorithms, Architectures, Platforms, and Systems...
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Efficient Learning Machines
Theories, Concepts, and Applications for Engineers and System Designers...
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Digital Video Concepts, Methods, and Metrics
Quality, Compression, Performance, and Power Trade-off Analysis...
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Statistics with Julia
Fundamentals for Data Science, Machine Learning and Artificial Intelligence...
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Representation Learning for Natural Language Processing
...
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Intel Xeon Phi Coprocessor Architecture and Tools
The Guide for Application Developers...
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Clinical Text Mining
Secondary Use of Electronic Patient Records...
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Ionospheric Multi-Spacecraft Analysis Tools
Approaches for Deriving Ionospheric Parameters...
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Biodiversity and Health in the Face of Climate Change
...
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Half-Skyrmion Spin Textures In Polariton Microcavities
We study the polarization dynamics of a spatially expanding polariton condensate under nonresonant linearly polarized optical excitation. The spatially and temporally resolved polariton emission revea...
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Bayesian Methods in the Search for MH370
...
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Programming for Computations - Python
A Gentle Introduction to Numerical Simulations with Python 3.6...
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Linear Selection Indices in Modern Plant Breeding
...
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Health of People, Health of Planet and Our Responsibility
Climate Change, Air Pollution and Health...
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A characterization of the normal distribution using stationary max-stable processes
Consider the max-stable process $\eta(t) = \max_{i\in\mathbb N} U_i \rm{e}^{\langle X_i, t\rangle - \kappa(t)}$, $t\in\mathbb{R}^d$, where $\{U_i, i\in\mathbb{N}\}$ are points of the Poisson process w...
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Optimizing software in C++
An optimization guide for Windows, Linux and Mac platforms...
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Sensor Data Acquisition and Processing Parameters for Human Activity Classification.
This article is from Sensors (Basel, Switzerland) , volume 14 . Abstract It is known that parameter selection for data sampling frequency and segmentation techniques (including different methods and w...
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Interface Oral Health Science 2016
Innovative Research on Biosis–Abiosis Intelligent Interface...
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FM-index for dummies
The FM-index is a celebrated compressed data structure for full-text pattern searching. After the first wave of interest in its theoretical developments, we can observe a surge of interest in practica...
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Physical (A)Causality
Determinism, Randomness and Uncaused Events...
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Finite Difference Computing with PDEs
A Modern Software Approach...
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WZ production beyond NLO for high-pT observables
We use the LoopSim and VBFNLO packages to investigate a merged sample of partonic events that is accurate at NLO in QCD simultaneously for the WZ and WZ+jet production processes. In certain regions of...
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Fractional Graph Theory
A Rational Approach to the Theory of Graphs...
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Fundamentals of Biomechanics
Equilibrium, Motion, and Deformation...
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Programming Computer Vision with Python
Tools and algorithms for analyzing images...
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Spatial Thinking in Planning Practice
An Introduction to GIS...
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Precise Large Deviation Results for Products of Random Matrices
The theorem of Furstenberg and Kesten provides a strong law of large numbers for the norm of a product of random matrices. This can be extended under various assumptions, covering nonnegative as well ...
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Foundations of Quantum Theory
From Classical Concepts to Operator Algebras...
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Survey of vector-like fermion extensions of the Standard Model and their phenomenological implicatio
With the renewed interest in vector-like fermion extensions of the Standard Model, we present here a study of multiple vector-like theories and their phenomenological implications. Our focus is mostly...
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Significant Productivity Improvement of the Baculovirus Expression Vector System by Engineering a No
This article is from PLoS ONE , volume 9 . Abstract Here we describe the development of a baculovirus vector expression cassette containing rearranged baculovirus-derived genetic regulatory elements. ...
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Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth
We present an application of the Layer-wise Relevance Propagation (LRP) algorithm to state of the art deep convolutional neural networks and Fisher Vector classifiers to compare the image perception a...
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Variant Construction from Theoretical Foundation to Applications
...
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Solving PDEs in Python
The FEniCS Tutorial I...
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Frustratingly Short Attention Spans in Neural Language Modeling
Neural language models predict the next token using a latent representation of the immediate token history. Recently, various methods for augmenting neural language models with an attention mechanism ...
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Foundations of Machine Learning
...
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Introduction to Data Science
Data Analysis and Prediction Algorithms with R...
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Error-Correction Coding and Decoding
Bounds, Codes, Decoders, Analysis and Applications...
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Heterotic GUT and Standard Model Vacua from simply connected Calabi-Yau Manifolds
We consider four-dimensional supersymmetric compactifications of the E8 x E8 heterotic string on Calabi-Yau manifolds endowed with vector bundles with structure group SU(N) x U(1) and five-branes. Aft...
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Ward-Green-Takahashi identities and the axial-vector vertex
The colour-singlet axial-vector vertex plays a pivotal role in understanding dynamical chiral symmetry breaking and numerous hadronic weak interactions, yet scant model-independent information is avai...
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Anisotropy Across Fields and Scales
...
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Sensitivity Analysis: Matrix Methods in Demography and Ecology
...
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Performance Bounds for Sparse Parametric Covariance Estimation in Gaussian Models
We consider estimation of a sparse parameter vector that determines the covariance matrix of a Gaussian random vector via a sparse expansion into known "basis matrices". Using the theory of reproducin...
View Book →Foundations of Vector Retrieval
First published in 2024...
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Understanding Machine Learning
From Theory to Algorithms...
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Ambisonics
A Practical 3D Audio Theory for Recording, Studio Production, Sound Reinforcement, and Virtual Reality...
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Language Technologies for the Challenges of the Digital Age
27th International Conference, GSCL 2017, Berlin, Germany, September 13-14, 2017, Proceedings...
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Annotated Algorithms in Python
With applications in Physics, Biology, and Finance...
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Statistical Mechanics of Soft Margin Classifiers
We study the typical learning properties of the recently introduced Soft Margin Classifiers (SMCs), learning realizable and unrealizable tasks, with the tools of Statistical Mechanics. We derive analy...
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Statistical analysis of trajectories on Riemannian manifolds: Bird migration, hurricane tracking and
We consider the statistical analysis of trajectories on Riemannian manifolds that are observed under arbitrary temporal evolutions. Past methods rely on cross-sectional analysis, with the given tempor...
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