
Stochastic Distance Transform
The distance transform (DT) and its many variations are ubiquitous tools...
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Datadriven discovery of PDEs in complex datasets
Many processes in science and engineering can be described by partial di...
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Supervised Classification Methods for Flash Xray single particle diffraction Imaging
Current Flash Xray singleparticle diffraction Imaging (FXI) experiment...
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Fast and Robust Symmetric Image Registration Based on Intensity and Spatial Information
Intensitybased image registration approaches rely on similarity measure...
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Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Approximate inference in probabilistic graphical models (PGMs) can be gr...
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Neural network augmented inverse problems for PDEs
In this paper we show how to augment classical methods for inverse probl...
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Learning Surrogate Models of Document Image Quality Metrics for Automated Document Image Processing
Computation of document image quality metrics often depends upon the ava...
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Is My Model Flexible Enough? InformationTheoretic Model Check
The choice of model class is fundamental in statistical learning and sys...
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A unified deep artificial neural network approach to partial differential equations in complex geometries
We use deep feedforward artificial neural networks to approximate soluti...
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Radial Line Fourier Descriptor for Segmentationfree Handwritten Word Spotting
Automatic recognition of historical handwritten manuscripts is a dauntin...
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Automatic Document Image Binarization using Bayesian Optimization
Document image binarization is often a challenging task due to various f...
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Deriving Probability Density Functions from Probabilistic Functional Programs
The probability density function of a probability distribution is a fund...
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ModelRobust Counterfactual Prediction Method
We develop a method for assessing counterfactual predictions with multip...
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Musical Instrument Recognition Using Their Distinctive Characteristics in Artificial Neural Networks
In this study an Artificial Neural Network was trained to classify music...
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On the construction of probabilistic Newtontype algorithms
It has recently been shown that many of the existing quasiNewton algori...
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Neural CtrlF: Segmentationfree QuerybyString Word Spotting in Handwritten Manuscript Collections
In this paper, we approach the problem of segmentationfree querybystr...
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DataEfficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models
Dataefficient reinforcement learning (RL) in continuous stateaction sp...
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How consistent is my model with the data? InformationTheoretic Model Check
The choice of model class is fundamental in statistical learning and sys...
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Assessing Uncertainties in Xray Singleparticle Threedimensional reconstructions
Modern technology for producing extremely bright and coherent Xray lase...
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A sequential Monte Carlo approach to Thompson sampling for Bayesian optimization
Bayesian optimization through Gaussian process regression is an effectiv...
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A flexible state space model for learning nonlinear dynamical systems
We consider a nonlinear statespace model with the state transition and ...
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System Identification through Online Sparse Gaussian Process Regression with Input Noise
There has been a growing interest in using nonparametric regression met...
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Efficient Computation of the Quasi Likelihood function for Discretely Observed Diffusion Processes
We introduce a simple method for nearly simultaneous computation of all ...
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QuasiNewton particle MetropolisHastings
Particle MetropolisHastings enables Bayesian parameter inference in gen...
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Newtonbased maximum likelihood estimation in nonlinear state space models
Maximum likelihood (ML) estimation using Newton's method in nonlinear st...
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Marginalizing Gaussian Process Hyperparameters using Sequential Monte Carlo
Gaussian process regression is a popular method for nonparametric proba...
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Identification of jump Markov linear models using particle filters
Jump Markov linear models consists of a finite number of linear state sp...
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Sparse Estimation From Noisy Observations of an Overdetermined Linear System
This note studies a method for the efficient estimation of a finite numb...
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Particle Gibbs with Ancestor Sampling
Particle Markov chain Monte Carlo (PMCMC) is a systematic way of combini...
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Bayesian Inference and Learning in Gaussian Process StateSpace Models with Particle MCMC
Statespace models are successfully used in many areas of science, engin...
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Dynamic DemandCapacity Balancing for Air Traffic Management Using ConstraintBased Local Search: First Results
Using constraintbased local search, we effectively model and efficientl...
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PairWise Cluster Analysis
This paper studies the problem of learning clusters which are consistent...
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Crosslingual Word Segmentation and Morpheme Segmentation as Sequence Labelling
This paper presents our segmentation system developed for the MLP 2017 s...
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Static and Dynamic Feature Selection in Morphosyntactic Analyzers
We study the use of greedy feature selection methods for morphosyntactic...
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Learning Structural Kernels for Natural Language Processing
Structural kernels are a flexible learning paradigm that has been widely...
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Learning nonlinear statespace models using smooth particlefilterbased likelihood approximations
When classical particle filtering algorithms are used for maximum likeli...
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Pricing Derivatives under Multiple Stochastic Factors by Localized Radial Basis Function Methods
We propose two localized Radial Basis Function (RBF) methods, the Radial...
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Faster Concurrent Range Queries with Contention Adapting Search Trees Using Immutable Data
The need for scalable concurrent ordered set data structures with linear...
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CannyFS: Opportunistically Maximizing I/O Throughput Exploiting the Transactional Nature of BatchMode Data Processing
We introduce a user mode file system, CannyFS, that hides latency by ass...
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Onthefly Historical Handwritten Text Annotation
The performance of information retrieval algorithms depends upon the ava...
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Nanosurveyor: a framework for realtime data processing
Scientists are drawn to synchrotrons and accelerator based light sources...
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On the Use of Underspecified DataType Semantics for Type Safety in LowLevel Code
In recent projects on operatingsystem verification, C and C++ data type...
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Monotonicity and robustness in Wiener disorder detection
We study the problem of detecting a drift change of a Brownian motion un...
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Task parallel implementation of a solver for electromagnetic scattering problems
Electromagnetic computations, where the wavelength is small in relation ...
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DuctTeip: An efficient programming model for distributed task based parallel computing
Current highperformance computer systems used for scientific computing ...
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Distributed dynamic load balancing for task parallel programming
In this paper, we derive and investigate approaches to dynamically load ...
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TexT  Text Extractor Tool for Handwritten Document Transcription and Annotation
This paper presents a framework for semiautomatic transcription of larg...
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Device Caching for Network Offloading: Delay Minimization with Presence of User Mobility
A delayoptimal caching problem (DOCP) in deviceto device (D2D) network...
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Improving the particle filter for highdimensional problems using artificial process noise
The particle filter is one of the most successful methods for state infe...
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PDNet: Semantic Segmentation integrated with a PrimalDual Network for Document binarization
Binarization of digital documents is the task of classifying each pixel ...
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Uppsala universitet
Uppsala University is a research university in Uppsala, Sweden, and is the oldest university in Sweden and all of the Nordic countries still in operation, founded in 1477.