Modeling Smooth Backgrounds and Generic Localized Signals with Gaussian ProcessesWe describe a procedure for constructing a model of a smooth data spectrum using Gaussian processes rather than the historical parametric description. This approach considers a fuller space of…Meghan Frate, Kyle Cranmer, Saarik Kalia et al.·Sep 17, 2017SaveLearn
Modeling correlated bursts by the bursty-get-burstier mechanismTemporal correlations of time series or event sequences in natural and social phenomena have been characterized by power-law decaying autocorrelation functions with decaying exponent γ. Such…Hang-Hyun Jo·Sep 15, 2017SaveLearn
AMORPH: A statistical program for characterizing amorphous materials by X-ray diffractionAMORPH utilizes a new Bayesian statistical approach to interpreting X-ray diffraction results of samples with both crystalline and amorphous components. AMORPH fits X-ray diffraction patterns with a…Michael C. Rowe, Brendon J. Brewer·Sep 13, 2017SaveLearn
Statistical Physics and Representations in Real and Artificial Neural NetworksThis document presents the material of two lectures on statistical physics and neural representations, delivered by one of us (R.M.) at the Fundamental Problems in Statistical Physics XIV summer…Simona Cocco, Rémi Monasson, Lorenzo Posani et al.·Sep 7, 2017SaveLearn
Impact of non-stationarity on hybrid ensemble filters: A study with a doubly stochastic advection-diffusion-decay modelEffects of non-stationarity on the performance of hybrid ensemble filters are studied (by hybrid filters we mean those which blend ensemble covariances with some other regularizing covariances). To…Michael Tsyrulnikov, Alexander Rakitko·Aug 29, 2017SaveLearn
Backward Simulation of Stochastic Process using a Time Reverse Monte Carlo methodThe "backward simulation" of a stochastic process is defined as the stochastic dynamics that trace a time-reversed path from the target region to the initial configuration. If the probabilities…Shinichi Takayanagi, Yukito Iba·Aug 27, 2017SaveLearn
The evaluation of the systematic uncertainties for the finite MC samples in the presence of negative weightsThe analysis of results from HEP experiments often involves the estimates of the composition of the binned data samples, based on Monte Carlo simulations of various sources. Due to a finite statistic…Petr Mandrik·Aug 25, 2017SaveLearn
A Conditional Model of Wind Power Forecast Errors and Its Application in Scenario GenerationIn power system operation, characterizing the stochastic nature of wind power is an important albeit challenging issue. It is well known that distributions of wind power forecast errors often exhibit…Zhiwen Wang, Chen Shen, Feng Liu·Aug 22, 2017SaveLearn
An Emergent Space for Distributed Data with Hidden Internal Order through Manifold LearningManifold-learning techniques are routinely used in mining complex spatiotemporal data to extract useful, parsimonious data representations/parametrizations; these are, in turn, useful in nonlinear…Felix P. Kemeth, Sindre W. Haugland, Felix Dietrich et al.·Aug 17, 2017SaveLearn
Long-range fluctuations and multifractality in connectivity density time series of a wind speed monitoring networkThis paper studies the daily connectivity time series of a wind speed-monitoring network using multifractal detrended fluctuation analysis. It investigates the long-range fluctuation and…Mohamed Laib, Luciano Telesca, Mikhail Kanevski·Aug 14, 2017SaveLearn
Quantifying multivariate redundancy with maximum entropy decompositions of mutual informationWilliams and Beer (2010) proposed a nonnegative mutual information decomposition, based on the construction of redundancy lattices, which allows separating the information that a set of variables…Daniel Chicharro·Aug 13, 2017SaveLearn
Some comments on computational mechanics, complexity measures, and all thatWe comment on some conceptual and and technical problems related to computational mechanics, point out some errors in several papers, and straighten out some wrong priority claims. We present…Peter Grassberger·Aug 10, 2017SaveLearn
Structural Damage Identification Using Piezoelectric Impedance Measurement with Sparse Inverse AnalysisThe impedance/admittance measurements of a piezoelectric transducer bonded to or embedded in a host structure can be used as damage indicator. When a credible model of the healthy structure, such as…Pei Cao, Qi Shuai, Jiong Tang·Aug 9, 2017SaveLearn
Reliable uncertainties in indirect measurementsIn this article we present very intuitive, easy to follow, yet mathematically rigorous, approach to the so called data fitting process. Rather than minimizing the distance between measured and…Marek W. Gutowski·Aug 4, 2017SaveLearn
A Deep Convolutional Neural Network to Analyze Position Averaged Convergent Beam Electron Diffraction PatternsWe establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk…Weizong Xu, James M. LeBeau·Aug 3, 2017SaveLearn
Practical StatisticsAccelerators and detectors are expensive, both in terms of money and human effort. It is thus important to invest effort in performing a good statistical analysis of the data, in order to extract the…L. Lyons·Aug 3, 2017SaveLearn
Latent common manifold learning with alternating diffusion: analysis and applicationsThe analysis of data sets arising from multiple sensors has drawn significant research attention over the years. Traditional methods, including kernel-based methods, are typically incapable of…Ronen Talmon, Hau-tieng Wu·Aug 3, 2017SaveLearn
Bayesian Block Histogramming for High Energy PhysicsThe Bayesian Block algorithm, originally developed for applications in astronomy, can be used to improve the binning of histograms in high energy physics. The visual improvement can be dramatic, as…Brian Pollack, Saptaparna Bhattacharya, Michael Schmitt·Aug 2, 2017SaveLearn
Improved Pseudolikelihood Regularization and Decimation methods on Non-linearly Interacting Systems with Continuous VariablesWe propose and test improvements to state-of-the-art techniques of Bayeasian statistical inference based on pseudolikelihood maximization with 1 regularization and with decimation. In…Alessia Marruzzo, Payal Tyagi, Fabrizio Antenucci et al.·Aug 2, 2017SaveLearn
Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet ComputationsThe development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with…Xun Huan, Cosmin Safta, Khachik Sargsyan et al.·Jul 29, 2017SaveLearn
Laser beam imaging from the speckle pattern of the off-axis scattered intensityWe study the inverse problem of localization (imaging) of a laser beam from measurements of the intensity of light scattered off-axis by a Poisson cloud of small particles. Starting from the wave…Liliana Borcea, Josselin Garnier·Jul 19, 2017SaveLearn
Transition to Reconstructibility in Weakly Coupled NetworksAcross scientific disciplines, thresholded pairwise measures of statistical dependence between time series are taken as proxies for the interactions between the dynamical units of a network. Yet such…Benedict J. Lünsmann, Christoph Kirst, Marc Timme·Jul 10, 2017SaveLearn
Complexity of eye fixation duration time series in reading of Persian texts: A multifractal detrended fluctuation analysisThere is growing evidence that cognitive processes may have fractal structures as a signature of complexity. It is an an ongoing topic of research to study the class of complexity and how it may…Mohammad Sharifi, Hamed Farahani, Farhad Shahbazi et al.·Jul 10, 2017SaveLearn
Uncertainty and auto-correlation in MeasurementAlthough a system is described by a well-known set of equations leading to a deterministic behavior, in the real world the value of a measurand obtained by an experiment will mostly scatter.…Markus Schiebl·Jul 7, 2017SaveLearn
Non-Poisson Renewal Events and MemoryWe study two different forms of fluctuation-dissipation processes generating anomalous relaxations to equilibrium of an initial out of equilibrium condition, the former being based on a stationary…Rohisha Tuladhar, Mauro Bologna, Paolo Grigolini·Jul 6, 2017SaveLearn