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Homology of the family of hyperelliptic curves
Homology of braid groups and Artin groups can be related to the study of spaces of curves. We completely calculate the integral homology of the family of smooth curves of genus $g$ with one boundary component, that are double coverings of the disk ramified over $n = 2g + 1$ points. The main part of such homology is d...
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Simulation of Drop Impact on a Hot Wall using SPH Method with Peng-Robinson Equation of State
This study presents a smoothed particle hydrodynamics (SPH) method with Peng-Robinson equation of state for simulating drop vaporization and drop impact on a hot surface. The conservation equations of momentum and energy and Peng-Robinson equation of state are applied to describe both the liquid and gas phases. The g...
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Generation of attosecond electron beams in relativistic ionization by short laser pulses
Ionization by relativistically intense short laser pulses is studied in the framework of strong-field quantum electrodynamics. Distinctive patterns are found in the energy probability distributions of photoelectrons. Except of the already observed patterns, which were studied in Phys. Rev. A {\bf 94}, 013402 (2016), ...
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Surface defects and elliptic quantum groups
A brane construction of an integrable lattice model is proposed. The model is composed of Belavin's R-matrix, Felder's dynamical R-matrix, the Bazhanov-Sergeev-Derkachov-Spiridonov R-operator and some intertwining operators. This construction implies that a family of surface defects act on supersymmetric indices of f...
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Disentangling and Assessing Uncertainties in Multiperiod Corporate Default Risk Predictions
Measuring the corporate default risk is broadly important in economics and finance. Quantitative methods have been developed to predictively assess future corporate default probabilities. However, as a more difficult yet crucial problem, evaluating the uncertainties associated with the default predictions remains lit...
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The XXL Survey: XVII. X-ray and Sunyaev-Zel'dovich Properties of the Redshift 2.0 Galaxy Cluster XLSSC 122
We present results from a 100 ks XMM-Newton observation of galaxy cluster XLSSC 122, the first massive cluster discovered through its X-ray emission at $z\approx2$. The data provide the first precise constraints on the bulk thermodynamic properties of such a distant cluster, as well as an X-ray spectroscopic confirma...
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A bound for rational Thurston-Bennequin invariants
In this paper, we introduce a rational $\tau$ invariant for rationally null-homologous knots in contact 3-manifolds with nontrivial Ozsváth-Szabó contact invariants. Such an invariant is an upper bound for the sum of rational Thurston-Bennequin invariant and the rational rotation number of the Legendrian representati...
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Generalized Fréchet Bounds for Cell Entries in Multidimensional Contingency Tables
We consider the lattice, $\mathcal{L}$, of all subsets of a multidimensional contingency table and establish the properties of monotonicity and supermodularity for the marginalization function, $n(\cdot)$, on $\mathcal{L}$. We derive from the supermodularity of $n(\cdot)$ some generalized Fréchet inequalities complem...
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Signaling on the Continuous Spectrum of Nonlinear Optical fiber
This paper studies different signaling techniques on the continuous spectrum (CS) of nonlinear optical fiber defined by nonlinear Fourier transform. Three different signaling techniques are proposed and analyzed based on the statistics of the noise added to CS after propagation along the nonlinear optical fiber. The ...
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Symmetry analysis and soliton solution of (2+1)- dimensional Zoomeron equation
Traveling wave solutions of (2 + 1)-dimensional Zoomeron equation(ZE) are developed in terms of exponential functions involving free parameters. It is shown that the novel Lie group of transformations method is a competent and prominent tool in solving nonlinear partial differential equations(PDEs) in mathematical ph...
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Estimation in the convolution structure density model. Part II: adaptation over the scale of anisotropic classes
This paper continues the research started in \cite{LW16}. In the framework of the convolution structure density model on $\bR^d$, we address the problem of adaptive minimax estimation with $\bL_p$--loss over the scale of anisotropic Nikol'skii classes. We fully characterize the behavior of the minimax risk for differ...
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Explaining Recurrent Neural Network Predictions in Sentiment Analysis
Recently, a technique called Layer-wise Relevance Propagation (LRP) was shown to deliver insightful explanations in the form of input space relevances for understanding feed-forward neural network classification decisions. In the present work, we extend the usage of LRP to recurrent neural networks. We propose a spec...
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Generalized Coherence Concurrence and Path distinguishability
We propose a new family of coherence monotones, named the \emph{generalized coherence concurrence} (or coherence $k$-concurrence), which is an analogous concept to the generalized entanglement concurrence. The coherence $k$-concurrence of a state is nonzero if and only if the coherence number (a recently introduced d...
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Passivity Based Whole-body Control for Quadrupedal Locomotion on Challenging Terrain
We present a passivity-based Whole-Body Control approach for quadruped robots that achieves dynamic locomotion while compliantly balancing the robot's trunk. We formulate the motion tracking as a Quadratic Program that takes into account the full robot rigid body dynamics, the actuation limit, the joint limits and th...
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Accelerations for Graph Isomorphism
In this paper, we present two main results. First, by only one conjecture (Conjecture 2.9) for recognizing a vertex symmetric graph, which is the hardest task for our problem, we construct an algorithm for finding an isomorphism between two graphs in polynomial time $ O(n^{3}) $. Second, without that conjecture, we p...
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Multi-Objective Maximization of Monotone Submodular Functions with Cardinality Constraint
We consider the problem of multi-objective maximization of monotone submodular functions subject to cardinality constraint, often formulated as $\max_{|A|=k}\min_{i\in\{1,\dots,m\}}f_i(A)$. While it is widely known that greedy methods work well for a single objective, the problem becomes much harder with multiple obj...
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Cosmology from conservation of global energy
It is argued that many of the problems and ambiguities of standard cosmology derive from a single one: violation of conservation of energy in the standard paradigm. Standard cosmology satisfies conservation of local energy, however disregards the inherent global aspect of energy. We therefore explore conservation of ...
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Electric field modulation of the non-linear areal magnetic anisotropy energy
We study the ferromagnetic layer thickness dependence of the voltage-controlled magnetic anisotropy (VCMA) in gated CoFeB/MgO heterostructures with heavy metal underlayers. When the effective CoFeB thickness is below ~1 nm, the VCMA efficiency of Ta/CoFeB/MgO heterostructures considerably decreases with decreasing Co...
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Gapless surface states originated from accidentally degenerate quadratic band touching in a three-dimensional tetragonal photonic crystal
A tetragonal photonic crystal composed of high-index pillars can exhibit a frequency-isolated accidental degeneracy at a high-symmetry point in the first Brillouin zone. A photonic band gap can be formed there by introducing a geometrical anisotropy in the pillars. In this gap, gapless surface/domain-wall states emer...
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On the impact of pull request decisions on future contributions
The pull-based development process has become prevalent on platforms such as GitHub as a form of distributed software development. Potential contributors can create and submit a set of changes to a software project through pull requests. These changes can be accepted, discussed or rejected by the maintainers of the s...
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The unreasonable effectiveness of the forget gate
Given the success of the gated recurrent unit, a natural question is whether all the gates of the long short-term memory (LSTM) network are necessary. Previous research has shown that the forget gate is one of the most important gates in the LSTM. Here we show that a forget-gate-only version of the LSTM with chrono-i...
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WMRB: Learning to Rank in a Scalable Batch Training Approach
We propose a new learning to rank algorithm, named Weighted Margin-Rank Batch loss (WMRB), to extend the popular Weighted Approximate-Rank Pairwise loss (WARP). WMRB uses a new rank estimator and an efficient batch training algorithm. The approach allows more accurate item rank approximation and explicit utilization ...
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Learning Features from Co-occurrences: A Theoretical Analysis
Representing a word by its co-occurrences with other words in context is an effective way to capture the meaning of the word. However, the theory behind remains a challenge. In this work, taking the example of a word classification task, we give a theoretical analysis of the approaches that represent a word X by a fu...
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Azumaya algebras and canonical components
Let $M$ be a compact 3-manifold and $\Gamma=\pi_1(M)$. The work of Thurston and Culler--Shalen established the $\mathrm{SL}_2(\mathbb{C})$ character variety $X(\Gamma)$ as fundamental tool in the study of the geometry and topology of $M$. This is particularly so in the case when $M$ is the exterior of a hyperbolic kn...
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On the Spectrum of Multi-Frequency Quasiperiodic Schrödinger Operators with Large Coupling
We study multi-frequency quasiperiodic Schrödinger operators on $\mathbb{Z} $. We prove that for a large real analytic potential satisfying certain restrictions the spectrum consists of a single interval. The result is a consequence of a criterion for the spectrum to contain an interval at a given location that we es...
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Model Spaces of Regularity Structures for Space-Fractional SPDEs
We study model spaces, in the sense of Hairer, for stochastic partial differential equations involving the fractional Laplacian. We prove that the fractional Laplacian is a singular kernel suitable to apply the theory of regularity structures. Our main contribution is to study the dependence of the model space for a ...
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Transit Detection of a "Starshade" at the Inner Lagrange Point of an Exoplanet
All water-covered rocky planets in the inner habitable zones of solar-type stars will inevitably experience a catastrophic runaway climate due to increasing stellar luminosity and limits to outgoing infrared radiation from wet greenhouse atmospheres. Reflectors or scatterers placed near Earth's inner Lagrange point (...
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Automatic Error Analysis of Human Motor Performance for Interactive Coaching in Virtual Reality
In the context of fitness coaching or for rehabilitation purposes, the motor actions of a human participant must be observed and analyzed for errors in order to provide effective feedback. This task is normally carried out by human coaches, and it needs to be solved automatically in technical applications that are to...
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A mechanism of synaptic clock underlying subjective time perception
Temporal resolution of visual information processing is thought to be an important factor in predator-prey interactions, shaped in the course of evolution by animals' ecology. Here I show that light can be considered to have a dual role of a source of information, which guides motor actions, and an environmental feed...
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Optimal Packings of Two to Four Equal Circles on Any Flat Torus
We find explicit formulas for the radii and locations of the circles in all the optimally dense packings of two, three or four equal circles on any flat torus, defined to be the quotient of the Euclidean plane by the lattice generated by two independent vectors. We prove the optimality of the arrangements using techn...
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Obfuscation in Bitcoin: Techniques and Politics
In the cryptographic currency Bitcoin, all transactions are recorded in the blockchain - a public, global, and immutable ledger. Because transactions are public, Bitcoin and its users employ obfuscation to maintain a degree of financial privacy. Critically, and in contrast to typical uses of obfuscation, in Bitcoin o...
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Path Planning and Controlled Crash Landing of a Quadcopter in case of a Rotor Failure
This paper presents a framework for controlled emergency landing of a quadcopter, experiencing a rotor failure, away from sensitive areas. A complete mathematical model capturing the dynamics of the system is presented that takes the asymmetrical aerodynamic load on the propellers into account. An equilibrium state o...
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Exact short-time height distribution in 1D KPZ equation with Brownian initial condition
The early time regime of the Kardar-Parisi-Zhang (KPZ) equation in $1+1$ dimension, starting from a Brownian initial condition with a drift $w$, is studied using the exact Fredholm determinant representation. For large drift we recover the exact results for the droplet initial condition, whereas a vanishingly small d...
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The role of cosmology in modern physics
Subject of this article is the relationship between modern cosmology and fundamental physics, in particular general relativity as a theory of gravity on one side, together with its unique application in cosmology, and the formation of structures and their statistics on the other. It summarises arguments for the formu...
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TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals
Temporal Action Proposal (TAP) generation is an important problem, as fast and accurate extraction of semantically important (e.g. human actions) segments from untrimmed videos is an important step for large-scale video analysis. We propose a novel Temporal Unit Regression Network (TURN) model. There are two salient ...
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Efficiently Learning Nonstationary Gaussian Processes for Real World Impact
Most real world phenomena such as sunlight distribution under a forest canopy, minerals concentration, stock valuation, exhibit nonstationary dynamics i.e. phenomenon variation changes depending on the locality. Nonstationary dynamics pose both theoretical and practical challenges to statistical machine learning algo...
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Causal Holography in Application to the Inverse Scattering Problems
For a given smooth compact manifold $M$, we introduce an open class $\mathcal G(M)$ of Riemannian metrics, which we call \emph{metrics of the gradient type}. For such metrics $g$, the geodesic flow $v^g$ on the spherical tangent bundle $SM \to M$ admits a Lyapunov function (so the $v^g$-flow is traversing). It turns ...
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Inferring short-term volatility indicators from Bitcoin blockchain
In this paper, we study the possibility of inferring early warning indicators (EWIs) for periods of extreme bitcoin price volatility using features obtained from Bitcoin daily transaction graphs. We infer the low-dimensional representations of transaction graphs in the time period from 2012 to 2017 using Bitcoin bloc...
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Discrete structure of the brain rhythms
Neuronal activity in the brain generates synchronous oscillations of the Local Field Potential (LFP). The traditional analyses of the LFPs are based on decomposing the signal into simpler components, such as sinusoidal harmonics. However, a common drawback of such methods is that the decomposition primitives are usua...
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A new class of solutions for the multi-component extended Harry Dym equation
We construct a point transformation between two integrable systems, the multi-component Harry Dym equation and the multi-component extended Harry Dym equation, that does not preserve the class of multi-phase solutions. As a consequence we obtain a new type of wave-like solutions, generalising the~multi-phase solution...
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Multivariate Generalized Linear Mixed Models for Joint Estimation of Sporting Outcomes
This paper explores improvements in prediction accuracy and inference capability when allowing for potential correlation in team-level random effects across multiple game-level responses from different assumed distributions. First-order and fully exponential Laplace approximations are used to fit normal-binary and Po...
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Accelerator Codesign as Non-Linear Optimization
We propose an optimization approach for determining both hardware and software parameters for the efficient implementation of a (family of) applications called dense stencil computations on programmable GPGPUs. We first introduce a simple, analytical model for the silicon area usage of accelerator architectures and a...
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Riddim: A Rhythm Analysis and Decomposition Tool Based On Independent Subspace Analysis
The goal of this thesis was to implement a tool that, given a digital audio input, can extract and represent rhythm and musical time. The purpose of the tool is to help develop better models of rhythm for real-time computer based performance and composition. This analysis tool, Riddim, uses Independent Subspace Analy...
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Cholesterol modulates acetylcholine receptor diffusion by tuning confinement sojourns and nanocluster stability
Translational motion of neurotransmitter receptors is key for determining receptor number at the synapse and hence, synaptic efficacy. We combine live-cell STORM superresolution microscopy of nicotinic acetylcholine receptor (nAChR) with single-particle tracking, mean-squared displacement (MSD), turning angle, ergodi...
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Incidence systems on Cartesian powers of algebraic curves
We show that a reduct of the Zariski structure of an algebraic curve which is not locally modular interprets a field, answering a question of Zilber's.
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Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition
Statisticians have made great progress in creating methods that reduce our reliance on parametric assumptions. However this explosion in research has resulted in a breadth of inferential strategies that both create opportunities for more reliable inference as well as complicate the choices that an applied researcher ...
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Certified Computation from Unreliable Datasets
A wide range of learning tasks require human input in labeling massive data. The collected data though are usually low quality and contain inaccuracies and errors. As a result, modern science and business face the problem of learning from unreliable data sets. In this work, we provide a generic approach that is based...
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A sparse grid approach to balance sheet risk measurement
In this work, we present a numerical method based on a sparse grid approximation to compute the loss distribution of the balance sheet of a financial or an insurance company. We first describe, in a stylised way, the assets and liabilities dynamics that are used for the numerical estimation of the balance sheet distr...
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Towards Metamerism via Foveated Style Transfer
The problem of $\textit{visual metamerism}$ is defined as finding a family of perceptually indistinguishable, yet physically different images. In this paper, we propose our NeuroFovea metamer model, a foveated generative model that is based on a mixture of peripheral representations and style transfer forward-pass al...
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Modeling Sheep pox Disease from the 1994-1998 Epidemic in Evros Prefecture, Greece
Sheep pox is a highly transmissible disease which can cause serious loss of livestock and can therefore have major economic impact. We present data from sheep pox epidemics which occurred between 1994 and 1998. The data include weekly records of infected farms as well as a number of covariates. We implement Bayesian ...
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Minimal hard surface-unlink and classical unlink diagrams
We describe a method for generating minimal hard prime surface-link diagrams. We extend the known examples of minimal hard prime classical unknot and unlink diagrams up to three components and generate figures of all minimal hard prime surface-unknot and surface-unlink diagrams with prime base surface components up t...
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Fading of collective attention shapes the evolution of linguistic variants
Language change involves the competition between alternative linguistic forms (1). The spontaneous evolution of these forms typically results in monotonic growths or decays (2, 3) like in winner-take-all attractor behaviors. In the case of the Spanish past subjunctive, the spontaneous evolution of its two competing f...
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Continuous-Time User Modeling in the Presence of Badges: A Probabilistic Approach
User modeling plays an important role in delivering customized web services to the users and improving their engagement. However, most user models in the literature do not explicitly consider the temporal behavior of users. More recently, continuous-time user modeling has gained considerable attention and many user b...
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Testing for observation-dependent regime switching in mixture autoregressive models
Testing for regime switching when the regime switching probabilities are specified either as constants (`mixture models') or are governed by a finite-state Markov chain (`Markov switching models') are long-standing problems that have also attracted recent interest. This paper considers testing for regime switching wh...
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The finiteness dimension of modules and relative Cohen-Macaulayness
Let $R$ be a commutative Noetherian ring, $\mathfrak a$ and $\mathfrak b$ ideals of $R$. In this paper, we study the finiteness dimension $f_{\mathfrak a}(M)$ of $M$ relative to $\mathfrak a$ and the $\mathfrak b$-minimum $\mathfrak a$-adjusted depth $\lambda_{\mathfrak a}^{\mathfrak b}(M)$ of $M$, where the underlyi...
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On Ladder Logic Bombs in Industrial Control Systems
In industrial control systems, devices such as Programmable Logic Controllers (PLCs) are commonly used to directly interact with sensors and actuators, and perform local automatic control. PLCs run software on two different layers: a) firmware (i.e. the OS) and b) control logic (processing sensor readings to determin...
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Stochastic variance reduced multiplicative update for nonnegative matrix factorization
Nonnegative matrix factorization (NMF), a dimensionality reduction and factor analysis method, is a special case in which factor matrices have low-rank nonnegative constraints. Considering the stochastic learning in NMF, we specifically address the multiplicative update (MU) rule, which is the most popular, but which...
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Bi-National Delay Pattern Analysis For Commercial and Passenger Vehicles at Niagara Frontier Border
Border crossing delays between New York State and Southern Ontario cause problems like enormous economic loss and massive environmental pollutions. In this area, there are three border-crossing ports: Peace Bridge (PB), Rainbow Bridge (RB) and Lewiston-Queenston Bridge (LQ) at Niagara Frontier border. The goals of th...
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A Scalable and Adaptive Method for Finding Semantically Equivalent Cue Words of Uncertainty
Scientific knowledge is constantly subject to a variety of changes due to new discoveries, alternative interpretations, and fresh perspectives. Understanding uncertainties associated with various stages of scientific inquiries is an integral part of scientists' domain expertise and it serves as the core of their meta...
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An optimization method to simultaneously estimate electrophysiology and connectivity in a model central pattern generator
Central pattern generators (CPGs) appear to have evolved multiple times throughout the animal kingdom, indicating that their design imparts a significant evolutionary advantage. Insight into how this design is achieved is hindered by the difficulty inherent in examining relationships among electrophysiological proper...
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Overdensities of SMGs around WISE-selected, ultra-luminous, high-redshift AGN
We investigate extremely luminous dusty galaxies in the environments around WISE-selected hot dust obscured galaxies (Hot DOGs) and WISE/radio-selected active galactic nuclei (AGNs) at average redshifts of z = 2.7 and z = 1.7, respectively. Previous observations have detected overdensities of companion submillimetre-...
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Constrained Best Linear Unbiased Estimation
The least squares (LS) estimator and the best linear unbiased estimator (BLUE) are two well-studied approaches for the estimation of a deterministic but unknown parameter vector. In many applications it is known that the parameter vector fulfills some constraints, e.g., linear constraints. For such situations the con...
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Compact Tensor Pooling for Visual Question Answering
Performing high level cognitive tasks requires the integration of feature maps with drastically different structure. In Visual Question Answering (VQA) image descriptors have spatial structures, while lexical inputs inherently follow a temporal sequence. The recently proposed Multimodal Compact Bilinear pooling (MCB)...
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Beam-induced Back-streaming Electron Suppression Analysis for Accelerator Type Neutron Generators
A facility based on a next-generation, high-flux D-D neutron generator has been commissioned and it is now operational at the University of California, Berkeley. The current generator design produces near monoenergetic 2.45 MeV neutrons at outputs of 10^8 n/s. Calculations provided show that future conditioning at hi...
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Vertical stratification of forest canopy for segmentation of under-story trees within small-footprint airborne LiDAR point clouds
Airborne LiDAR point cloud representing a forest contains 3D data, from which vertical stand structure even of understory layers can be derived. This paper presents a tree segmentation approach for multi-story stands that stratifies the point cloud to canopy layers and segments individual tree crowns within each laye...
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Temperature effect observed by the Nagoya muon telescope
The temperature coefficients for all the directions of the Nagoya muon telescope were obtained. The zenith angular dependence of the temperature coefficients was studied.
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Generalizing Hamiltonian Monte Carlo with Neural Networks
We present a general-purpose method to train Markov chain Monte Carlo kernels, parameterized by deep neural networks, that converge and mix quickly to their target distribution. Our method generalizes Hamiltonian Monte Carlo and is trained to maximize expected squared jumped distance, a proxy for mixing speed. We dem...
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Multiplicities of Character Values of Binary Sidel'nikov-Lempel-Cohn-Eastman Sequences
Binary Sidel'nikov-Lempel-Cohn-Eastman sequences (or SLCE sequences) over F 2 have even period and almost perfect autocorrelation. However, the evaluation of the linear complexity of these sequences is really difficult. In this paper, we continue the study of [1]. We first express the multiple roots of character poly...
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Complex and Holographic Embeddings of Knowledge Graphs: A Comparison
Embeddings of knowledge graphs have received significant attention due to their excellent performance for tasks like link prediction and entity resolution. In this short paper, we are providing a comparison of two state-of-the-art knowledge graph embeddings for which their equivalence has recently been established, i...
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Deep Image Prior
Deep convolutional networks have become a popular tool for image generation and restoration. Generally, their excellent performance is imputed to their ability to learn realistic image priors from a large number of example images. In this paper, we show that, on the contrary, the structure of a generator network is s...
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Efficient SMC$^2$ schemes for stochastic kinetic models
Fitting stochastic kinetic models represented by Markov jump processes within the Bayesian paradigm is complicated by the intractability of the observed data likelihood. There has therefore been considerable attention given to the design of pseudo-marginal Markov chain Monte Carlo algorithms for such models. However,...
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Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks, paired training data will not be available. We present an approach for learning to translate an ...
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Consistent structure estimation of exponential-family random graph models with block structure
We consider the challenging problem of statistical inference for exponential-family random graph models based on a single observation of a random graph with complex dependence. To facilitate statistical inference, we consider random graphs with additional structure in the form of block structure. We have shown elsewh...
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Taskonomy: Disentangling Task Transfer Learning
Do visual tasks have a relationship, or are they unrelated? For instance, could having surface normals simplify estimating the depth of an image? Intuition answers these questions positively, implying existence of a structure among visual tasks. Knowing this structure has notable values; it is the concept underlying ...
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The Energy Measure for the Euler and Navier-Stokes Equations
The potential failure of energy equality for a solution $u$ of the Euler or Navier-Stokes equations can be quantified using a so-called `energy measure': the weak-$*$ limit of the measures $|u(t)|^2\,\mbox{d}x$ as $t$ approaches the first possible blowup time. We show that membership of $u$ in certain (weak or strong...
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Inference of Spatio-Temporal Functions over Graphs via Multi-Kernel Kriged Kalman Filtering
Inference of space-time varying signals on graphs emerges naturally in a plethora of network science related applications. A frequently encountered challenge pertains to reconstructing such dynamic processes, given their values over a subset of vertices and time instants. The present paper develops a graph-aware kern...
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Z2-Thurston Norm and Complexity of 3-Manifolds, II
In this sequel to earlier papers by three of the authors, we obtain a new bound on the complexity of a closed 3--manifold, as well as a characterisation of manifolds realising our complexity bounds. As an application, we obtain the first infinite families of minimal triangulations of Seifert fibred spaces modelled on...
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Discriminative k-shot learning using probabilistic models
This paper introduces a probabilistic framework for k-shot image classification. The goal is to generalise from an initial large-scale classification task to a separate task comprising new classes and small numbers of examples. The new approach not only leverages the feature-based representation learned by a neural n...
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Comparative analysis of criteria for filtering time series of word usage frequencies
This paper describes a method of nonlinear wavelet thresholding of time series. The Ramachandran-Ranganathan runs test is used to assess the quality of approximation. To minimize the objective function, it is proposed to use genetic algorithms - one of the stochastic optimization methods. The suggested method is test...
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Extend of the $\mathbb{Z}_2$-spin liquid phase on the Kagomé-lattice
The $\mathbb{Z}_2$ topological phase in the quantum dimer model on the Kagomé-lattice is a candidate for the description of the low-energy physics of the anti-ferromagnetic Heisenberg model on the same lattice. We study the extend of the topological phase by interpolating between the exactly solvable parent Hamiltoni...
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Accelerated Stochastic Quasi-Newton Optimization on Riemann Manifolds
We propose an L-BFGS optimization algorithm on Riemannian manifolds using minibatched stochastic variance reduction techniques for fast convergence with constant step sizes, without resorting to linesearch methods designed to satisfy Wolfe conditions. We provide a new convergence proof for strongly convex functions w...
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Bridging trees for posterior inference on Ancestral Recombination Graphs
We present a new Markov chain Monte Carlo algorithm, implemented in software Arbores, for inferring the history of a sample of DNA sequences. Our principal innovation is a bridging procedure, previously applied only for simple stochastic processes, in which the local computations within a bridge can proceed independe...
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Strong magnetic frustration in Y$_{3}$Cu$_{9}$(OH)$_{19}$Cl$_{8}$: a distorted kagome antiferromagnet
We present the crystal structure and magnetic properties of Y$_{3}$Cu$_{9}$(OH)$_{19}$Cl$_{8}$, a stoichiometric frustrated quantum spin system with slightly distorted kagome layers. Single crystals of Y$_{3}$Cu$_{9}$(OH)$_{19}$Cl$_{8}$ were grown under hydrothermal conditions. The structure was determined from singl...
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The Character Field Theory and Homology of Character Varieties
We construct an extended oriented $(2+\epsilon)$-dimensional topological field theory, the character field theory $X_G$ attached to a affine algebraic group in characteristic zero, which calculates the homology of character varieties of surfaces. It is a model for a dimensional reduction of Kapustin-Witten theory ($N...
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A new generator of chaotic bit sequences with mixed-mode inputs
This paper presents a new generator of chaotic bit sequences with mixed-mode (continuous and discrete) inputs. The generator has an improved level of chaotic properties in comparison with the existing single source (input) digital chaotic bit generators. The 0-1 test is used to show the improved chaotic behavior of o...
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HAWC response to atmospheric electricity activity
The HAWC Gamma Ray observatory consists of 300 water Cherenkov detectors (WCD) instrumented with four photo multipliers tubes (PMT) per WCD. HAWC is located between two of the highest mountains in Mexico. The high altitude (4100 m asl), the relatively short distance to the Gulf of Mexico (~100 km), the large detectin...
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Optical Music Recognition with Convolutional Sequence-to-Sequence Models
Optical Music Recognition (OMR) is an important technology within Music Information Retrieval. Deep learning models show promising results on OMR tasks, but symbol-level annotated data sets of sufficient size to train such models are not available and difficult to develop. We present a deep learning architecture call...
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Fractional Cable Model for Signal Conduction in Spiny Neuronal Dendrites
The cable model is widely used in several fields of science to describe the propagation of signals. A relevant medical and biological example is the anomalous subdiffusion in spiny neuronal dendrites observed in several studies of the last decade. Anomalous subdiffusion can be modelled in several ways introducing som...
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Hedging in fractional Black-Scholes model with transaction costs
We consider conditional-mean hedging in a fractional Black-Scholes pricing model in the presence of proportional transaction costs. We develop an explicit formula for the conditional-mean hedging portfolio in terms of the recently discovered explicit conditional law of the fractional Brownian motion.
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Finite flat spaces
We say that a finite metric space $X$ can be embedded almost isometrically into a class of metric spaces $C$, if for every $\epsilon > 0$ there exists an embedding of $X$ into one of the elements of $C$ with the bi-Lipschitz distortion less then $1 + \epsilon$. We show that almost isometric embeddability conditions a...
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On The Equivalence of Projections In Relative $α$-Entropy and Rényi Divergence
The aim of this work is to establish that two recently published projection theorems, one dealing with a parametric generalization of relative entropy and another dealing with Rényi divergence, are equivalent under a correspondence on the space of probability measures. Further, we demonstrate that the associated "Pyt...
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Comparing high dimensional partitions, with the Coclustering Adjusted Rand Index
The popular Adjusted Rand Index (ARI) is extended to the task of simultaneous clustering of the rows and columns of a given matrix. This new index called Coclustering Adjusted Rand Index (CARI) remains convenient and competitive facing other indices. Indeed, partitions with high number of clusters can be considered a...
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Dependence between Path-length and Size in Random Digital Trees
We study the size and the external path length of random tries and show that they are asymptotically independent in the asymmetric case but strongly dependent with small periodic fluctuations in the symmetric case. Such an unexpected behavior is in sharp contrast to the previously known results on random tries that t...
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Analysing Shortcomings of Statistical Parametric Speech Synthesis
Output from statistical parametric speech synthesis (SPSS) remains noticeably worse than natural speech recordings in terms of quality, naturalness, speaker similarity, and intelligibility in noise. There are many hypotheses regarding the origins of these shortcomings, but these hypotheses are often kept vague and pr...
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On Meshfree GFDM Solvers for the Incompressible Navier-Stokes Equations
Meshfree solution schemes for the incompressible Navier--Stokes equations are usually based on algorithms commonly used in finite volume methods, such as projection methods, SIMPLE and PISO algorithms. However, drawbacks of these algorithms that are specific to meshfree methods have often been overlooked. In this pap...
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Using a new parsimonious AHP methodology combined with the Choquet integral: An application for evaluating social housing initiatives
We propose a development of the Analytic Hierarchy Process (AHP) permitting to use the methodology also in cases of decision problems with a very large number of alternatives evaluated with respect to several criteria. While the application of the original AHP method involves many pairwise comparisons between alterna...
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Importance Sketching of Influence Dynamics in Billion-scale Networks
The blooming availability of traces for social, biological, and communication networks opens up unprecedented opportunities in analyzing diffusion processes in networks. However, the sheer sizes of the nowadays networks raise serious challenges in computational efficiency and scalability. In this paper, we propose a ...
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Motivations, Classification and Model Trial of Conversational Agents for Insurance Companies
Advances in artificial intelligence have renewed interest in conversational agents. So-called chatbots have reached maturity for industrial applications. German insurance companies are interested in improving their customer service and digitizing their business processes. In this work we investigate the potential use...
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Dark Matter and Neutrinos
The Keplerian distribution of velocities is not observed in the rotation of large scale structures, such as found in the rotation of spiral galaxies. The deviation from Keplerian distribution provides compelling evidence of the presence of non-luminous matter i.e. called dark matter. There are several astrophysical m...
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Variational Bi-LSTMs
Recurrent neural networks like long short-term memory (LSTM) are important architectures for sequential prediction tasks. LSTMs (and RNNs in general) model sequences along the forward time direction. Bidirectional LSTMs (Bi-LSTMs) on the other hand model sequences along both forward and backward directions and are ge...
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