November 2020 arXiv papers — page 34

Zuzana Došlá, Mauro Marini, Serena Matucci

A boundary value problem associated to the difference equation with advanced argument \begin{equation} \label{*}\Delta\bigl (a_{n}\Phi(\Delta x_{n})\bigr)+b_{n}\Phi(x_{n+p} )=0,\ \ n\geq1 \tag{$*$} \end{equation} is presented, where $\Phi(u)=|u|^{\alpha}$sgn $u,$ $\alpha>0,p$ is a positive integer and the sequences $a,b,$ are positive. We deal with a particu

Zitong Yu, Xiaobai Li, Jingang Shi, Zhaoqiang Xia

Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from the presentation attacks (PAs). As more and more realistic PAs with novel types spring up, it is necessary to develop robust algorithms for detecting unknown attacks even in unseen scenarios. However, deep models supervised by traditional binary loss (e.g., `0' for bonafide

Mikhail Anikushin

We obtain a version of the Frequency Theorem (a theorem on solvability of certain operator inequalities), which allows to construct quadratic Lyapunov functionals for semilinear parabolic equations. We show that the well-known Spectral Gap Condition, which was used in the theory of inertial manifolds by C. Foias, R. Temam and G. R. Sell, is a particular case

Jens O. Andersen, Magdalena Eriksson, Anders Tranberg

Inflation is often described through the dynamics of a scalar field, slow-rolling in a suitable potential. Ultimately, this inflaton must be identified as the expectation value of a quantum field, evolving in a quantum effective potential. The shape of this potential is determined by the underlying tree-level potential, dressed by quantum corrections from th

Yoshikazu Giga, Zhongyang Gu

We introduce various spaces of vector fields of bounded mean oscillation ($BMO$) defined in a domain so that normal trace on the boundary is bounded when its divergence is well controlled. The behavior of "normal" component and "tangential" component may be different for our $BMO$ vector fields. As a result zero extension of the normal component stays in $BM

Hanaa Alshareef, Sandro Stucki, Gerardo Schneider

Recent regulations, such as the European General Data Protection Regulation (GDPR), put stringent constraints on the handling of personal data. Privacy, like security, is a non-functional property, yet most software design tools are focused on functional aspects, using for instance Data Flow Diagrams (DFDs). In previous work, a conceptual model was introduce

Boris Mityagin, Petr Siegl, Joe Viola

We study the semigroup generated by the hypoelliptic Laplacian on the circle and the maximal bounded holomorphic extension of this semigroup. Using an orthogonal decomposition into harmonic oscillators with complex shifts, we describe the domain of this extension and we show that boundedness in a half-plane corresponds to absolute convergence of the expansio

Ivan Skorokhodov, Savva Ignatyev, Mohamed Elhoseiny

In most existing learning systems, images are typically viewed as 2D pixel arrays. However, in another paradigm gaining popularity, a 2D image is represented as an implicit neural representation (INR) - an MLP that predicts an RGB pixel value given its (x,y) coordinate. In this paper, we propose two novel architectural techniques for building INR-based image

Thomas Verelst, Tinne Tuytelaars

SegBlocks reduces the computational cost of existing neural networks, by dynamically adjusting the processing resolution of image regions based on their complexity. Our method splits an image into blocks and downsamples blocks of low complexity, reducing the number of operations and memory consumption. A lightweight policy network, selecting the complex regi

Haoxi Ran, Guangfu Wang, Li Lu

Human imitation has become topical recently, driven by GAN's ability to disentangle human pose and body content. However, the latest methods hardly focus on 3D information, and to avoid self-occlusion, a massive amount of input images are needed. In this paper, we propose RIN, a novel volume-based framework for reconstructing a textured 3D model from a singl

J. Falcon-Barroso, M. Martig

We introduce BAYES-LOSVD, a novel implementation of the non-parametric extraction of line-of-sight velocity distributions (LOSVDs) in galaxies. We employ bayesian inference to obtain robust LOSVDs and associated uncertainties. Our method relies on principal component analysis to reduce the dimensionality of the base of templates required for the extraction a

Junzhe Zhu, Raymond Yeh, Mark Hasegawa-Johnson

We propose an end-to-end trainable approach to single-channel speech separation with unknown number of speakers. Our approach extends the MulCat source separation backbone with additional output heads: a count-head to infer the number of speakers, and decoder-heads for reconstructing the original signals. Beyond the model, we also propose a metric on how to

Beatriz Seoane, Alessandra Carbone

The idea that structural disorder might be a novel mechanism of protein interaction is widespread in the Literature, although the number of statistically significant structural studies supporting this is surprisingly low. At variance with previous works, our conclusions rely exclusively on a large-scale analysis of all the 134337 X-ray crystallographic struc

Jean Renault

Given a locally compact group bundle, we show that the system of the Plancherel weights of their C*-algebras is lower semi-continuous. As a corollary, we obtain that the dual Haar sytem of a continuous Haar system of a locally compact abelian group bundle is also continuous.

Vladimir Yussupov, Ghareeb Falazi, Uwe Breitenbücher, Frank Leymann

Although historically the term serverless was also used in the context of peer-to-peer systems, it is more frequently associated with the architectural style for developing cloud-native applications. From the developer's perspective, serverless architectures allow reducing management efforts since applications are composed using provider-managed components,

M. S. J Barson, L. M. Oberg, L. P. McGuinness, A. Denisenko

The ability to perform nanoscale electric field imaging of elementary charges at ambient temperatures will have diverse interdisciplinary applications. While the nitrogen-vacancy (NV) center in diamond is capable of high-sensitivity electrometry, demonstrations have so far been limited to macroscopic field features or detection of single charges internal to

Abhishek Aggarwal, Vinayak, Saientan Bag, Chiranjib Bhattacharyya

Double-stranded DNA (dsDNA) has been established as an efficient medium for charge migration, bringing it to the forefront of the field of molecular electronics as well as biological research. The charge migration rate is controlled by the electronic couplings between the two nucleobases of DNA/RNA. These electronic couplings strongly depend on the intermole

Piyush Mani Tripathi, Saptarshi Basu

The current resurgence in the phase diagram study beyond the critical point has questioned the conventional belief of supercritical fluid as a single phase with varying properties. On the same line, a novel two-phase approach has been proposed to study the supercritical flow with heat transfer deterioration (HTD) phenomena. The Volume of Fluid (VOF) multipha

Hélène Seiler, Marcin Krynski, Daniela Zahn, Sebastian Hammer

Singlet exciton fission (SEF) is a key process in the development of efficient opto-electronic devices. An aspect that is rarely probed directly, and yet has a tremendous impact on SEF properties, is the nuclear structure and dynamics involved in this process. Here we directly observe the nuclear dynamics accompanying the SEF process in single crystal pentac

Mark A. George, Noboru Takamure, David R. McKenzie

A theoretical and experimental analysis is carried out of radiative heat transfer in the coaxial geometry of evacuated tube solar collectors. The gray body approximation implicit in the use of an effective emissivity does not strictly apply to evacuated tube solar collectors due to selective absorber coating and partially transmitting outer glass in the ther

Jussi Rossi, Juho Uotila, Sucheta Sharma, Toni Laurila

We present an experimental comparison of photoacoustic responsivities of common highly absorbing carbon-based materials. The comparison was carried out with parameters relevant for photoacoustic power detectors and Fourier-transform infrared (FTIR) spectroscopy: we covered a broad wavelength range from the visible red to far infrared (633 nm to 25 um) and th

Maximilian Spliethöver, Henning Wachsmuth

Social bias in language - towards genders, ethnicities, ages, and other social groups - poses a problem with ethical impact for many NLP applications. Recent research has shown that machine learning models trained on respective data may not only adopt, but even amplify the bias. So far, however, little attention has been paid to bias in computational argumen

Herbert Jaeger

The acceleration race of digital computing technologies seems to be steering toward impasses -- technological, economical and environmental -- a condition that has spurred research efforts in alternative, "neuromorphic" (brain-like) computing technologies. Furthermore, since decades the idea of exploiting nonlinear physical phenomena "directly" for non-digit

Shashi Kant Gupta

The backpropagation algorithm is often debated for its biological plausibility. However, various learning methods for neural architecture have been proposed in search of more biologically plausible learning. Most of them have tried to solve the "weight transport problem" and try to propagate errors backward in the architecture via some alternative methods. I

Dmitry Churikov, Ilia Ponomarenko

A permutation group $G\le\operatorname{Sym}(\Omega)$ is said to be $2$-closed if no group $H$ such that $G<H\le\operatorname{Sym}(\Omega)$ has the same orbits on $\Omega\times\Omega$ as $G$. A simple and efficient inductive criterion for the $2$-closedness is established for abelian permutation groups with cyclic transitive constituents.

Cheng Wang, Carolin Lawrence, Mathias Niepert

Uncertainty quantification is crucial for building reliable and trustable machine learning systems. We propose to estimate uncertainty in recurrent neural networks (RNNs) via stochastic discrete state transitions over recurrent timesteps. The uncertainty of the model can be quantified by running a prediction several times, each time sampling from the recurre

Ehud Hrushovski

We work in a first-order setting where structures are spread out over a metric space, with quantification allowed only over bounded subsets. Assuming a doubling property for the metric space, we define a canonical {\em core} $\mathcal{J}$ associated to such a theory, a locally compact structure that embeds into the type space over any model. The automorphism

Nurperi Yavuz, Mustafa Mert Bayer, Hüseyin Ozan Cirkinoğlu, Ali Serpengüzel

An all-diamond photonic circuit was implemented by integrating a diamond microsphere with a femtosecond-laser-written bulk diamond waveguide. The near surface waveguide was fabricated by exploiting the Type II fabrication method to achieve stress-induced waveguiding. Transverse electrically and transverse magnetically polarized light from a tunable laser ope

Pierpaolo Vivo

We critically discuss the problem of finding the $\lambda$-index $\mathcal{N}(\lambda)\in [0,1,\ldots,N]$ of a real symmetric matrix $\mathbf{M}$, defined as the number of eigenvalues smaller than $\lambda$, using the entries of $\mathbf{M}$ as only input. We show that a widely used formula $$ \mathcal{N}(\lambda)=\lim_{\epsilon\to 0^+}\frac{1}{2\pi \mathrm{

Konstantinos Orfanakis, Sai Kiran Rajendran, Hamid Ohadi, Sylwia Zielińska-Raczyńska

The quantum confinement of Rydberg excitons is an important step towards exploiting their large nonlinearities for quantum applications. We observe Rydberg excitons in natural nanoparticles of Cu$_2$O. We resolve up to the principal quantum number $n=12$ in a bulk Cu$_2$O crystal and up to $n=6$ in nanoparticles extracted from the same crystal. The exciton t

Ibrahim Akal, Yuya Kusuki, Noburo Shiba, Tadashi Takayanagi

We calculate the time evolution of entanglement entropy in two dimensional conformal field theory with a moving mirror. For a setup modeling Hawking radiation, we obtain a linear growth of entanglement entropy and show that this can be interpreted as the production of entangled pairs. For a setup, which mimics black hole formation and evaporation, we find th

Racha Friji, Hassen Drira, Faten Chaieb, Sebastian Kurtek

Deep Learning architectures, albeit successful in most computer vision tasks, were designed for data with an underlying Euclidean structure, which is not usually fulfilled since pre-processed data may lie on a non-linear space. In this paper, we propose a geometry aware deep learning approach for skeleton-based action recognition. Skeleton sequences are firs

Christian Steinert

We prove that for every complex classical group $G$ the string polytope associated to a special reduced decomposition and any dominant integral weight $\lambda$ will be a lattice polytope if and only if the highest weight representation of the Lie algebra of $G$ with highest weight $\lambda$ integrates to a representation of $G$ itself. This affirms an earli

SJ Spencer, Alexander Seaton, Tom Goffrey, Tony Arber

In the shock-ignition inertial confinement fusion scheme, high-intensity lasers propagate through an inhomogeneous coronal plasma, driving a shock designed to cause fuel ignition. During the high-intensity ignitor laser pulse, SRS backscatter in the long scale-length coronal plasma is likely to be in the kinetic regime. In this work, we use one-dimensional p

Yang You, Zelin Ye, Yujing Lou, Chengkun Li

3D object detection has attracted much attention thanks to the advances in sensors and deep learning methods for point clouds. Current state-of-the-art methods like VoteNet regress direct offset towards object centers and box orientations with an additional Multi-Layer-Perceptron network. Both their offset and orientation predictions are not accurate due to

Gilles Dolfo, Jacques Vigué, Daniel Lhuillier

In this note, we present Stokes' calculation of the force exerted by the fluid on an oscillating cylinder. While the calculation of the similar problem in the case of the sphere is treated in several textbooks, the case of the cylinder is absent from these textbooks. Because modified Bessel functions were not defined in 1851 when Stokes made this calculation

Rajiv V. Gavai

Extending the successes of lattice quantum chromodynamics(QCD) at zero as well as nonzero temperatures to nonzero density is extremely desirable in view of the quest for the QCD phase diagram both theoretically and experimentally. It turns out though to give rise to some conundrums whose resolution may assist progress in this exciting but difficult area, and

N Bridonneau, M Zhao, N Battaglini, G Mattana

We studied the dependence of solid deposit shape obtained by free drying of sessile drops on the particles concentration and Derjaguin-Landau-Verwey-Overbeek (DLVO) particle/substrate interaction. In contrast to previous contributions using pH as a control parameter of interactions, we investigated an unprecedentedly wide range of concentrations and particle

Dmitry Ioffe, Sébastien Ott, Senya Shlosman, Yvan Velenik

In this paper we develop a detailed analysis of critical prewetting in the context of the two-dimensional Ising model. Namely, we consider a two-dimensional nearest-neighbor Ising model in a $2N\times N$ rectangular box with a boundary condition inducing the coexistence of the $+$ phase in the bulk and a layer of $-$ phase along the bottom wall. The presence

Christophe Besse, Grégory Faye

We propose a new model that describes the dynamics of epidemic spreading on connected graphs. Our model consists in a PDE-ODE system where at each vertex of the graph we have a standard SIR model and connexions between vertices are given by heat equations on the edges supplemented with Robin like boundary conditions at the vertices modeling exchanges between

Silas C. Lobo, Stefan Neumeier, Evelio M. G. Fernandez, Christian Facchi

Vehicular Ad Hoc Networks (VANETs) are expected to be the next big step towards safer road transport, supporting applications to exchange information between vehicles. To develop novel applications for this area a high number of tests, considering all traffic situations, are demanded. However, it is unfeasible to reproduce these tests in real life, by the fa

Chiara Amorino

We study the problem of the non-parametric estimation for the density of the stationary distribution of the multivariate stochastic differential equation with jumps (Xt) , when the dimension d is bigger than 3. From the continuous observation of the sampling path on [0, T ] we show that, under anisotropic Holder smoothness constraints, kernel based estimator

Kwang Sik Jeong, Chan Beom Park

Mirage mediation realized in the Kachru-Kallosh-Linde-Trivedi (KKLT) flux compactification can naturally suppress the up-type Higgs soft mass at low energy scales. As a result, compared to the conventional scenarios, the degree of electroweak fine-tuning can be reduced further up to by a loop factor if the Higgsinos are much lighter than the heavy Higgs doub

Fatimata Sy, Pantxo Diribarne, Bernard Rousset, Mathieu Gibert

In this paper we present a novel hydrodynamic experiment using liquid $^4$He. The flow is forced inertially by a canonical oscillating grid using either its normal (He~I) or superfluid (He~II) phase, generating a statistically stationary turbulence. We characterise the turbulent properties of the flow using 2D Lagrangian Particle tracking on hollow glass mic

Daisuke Nishiyama, Mario Ynocente Castro, Shirou Maruyama, Shinya Shiroshita

Automated Vehicles require exhaustive testing in simulation to detect as many safety-critical failures as possible before deployment on public roads. In this work, we focus on the core decision-making component of autonomous robots: their planning algorithm. We introduce a planner testing framework that leverages recent progress in simulating behaviorally di

Shijie Dong, Zoe Wyatt

From the work on the weak-null condition by Lindblad and Rodnianski, it is well-known that `bad' quadratic sourcing terms are allowed to appear in coupled semilinear wave equations in three spatial dimensions, provided that such terms appear as sources for `good' variables and that the good variables feed back into the system via `good' sourcing terms. Motiv

Drazen Adamovic, Berislav Jandric, Gordan Radobolja

We study the representation theory of the N=1 super Heisenberg-Virasoro vertex algebra at level zero, which extends the previous work on the Heisenberg-Virasoro vertex algebra arXiv:math/0201314, arXiv:1405.1707 and arXiv:1703.00531 to the super case. We calculated all characters of irreducible highest weight representations by investigating certain Fock spa

Xiaobin Sun, Huilian Xia, Yingchao Xie, Xingcheng Zhou

In this paper, the strong averaging principle is researched for a class of H\"{o}lder continuous drift slow-fast SPDEs with $\alpha$-stable process by the Zvonkin's transformation and the classical Khasminkii's time discretization method. As applications, an example is also provided to explain our result.

Shuai-Feng Guo, Feng Chen, Qi Liu, Ming Xue

An energy gap develops near quantum critical point of quantum phase transition in a finite many-body (MB) system, facilitating the ground state transformation by adiabatic parameter change. In real application scenarios, however, the efficacy for such a protocol is compromised by the need to balance finite system life time with adiabaticity, as exemplified i

O. Castelnau, K. Derrien, S Ritterbex, P. Carrez

The viscoplastic behavior of polycrystalline Mg$_2$SiO$_4$ wadsleyite aggregates, a major high pressure phase of the mantle transition zone of the Earth (depth range: 410 -- 520 km), is obtained by properly bridging several scale transition models. At the very fine nanometric scale corresponding to the disloca-tion core structure, the behavior of thermally a

Daniel Barath, Dmytro Mishkin, Ivan Eichhardt, Ilia Shipachev

We propose ways to speed up the initial pose-graph generation for global Structure-from-Motion algorithms. To avoid forming tentative point correspondences by FLANN and geometric verification by RANSAC, which are the most time-consuming steps of the pose-graph creation, we propose two new methods - built on the fact that image pairs usually are matched conse

Mingrui Liu, Wei Zhang, Francesco Orabona, Tianbao Yang

Adam is a widely used stochastic optimization method for deep learning applications. While practitioners prefer Adam because it requires less parameter tuning, its use is problematic from a theoretical point of view since it may not converge. Variants of Adam have been proposed with provable convergence guarantee, but they tend not be competitive with Adam o

Katerina Zmolikova, Marc Delcroix, Lukáš Burget, Tomohiro Nakatani

In this paper, we propose a method combining variational autoencoder model of speech with a spatial clustering approach for multi-channel speech separation. The advantage of integrating spatial clustering with a spectral model was shown in several works. As the spectral model, previous works used either factorial generative models of the mixed speech or disc

Xiang Yu, Fuping Chu, Junqi Wu, Bo Huang

The recommendation system is an important commercial application of machine learning, where billions of feed views in the information flow every day. In reality, the interaction between user and item usually makes user's interest changing over time, thus many companies (e.g. ByteDance, Baidu, Alibaba, and Weibo) employ online learning as an effective way to

Claudio Mele, Alessandro Oliaro

In this paper we study regularity of partial differential equations with polynomial coefficients in non isotropic Beurling spaces of ultradifferentiable functions of global type. We study the action of transformations of Gabor and Wigner type in such spaces and we prove that a suitable representation of Wigner type allows to prove regularity for classes of o

Hao Xu, Dongxiao Zhang, Nanzhe Wang

Data-driven discovery of partial differential equations (PDEs) has attracted increasing attention in recent years. Although significant progress has been made, certain unresolved issues remain. For example, for PDEs with high-order derivatives, the performance of existing methods is unsatisfactory, especially when the data are sparse and noisy. It is also di

Gareth Boxall, Taboka Chalebgwa, Gareth Jones

Suppose that $\Omega$ is a lattice in the complex plane and let $\sigma$ be the corresponding Weierstrass $\sigma$-function. Assume that the point $\tau$ associated to $\Omega$ in the standard fundamental domain has imaginary part at most 1.9. Assuming that $\Omega$ has algebraic invariants $g_2,g_3$ we show that a bound of the form $c d^m (\log H)^n$ holds

Ádám Bácsi, Balázs Dóra

We investigate a quantum quench from a critical to an exceptional point. The initial state, prepared in the ground state of a critical hermitian system, is time evolved with a non-hermitian SSH model, tuned to its exceptional point. The single particle density matrix exhibits supersonic modes and multiple light cones, characteristic to non-hermitian time evo

Matthew R. Moore, Dominic Vella, James M. Oliver

We study the initial evolution of the coffee ring that is formed by the evaporation of a thin, axisymmetric, surface tension-dominated droplet containing a dilute solute. When the solutal P\'{e}clet number is large, we show that diffusion close to the droplet contact line controls the coffee-ring structure in the initial stages of evaporation. We perform a s

Christoph Fischbacher, Oluwadara Ogunkoya

We consider the Heisenberg XXZ spin-$J$ chain ($J\in\mathbb{N}/2$) with anisotropy parameter $\Delta$. Assuming that $\Delta>2J$, and introducing threshold energies $E_{K}:=K\left(1-\frac{2J}{\Delta}\right)$, we show that the bipartite entanglement entropy (EE) of states belonging to any spectral subspace with energy less than $E_{K+1}$ satisfy a logarithmic

Alexis Poulhes, Paul Mirial

In leisure spaces, particularly theme parks and museums, researchers and managers have long been using simulation tools to tackle the big issue associated with attractiveness, flow management. In this research, we present the management and planning perspective of a multi-agent simulation tool which models the behavior of skiers in a ski-area. This is the fi

Hiroshi Kunitomo

We show that the tree-level S-matrices of the superstring field theories based on the homotopy-algebra structure agree with those obtained in the first-quantized formulation. The proof is given in detail for the heterotic string field theory. The extensions to the type II and open superstring field theories are straightforward.

Yang You, Wenhai Liu, Yanjie Ze, Yong-Lu Li

Keypoint detection is an essential component for the object registration and alignment. In this work, we reckon keypoint detection as information compression, and force the model to distill out irrelevant points of an object. Based on this, we propose UKPGAN, a general self-supervised 3D keypoint detector where keypoints are detected so that they could recon

Hongkang Shi, Yuqiong Cheng, Zheng Yang, Yuntian Chen

Optical isolation enables nonreciprocal manipulations of light with broad applications in optical communications. Optical isolation by rotating structures has drawn considerable attention due to its magnetic-free nature and unprecedented performance. Conventional rotation-based optical isolation relies on the use of bulky cavities hindering applications in s

Daniel Beßler, Robert Porzel, Mihai Pomarlan, Abhijit Vyas

In this paper, we present foundations of the Socio-physical Model of Activities (SOMA). SOMA represents both the physical as well as the social context of everyday activities. Such tasks seem to be trivial for humans, however, they pose severe problems for artificial agents. For starters, a natural language command requesting something will leave many pieces

Yuta Sekino, Yusuke Nishida

We investigate local quantum field theories for one-dimensional (1D) Bose and Fermi gases with contact interactions, which are closely connected with each other by Girardeau's Bose-Fermi mapping. While the Lagrangian for bosons includes only a two-body interaction, a marginally relevant three-body interaction term is found to be necessary for fermions. Becau

Manish Agrawal, Abhilash Nandy

Music genre classification is one of the trending topics in regards to the current Music Information Retrieval (MIR) Research. Since, the dependency of genre is not only limited to the audio profile, we also make use of textual content provided as lyrics of the corresponding song. We implemented a CNN based feature extractor for spectrograms in order to inco

Flavio Del Santo

After World War II, a hyper-pragmatic paradigm was established in physics in most of the western countries, within which foundations of quantum mechanics were vastly dismissed as pointless speculations. In this paper, we show that in Italy, however, the interest toward quantum foundations was revived at the turn of the 1960s, mainly thanks to the initiative

Minling Li, Zheng-an Yao, Rongfeng Yu

We are concerned about the barotropic compressible Navier-Stokes equations with density-dependent viscosities which may degenerate in vacuum. We show that any classical solution to barotropic compressible Navier-Stokes equations in bounded domains will blow up, when the initial density admits an isolated mass group and the viscousity coefficients satisfy som

E. Perfetto, G. Stefanucci

We study the screened dynamics of the nonequilibrium excitonic consensate forming in a bulk WSe$_{2}$ when illuminated by coherent light resonant with the lowest-energy exciton. Intervalley scattering causes electron migration from the optically populated K valley to the conduction band minimum at $\Sigma$. Due to the electron-hole unbalance at the K point a

Christophe Kervazo, Nicolas Gillis, Nicolas Dobigeon

In this work, we consider the problem of blind source separation (BSS) by departing from the usual linear model and focusing on the linear-quadratic (LQ) model. We propose two provably robust and computationally tractable algorithms to tackle this problem under separability assumptions which require the sources to appear as samples in the data set. The first

Uwe Semmelmann, Changliang Wang, M. Y. -K. Wang

In this article we study the stability problem for the Einstein metrics on Sasaki Einstein and on complete nearly parallel ${\rm G}_2$ manifolds. In the Sasaki case we show linear instability if the second Betti number is positive. Similarly we prove that nearly parallel $\rm G_2$ manifolds with positive third Betti number are linearly unstable. Moreover, we

Fangzhou Hong, Hui Zhou, Xinge Zhu, Hongsheng Li

With the rapid advances of autonomous driving, it becomes critical to equip its sensing system with more holistic 3D perception. However, existing works focus on parsing either the objects (e.g. cars and pedestrians) or scenes (e.g. trees and buildings) from the LiDAR sensor. In this work, we address the task of LiDAR-based panoptic segmentation, which aims

Dan Allan, Niklas Hörnedal, Ole Andersson

In this paper, we derive sharp lower bounds, also known as quantum speed limits, for the time it takes to transform a quantum system into a state such that an observable assumes its lowest average value. We assume that the system is initially in an incoherent state relative to the observable and that the state evolves according to a von Neumann equation with

Alex Ling Yu Hung, John Galeotti

Ultrasound 3D compounding is important for volumetric reconstruction, but as of yet there is no consensus on best practices for compounding. Ultrasound images depend on probe direction and the path sound waves pass through, so when multiple intersecting B-scans of the same spot from different perspectives yield different pixel values, there is not a single,

Zhanghan Ke, Jiayu Sun, Kaican Li, Qiong Yan

Existing portrait matting methods either require auxiliary inputs that are costly to obtain or involve multiple stages that are computationally expensive, making them less suitable for real-time applications. In this work, we present a light-weight matting objective decomposition network (MODNet) for portrait matting in real-time with a single input image. T

Franz Kaiser, Henrik Ronellenfitsch, Dirk Witthaut

The structure and design of optimal supply networks is an important topic in complex networks research. A fundamental trait of natural and man-made networks is the emergence of loops and the trade-off governing their formation: adding redundant edges to supply networks is costly, yet beneficial for resilience. Loops typically form when costs for new edges ar

Chih-Hong Cheng

For deep neural networks (DNNs) to be used in safety-critical autonomous driving tasks, it is desirable to monitor in operation time if the input for the DNN is similar to the data used in DNN training. While recent results in monitoring DNN activation patterns provide a sound guarantee due to building an abstraction out of the training data set, reducing fa

Alex Ling Yu Hung, Edward Chen, John Galeotti

Ultrasound image quality has continually been improving. However, when needles or other metallic objects are operating inside the tissue, the resulting reverberation artifacts can severely corrupt the surrounding image quality. Such effects are challenging for existing computer vision algorithms for medical image analysis. Needle reverberation artifacts can

Yingpeng Deng, Lina J. Karam

Although deep neural networks (DNNs) have been shown to be susceptible to image-agnostic adversarial attacks on natural image classification problems, the effects of such attacks on DNN-based texture recognition have yet to be explored. As part of our work, we find that limiting the perturbation's $l_p$ norm in the spatial domain may not be a suitable way to

Alex Ling Yu Hung, Wanwen Chen, John Galeotti

Ultrasound imaging has been improving, but continues to suffer from inherent artifacts that are challenging to model, such as attenuation, shadowing, diffraction, speckle, etc. These artifacts can potentially confuse image analysis algorithms unless an attempt is made to assess the certainty of individual pixel values. Our novel confidence algorithms analyze

Kailai Xu, Eric Darve

ADCME is a novel computational framework to solve inverse problems involving physical simulations and deep neural networks (DNNs). This paper benchmarks its capability to learn spatially-varying physical fields using DNNs. We demonstrate that our approach has superior accuracy compared to the discretization approach on a variety of problems, linear or nonlin

Fredrik Westling, Mitch Bryson, James Underwood

There are numerous emerging applications for digitizing trees using terrestrial and aerial laser scanning, particularly in the fields of agriculture and forestry. Interpretation of LiDAR point clouds is increasingly relying on data-driven methods (such as supervised machine learning) that rely on large quantities of hand-labelled data. As this data is potent

Wenhao Wang, Shengcai Liao, Fang Zhao, Cuicui Kang

Existing person re-identification models often have low generalizability, which is mostly due to limited availability of large-scale labeled data in training. However, labeling large-scale training data is very expensive and time-consuming, while large-scale synthetic dataset shows promising value in learning generalizable person re-identification models. Th

Hao Zheng, Yulei Qin, Yun Gu, Fangfang Xie

Automated airway segmentation is a prerequisite for pre-operative diagnosis and intra-operative navigation for pulmonary intervention. Due to the small size and scattered spatial distribution of peripheral bronchi, this is hampered by severe class imbalance between foreground and background regions, which makes it challenging for CNN-based methods to parse d

Peng Zhou, Rui Peng, Maggie Xu, Victor Wu

This paper presents a point cloud based robotic system for arc welding. Using hand gesture controls, the system scans partial point cloud views of workpiece and reconstructs them into a complete 3D model by a linear iterative closest point algorithm. Then, a bilateral filter is extended to denoise the workpiece model and preserve important geometrical inform

Nikitha Rao, Chetan Bansal, Joe Guan

Developers use search for various tasks such as finding code, documentation, debugging information, etc. In particular, web search is heavily used by developers for finding code examples and snippets during the coding process. Recently, natural language based code search has been an active area of research. However, the lack of real-world large-scale dataset

Shi-Ping He

Top partners are well motivated in many new physics models. Usually, vector like quarks $T_{L,R}$ are introduced to avoid the quantum anomaly. It is crucial to probe their interactions with the standard model particles. However, flavor changing neutral couplings are always difficult to detect directly in the current and future experiments. In this paper, we

Davide Gerosa, Matthew Mould, Daria Gangardt, Patricia Schmidt

Originally designed for waveform approximants, the effective precession parameter $\chi_\mathrm{p}$ is the most commonly used quantity to characterize spin-precession effects in gravitational-wave observations of black-hole binary coalescences. We point out that the current definition of $\chi_\mathrm{p}$ retains some, but not all, variations taking place on

Martin Vollmann

The phenomenology of diffuse radio emission from Dark Matter annihilation or decay in dwarf spheroidal galaxies is examined. We introduce (in the context of cosmic-ray physics) a novel strategy for the computation of the relevant synchrotron signals. In particular, we identify various regimes where, in analogy to prompt gamma rays, the diffuse radio signal f

Noé Pion, Martin Humenberger, Gabriela Csurka, Yohann Cabon

Visual localization, i.e., camera pose estimation in a known scene, is a core component of technologies such as autonomous driving and augmented reality. State-of-the-art localization approaches often rely on image retrieval techniques for one of two tasks: (1) provide an approximate pose estimate or (2) determine which parts of the scene are potentially vis

H. Abels, G. A. Margulis, G. A. Soifer

In 1964 L. Auslander conjectured that every crystallographic subgroup of an the affine group is virtually solvable, i.e. contains a solvable subgroup of finite index. D. Fried and W. Goldman proved Auslander's conjecture for n = 3 using cohomological arguments. We prove the Auslander conjecture for n < 7. The proof is based mainly on dynamical arguments. In

Hideto Nakashima

It is well known that the Riemann zeta function can be completed to the Riemann xi function $\xi(s)$ in the sense that its functional equation has a higher symmetric form $\xi(1-s)=\xi(s)$. In the previous paper (Tohoku Math. J. 72 (2020), 349--378), we give an explicit formula of functional equations between local and global zeta functions associated with a

Yaru Li, Yulai Zhang

Particle swarm optimization (PSO) method cannot be directly used in the problem of hyper-parameter estimation since the mathematical formulation of the mapping from hyper-parameters to loss function or generalization accuracy is unclear. Bayesian optimization (BO) framework is capable of converting the optimization of the hyper-parameters into the optimizati

W. L. Lv, Y. F. Niu, G. Colò

The direct $\gamma$-decays of the giant dipole resonance (GDR) and the giant quadrupole resonance (GQR) of $^{208}$Pb to low-lying states are investigated by means of a microscopic self-consistent model. The model considers effects beyond the linear response approximation. The strong sensitivity of $\gamma$-decay to the isospin of the involved states is prov

Adrian Santos, Sira Vegas, Oscar Dieste, Fernando Uyaguari

Context: Test-driven development (TDD) is an agile software development approach that has been widely claimed to improve software quality. However, the extent to which TDD improves quality appears to be largely dependent upon the characteristics of the study in which it is evaluated (e.g., the research method, participant type, programming environment, etc.)

Yi Yang, Pei-Hung Yuan

We explore QCD phase diagram by constructing a holographic QCD model using the Einstein-Maxwell-Scalar system. The chiral transition is investigated by adding a probe scalar and confinement transition is studied by adding a probe string into the system. By interpreting the black hole phase transition in the bulk spacetime as the quarkyonic transition in the

Zhiqi Wang, Yue Chen, Wolfgang Glänzel

In this study we analyse the key driving factors of preprints in enhancing scholarly communication. To this end we use four groups of metrics, one referring to scholarly communication and based on bibliometric indicators (Web of Science and Scopus citations), while the others reflect usage (usage counts in Web of Science), capture (Mendeley readers) and soci

Dong Luo, Arya Ebadi, Yilun He, Kristen Emery

Recently, Barber and Cand\`es laid the theoretical foundation for a general framework for false discovery rate (FDR) control based on the notion of "knockoffs." A closely related FDR control methodology has long been employed in the analysis of mass spectrometry data, referred to there as "target-decoy competition" (TDC). However, any approach that aims to c

Junyou He, Guibao Mei, Feng Xing, Xiaorui Yang

Click through rate(CTR) prediction is a core task in advertising systems. The booming e-commerce business in our company, results in a growing number of scenes. Most of them are so-called long-tail scenes, which means that the traffic of a single scene is limited, but the overall traffic is considerable. Typical studies mainly focus on serving a single scene