March 2020 arXiv papers — page 24

O. Gorobets, Yu. Gorobets, I. Tiukavkina, R. Gerasimenko

The purpose of the research is the construction of the analytical model for description of spin-polarized current-driven ferromagnetic domain wall motion with a skyrmion building block. The dependence of velocity of ferromagnetic domain wall motion with a skyrmion building block is found as a function of driving torques and an external magnetic field strengt

Alessandra Bertapelle, Emma Previato, Arnab Saha

We extend Borger's construction of algebraic jet spaces to allow for an arbitrary prolongation sequence, clarify the relation between Borger's and Buium's jet spaces and compare them in the extended sense. As a result, we strengthen a result of Buium on the relation between Greenberg's transform and the special fiber of jet spaces, including the ramified cas

Robert D. Skeel, Jan L. Cieśliński

The well known 1956 unpublished report by De Vogelaere, motivated by the physics of particle accelerators, is the first demonstration of the existence of numerical integrators (now called symplectic integrators) that preserve a basic property of Hamiltonian systems. The purpose of this short note is to introduce Ren\'e De Vogelaere, list his pioneering accom

Akira Dohi, Ryotaro Kase, Rampei Kimura, Kazuhiro Yamamoto

We study thermal evolution of isolated neutron stars in scalar-tensor theories for the first time. Whether the rapid cooling due to the direct Urca process occurs or not is an interesting question in the viewpoint of the temperature observation of isolated neutron stars. Moreover, investigation of the cooling effect of nucleon superfluidity also has the larg

Yifang Men, Yiming Mao, Yuning Jiang, Wei-Ying Ma

This paper introduces the Attribute-Decomposed GAN, a novel generative model for controllable person image synthesis, which can produce realistic person images with desired human attributes (e.g., pose, head, upper clothes and pants) provided in various source inputs. The core idea of the proposed model is to embed human attributes into the latent space as i

Joohyung Lee, Youngmoon Jung, Hoirin Kim

Voice activity detection (VAD) is a challenging task in low signal-to-noise ratio (SNR) environment, especially in non-stationary noise. To deal with this issue, we propose a novel attention module that can be integrated in Long Short-Term Memory (LSTM). Our proposed attention module refines each LSTM layer's hidden states so as to make it possible to adapti

Alexander Schindler, Sergiu Gordea, Peter Knees

We present an approach to unsupervised audio representation learning. Based on a triplet neural network architecture, we harnesses semantically related cross-modal information to estimate audio track-relatedness. By applying Latent Semantic Indexing (LSI) we embed corresponding textual information into a latent vector space from which we derive track related

Dongyi Wei, Shiwu Yang

This paper is devoted to the study of asymptotic behaviors of solutions to the one-dimensional defocusing semilinear wave equation. We prove that finite energy solution tends to zero in the pointwise sense, hence improving the averaged decay of Lindblad and Tao. Moreover, for sufficiently localized data belonging to some weighted energy space, the solution d

Munetaka Minoguchi, Ken Okayama, Yutaka Satoh, Hirokatsu Kataoka

To construct an algorithm that can provide robust person detection, we present a dataset with over 8 million images that was produced in a weakly supervised manner. Through labor-intensive human annotation, the person detection research community has produced relatively small datasets containing on the order of 100,000 images, such as the EuroCity Persons da

Souradip Sarkar, Gert-Jan Stockman, Brecht Francois

This work describes the architecture and implementation of a high-data-rate, energy-efficient millimeter-wave (mm-wave) waveguide solution for integration inside an Integrated Circuit (IC) package. The complete waveguide solution (together with couplers) has been designed to fit into the tight dimensional requirements of a wafer bonded 3D package and provide

Tal Gurfinkel, Lyle Noakes, Luchezar Stoyanov

We consider travelling times of billiard trajectories in the exterior of an obstacle K on a two-dimensional Riemannian manifold M. We prove that given two obstacles with almost the same travelling times, the generalised geodesic flows on the non-trapping parts of their respective phase-spaces will have a time-preserving conjugacy. Moreover, if M has non-posi

Thomas Courtat, Hélion du Mas des Bourboux

We present a neural network architecture able to efficiently detect modulation scheme in a portion of I/Q signals. This network is lighter by up to two orders of magnitude than other state-of-the-art architectures working on the same or similar tasks. Moreover, the number of parameters does not depend on the signal duration, which allows processing stream of

Chunyang Wang, Guanglei Ding, Yitong Liu, Huolin L. Xin

Electron tomography, as an important 3D imaging method, offers a powerful method to probe the 3D structure of materials from the nano- to the atomic-scale. However, as a grant challenge, radiation intolerance of the nanoscale samples and the missing-wedge-induced information loss and artifacts greatly hindered us from obtaining 3D atomic structures with high

Sayed Amir Hoseini, Jahan Hassan, Ayub Bokani, Salil S. Kanhere

Despite the increasing popularity of commercial usage of UAVs or drone-delivered services, their dependence on the limited-capacity on-board batteries hinders their flight-time and mission continuity. As such, developing in-situ power transfer solutions for topping-up UAV batteries have the potential to extend their mission duration. In this paper, we study

Fang Li, Jie Pan

Motivated by the phenomenon that compatible Poisson structures on a cluster algebra play a key role on its quantization (that is, quantum cluster algebra), we introduce the second quantization of a quantum cluster algebra, which means the correspondence between compatible Poisson structures of the quantum cluster algebra and its secondly quantized cluster al

Ichiro Oda

We show that in a quadratic gravity based on Weyl's conformal geometry, the Planck mass scale can be generated from quantum effects of the gravitational field and the Weyl gauge field via the Coleman-Weinberg mechanism where a local scale symmetry is broken. At the same time, the Weyl gauge field acquires a mass less than the Planck mass by absorbing the sca

Xiaomin Zhou, Chen Li, Md Mamunur Rahaman, Yudong Yao

Breast cancer is one of the most common and deadliest cancers among women. Since histopathological images contain sufficient phenotypic information, they play an indispensable role in the diagnosis and treatment of breast cancers. To improve the accuracy and objectivity of Breast Histopathological Image Analysis (BHIA), Artificial Neural Network (ANN) approa

Masaaki Umehara, Kotaro Yamada

In the authors' previous work, it was shown that if a zero mean curvature $C^4$-differentiable hypersurface in an arbitrarily given Lorentzian manifold admits a degenerate light-like point, then the hypersurface contains a light-like geodesic segment passing through the point. The purpose of this paper is to point out that the same conclusion holds with just

Wan-Xia Li, Xiao-Ming Xu, H. J. Weber

We study the processes $K\bar{K} \to \phi$, $\pi D \to D^\ast$, $\pi \bar{D} \to \bar{D}^\ast$, and the production of $\psi (3770)$, $\psi (4040)$, $\psi (4160)$, and $\psi (4415)$ mesons in collisions of charmed mesons or charmed strange mesons. The process of 2-to-1 meson-meson scattering involves a quark and an antiquark from the two initial mesons annihi

Xing Huang, Chen-Te Ma

We discover the connection between the Berry curvature and the Riemann curvature tensor in any kinematic space of minimal surfaces anchored on spherical entangling surfaces. This new holographic principle establishes the Riemann geometry in kinematic space of arbitrary dimensions from the holonomy of modular Hamiltonian, which in the higher dimensions is spe

Yakov Eliashberg, Noboru Ogawa, Toru Yoshiyasu

We show that a stabilized convex symplectic (also called Liouville) manifold with the homotopy type of a half dimensional CW-complex is symplectomorphic to a flexible Weinstein manifold.

Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li

Bayesian optimisation is a well-known sample-efficient method for the optimisation of expensive black-box functions. However when dealing with big search spaces the algorithm goes through several low function value regions before reaching the optimum of the function. Since the function evaluations are expensive in terms of both money and time, it may be desi

K. Siddharth Choudary, A. Satyanarayana Reddy

In this article, we prove various properties of Calkin-Wilf tree. We also see how the Minkowski question mark function will act on Calkin-Wilf tree and its diagonals.

Jiangshan Lan, Chandan Mondal, Shaoyang Jia, Xingbo Zhao

We investigate the parton distribution functions (PDFs) of the pion and kaon from the eigenstates of a light-front effective Hamiltonian in the constituent quark-antiquark representation suitable for low-momentum scale applications. By taking these scales as the only free parameters, the valence quark distribution functions of the pion, after QCD evolving, a

T. E. Gureyev, D. M. Paganin, B. Arhatari, S. T. Taba

A method for extracting the dark-field signal in propagation-based phase-contrast imaging is proposed. In the case of objects consisting predominantly of a single material, or several different materials with similar ratios of the real decrement to the imaginary part of the complex refractive index, the proposed method requires a single image for extraction

Shouto Yonekura, Alexandros Beskos

We introduce a methodology for online estimation of smoothing expectations for a class of additive functionals, in the context of a rich family of diffusion processes (that may include jumps) -- observed at discrete-time instances. We overcome the unavailability of the transition density of the underlying SDE by working on the augmented pathspace. The new me

T. V. Gordeychuk, M. V. Kazachek

Time-correlated single photon counting (TCSPC) was used for the first time for resolving a duration and a sequence of the flashes of Na and continuum during MBSL from argon gas saturated aqueous NaCl and SDS solutions. It was found that a bubble giving both kinds of the flashes emits them simultaneously with a negligible delay of about 0.5 ns for Na flash. T

Uǧis Lācis, Petter Johansson, Tomas Fullana, Berk Hess

The movement of the triple contact line plays a crucial role in many applications such as ink-jet printing, liquid coating and drainage (imbibition) in porous media. To design accurate computational tools for these applications, predictive models of the moving contact line are needed. However, the basic mechanisms responsible for movement of the triple conta

Keigo Takeuchi

This paper proposes Bayes-optimal convolutional approximate message-passing (CAMP) for signal recovery in compressed sensing. CAMP uses the same low-complexity matched filter (MF) for interference suppression as approximate message-passing (AMP). To improve the convergence property of AMP for ill-conditioned sensing matrices, the so-called Onsager correction

Hadi Mansourifar, Weidong Shi

Fake face detection is a significant challenge for intelligent systems as generative models become more powerful every single day. As the quality of fake faces increases, the trained models become more and more inefficient to detect the novel fake faces, since the corresponding training data is considered outdated. In this case, robust One-Shot learning meth

Jin Chen, Xijun Wang, Zichao Guo, Xiangyu Zhang

We propose a new convolution called Dynamic Region-Aware Convolution (DRConv), which can automatically assign multiple filters to corresponding spatial regions where features have similar representation. In this way, DRConv outperforms standard convolution in modeling semantic variations. Standard convolutional layer can increase the number of filers to extr

Shuhui Shi

Let $\mathbb{F}_q$ be the finite field of $q$ elements. In this paper, we study the vanishing behavior of multizeta values over $\mathbb{F}_q[t]$ at negative integers. These values are analogs of the classical multizeta values. At negative integers, they are series of products of power sums $S_d(k)$ which are polynomials in $t$. By studying the $t$-valuation

Maoting Tong, Daorong Ton

In this paper we prove that the Navier-Stokes initial value problem (1) has a unique smooth local strong solution and if the following condition are satisfied (1) and is H\"older continuous about on, (2) The initial value

Sunghoon Kim, Ki-Ahm Lee

In this paper, we consider the solution $\bold{u}=\left(u^1,\cdots,u^k\right)$ of the generalized parabolic system \begin{equation*} \left(u^i\right)_t=\nabla\cdot\left(mU^{m-1}\mathcal{A}\left(\nabla u^i,u^i,x,t\right)+\mathcal{B}\left(u^i,x,t\right)\right), \qquad \left(1\leq i\leq k\right) \end{equation*} in the range of exponents $m>\frac{n-2}{n}$ where

Bing Wang, Yong Wu, Xiaoxiao Zhang, Hao Chen

The directional transport of finite size self-propelled Brownian particles confined in a 2D zigzag channel with colored noise is investigated. The noises(noise parallel to x-axis and y-axis), the asymmetry parameter {\Delta}k, the ratio f(ratio of the particle radius and the bottleneck half width), the selfpropelled speed v0 have joint effect on the particle

Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare

We present a distributional approach to theoretical analyses of reinforcement learning algorithms for constant step-sizes. We demonstrate its effectiveness by presenting simple and unified proofs of convergence for a variety of commonly-used methods. We show that value-based methods such as TD($\lambda$) and $Q$-Learning have update rules which are contracti

Chaoyang He, Haishan Ye, Li Shen, Tong Zhang

Many recently proposed methods for Neural Architecture Search (NAS) can be formulated as bilevel optimization. For efficient implementation, its solution requires approximations of second-order methods. In this paper, we demonstrate that gradient errors caused by such approximations lead to suboptimality, in the sense that the optimization procedure fails to

Shuhao Cui, Shuhui Wang, Junbao Zhuo, Liang Li

The learning of the deep networks largely relies on the data with human-annotated labels. In some label insufficient situations, the performance degrades on the decision boundary with high data density. A common solution is to directly minimize the Shannon Entropy, but the side effect caused by entropy minimization, i.e., reduction of the prediction diversit

Fengxiang He, Bohan Wang, Dacheng Tao

Understanding the loss surface of a neural network is fundamentally important to the understanding of deep learning. This paper presents how piecewise linear activation functions substantially shape the loss surfaces of neural networks. We first prove that {\it the loss surfaces of many neural networks have infinite spurious local minima} which are defined a

Wanfu Shen, Yaxu Wei, Chunguang Hu, C. B. Lopez-Posadas

In-plane optical anisotropy has been detected from monolayer MoS$_2$ grown on a-plane (11-20) sapphire substrate in the ultraviolet-visible wavelength range. Based on the measured optical anisotropy, the energy differences between the optical transitions polarized along the ordinary and extraordinary directions of the underlying sapphire substrate have been

Jean Thierry-Mieg

A natural generalization of a Lie algebra connection, or Yang-Mills field, to the case of a Lie-Kac superalgebra, for example SU(m/n), just in terms of ordinary complex functions and differentials, is proposed. Using the chirality $\chi$ which defines the supertrace of the superalgebra: $STr(...) = Tr (\chi ...)$, we construct a covariant differential: $D =

Mingtao Xia, Chris D. Greenman, Tom Chou

Cell division is a process that involves many biochemical steps and complex biophysical mechanisms. To simplify the understanding of what triggers cell division, three basic models that subsume more microscopic cellular processes associated with cell division have been proposed. Cells can divide based on the time elapsed since their birth, their size, and/or

Yanfang Ye, Shifu Hou, Yujie Fan, Yiyue Qian

The novel coronavirus and its deadly outbreak have posed grand challenges to human society: as of March 26, 2020, there have been 85,377 confirmed cases and 1,293 reported deaths in the United States; and the World Health Organization (WHO) characterized coronavirus disease (COVID-19) - which has infected more than 531,000 people with more than 24,000 deaths

Kuan Liu, Da-Bin Lin, Kai Wang, Li Zhou

Although the physical origin of prompt emission in gamma-ray bursts (GRBs) remains inconclusive, previous studies have considered the synchrotron radiation of relativistic electrons as a promising mechanism. These works usually adopted a invariable injection rate of electrons ($Q$) which may be discordant with that in a Poynting-flux dominated jet. In a Poyn

Yang Li, Aljaž Božič, Tianwei Zhang, Yanli Ji

One of the widespread solutions for non-rigid tracking has a nested-loop structure: with Gauss-Newton to minimize a tracking objective in the outer loop, and Preconditioned Conjugate Gradient (PCG) to solve a sparse linear system in the inner loop. In this paper, we employ learnable optimizations to improve tracking robustness and speed up solver convergence

Ya-Yun Ding, Meng-Chao Liu, Jie Zhao, Wen-Qi Yan

Inductively coupled plasma mass (ICP-MS) spectroscopy is widely used for screening materials of low background detectors in dark matter and double beta decay searches due to its high sensitivity to trace $^{238}$U and $^{232}$Th. This work describes a novel co-precipitation approach to measure the amount of $^{238}$U in high-purity copper to sub-ppt level. S

Yutao Jiao, Ping Wang, Dusit Niyato, Bin Lin

Wireless power transfer (WPT) is a promising technology to prolong the lifetime of the sensors and communication devices, i.e., workers, in completing crowdsourcing tasks by providing continuous and cost-effective energy supplies. In this paper, we propose a wireless powered spatial crowdsourcing framework which consists of two mutually dependent phases: tas

Steven W. Gagniere, David A. B. Hyde, Alan Marquez-Razon, Chenfanfu Jiang

We present a hybrid particle/grid approach for simulating incompressible fluids on collocated velocity grids. We interchangeably use particle and grid representations of transported quantities to balance efficiency and accuracy. A novel Backward Semi-Lagrangian method is derived to improve accuracy of grid based advection. Our approach utilizes the implicit

Su-Ping Jin, Xue-Qing Hu, Zhen-Jun Xiao

In this paper, we studied systematically the semileptonic decays $\bar{B}_s \to K^{(*)} \ell^+ \ell^-$ with $l^-=(e^-,\mu^-,\tau^-)$ by using the perturbative QCD (PQCD) and the "PQCD+Lattice" factorization approach, respectively. We first evaluated all relevant form factors $F_i(q^2)$ in the low $q^2$ region using the PQCD approach, and we also take the ava

Masahito Hayashi, Ning Cai

When there exists a malicious attacker in the network, we need to be careful of eavesdropping and contamination. This problem is crucial for network communication when the network is realized by a partially trusted relay of quantum key distribution. We discuss the asymptotic rate in a linear network with the secrecy and robustness conditions when the above t

Zhizheng Zhang, Cuiling Lan, Wenjun Zeng, Zhibo Chen

Video-based person re-identification (reID) aims at matching the same person across video clips. It is a challenging task due to the existence of redundancy among frames, newly revealed appearance, occlusion, and motion blurs. In this paper, we propose an attentive feature aggregation module, namely Multi-Granularity Reference-aided Attentive Feature Aggrega

Masahito Hayashi, Ning Cai

When there exists a malicious attacker in the network, we need to consider the possibilities of eavesdropping and the contamination simultaneously. Under an acyclic broadcast network, the optimality of linear codes was shown when Eve is allowed to attack any $r$ edges. The optimality of linear codes is not shown under a different assumption for Eve. As a typ

Heinrich Dinkel, Yefei Chen, Mengyue Wu, Kai Yu

Traditional supervised voice activity detection (VAD) methods work well in clean and controlled scenarios, with performance severely degrading in real-world applications. One possible bottleneck is that speech in the wild contains unpredictable noise types, hence frame-level label prediction is difficult, which is required for traditional supervised VAD trai

G. G. Baez Flores, Alexey A. Kovalev, M. van Schilfgaarde, K. D. Belashchenko

Spin transport at metallic interfaces is an essential ingredient of various spintronic device concepts, such as giant magnetoresistance, spin-transfer torque, and spin pumping. Spin-orbit coupling plays an important role in many such devices. In particular, spin current is partially absorbed at the interface due to spin-orbit coupling. We develop a general m

BESIII Collaboration

By analyzing a data sample corresponding to an integrated luminosity of $2.93~\mathrm{fb}^{-1}$ collected at a center-of-mass energy of 3.773 GeV with the BESIII detector, we measure for the first time the absolute branching fraction of the $D^+\to \eta \mu^+\nu_\mu$ decay to be ${\mathcal B}_{D^+\to \eta \mu^+\nu_\mu}=(10.4\pm1.0_{\rm stat}\pm0.5_{\rm syst}

Kevin Coulembier

We demonstrate equivalence between two definitions of lower finite highest weight categories. We also show that, in the presence of a duality, a lower finite highest weight structure on a category is unique. Finally, we give a new proof for the fact that any abelian category is extension full in its ind-completion.

Junfang Zhu, Xuezao Ren, Peijie Ma, Kun Gao

Community detection is a significant and challenging task in network research. Nowadays, plenty of attention has been focused on local methods of community detection. Among them, community detection with a greedy algorithm typically starts from the identification of local essential nodes called central nodes of the network; communities expand later from thes

Xuan Wang, Xiangchen Song, Bangzheng Li, Yingjun Guan

We created this CORD-NER dataset with comprehensive named entity recognition (NER) on the COVID-19 Open Research Dataset Challenge (CORD-19) corpus (2020-03-13). This CORD-NER dataset covers 75 fine-grained entity types: In addition to the common biomedical entity types (e.g., genes, chemicals and diseases), it covers many new entity types related explicitly

Alexey S. Zhevlakov, Valery E. Lyubovitskij

We analyze contributions to the electric dipole (EDM) and Schiff (SFM) moments of deuteron induced by the CP-violating three-pseudoscalar meson couplings using phenomenological Lagrangian approach involving nucleons and pseudoscalar mesons $P=\pi, K, \eta, \eta'$. Deuteron is considered as a proton-neutron bound state and its properties are defined by one- a

S. M. Aydin Shoja, Giovanni A. Meles, Kees Wapenaar

The Hessian matrix plays an important role in correct interpretation of the multiple scattered wave fields inside the FWI frame work. Due to the high computational costs, the computation of the Hessian matrix is not feasible. Consequently, FWI produces overburden related artifacts inside the target zone model, due to the lack of the exact Hessian matrix. We

Jun Li, Youjia Chen, Zihuai Lin, Wen Chen

Heterogeneous cellular networks (HCN) with embedded small cells are considered, where multiple mobile users wish to download network content of different popularity. By caching data into the small-cell base stations (SBS), we will design distributed caching optimization algorithms via belief propagation (BP) for minimizing the downloading latency. First, we

Xijiao Mu, Mengtao Sun

The multi-scale computational method of combining first-principles calculation and finite element electromagnetic simulations is used to study plasmon-enhanced interlayer charge transfer (ICT) exciton of 2D lateral and van der Waals MoS2/WS2 heterostructure with 2H phase. The weak ICT excitons are observed in the 2H lateral and van der Waals MoS$_2$/WS$_2$ h

Benjamin Wells

Let \[ \begin{array}{c}\overline{A} = ABCBA\ CBC\ ABCBA,\\ \overline{B} = BCACB\ ACA\ BCACB,\\ \overline{C} = CABAC\ BAB\ CABAC. \end{array} \] The Leech sequence $L$ is the squarefree sequence obtained as the limit of the palindromes \[ A, \overline{A}, \overline{\overline{A}}, \ldots . \] In order to specify a certain class of pseudorecursive varieties of

Yan Zhang, Ze-Yuan Yu, Xin-Ying Li, Zi-Yan Deng

Liquid scintillator (LS) is widely used in various neutrino oscillation experiments, in particular, the reactor neutrino experiments. The complex absorption and re-emission processes of optical photons are known to be an important source of the non-linear and non-uniform response of LS detectors. Precise simulation of light propagation in LS is highly desira

Jak Chakhalian, Xiaoran Liu, Gregory A. Fiete

We highlight recent advances in the theory, materials fabrication, and experimental characterization of strongly correlated and topological states in [111] oriented transition metal oxide thin films and heterostructures, which are notoriously difficult to realize compared to their [001] oriented counterparts. We focus on two classes of complex oxides, with t

Shao-Bo Lin, Di Wang, Ding-Xuan Zhou

This paper focuses on generalization performance analysis for distributed algorithms in the framework of learning theory. Taking distributed kernel ridge regression (DKRR) for example, we succeed in deriving its optimal learning rates in expectation and providing theoretically optimal ranges of the number of local processors. Due to the gap between theory an

Michael Coblenz, Jonathan Aldrich, Joshua Sunshine, Brad A. Myers

Some blockchain programs (smart contracts) have included serious security vulnerabilities. Obsidian is a new typestate-oriented programming language that uses a strong type system to rule out some of these vulnerabilities. Although Obsidian was designed to promote usability to make it as easy as possible to write programs, strong type systems can cause a lan

Jacob Fustos, Michael Bechtel, Heechul Yun

Transient execution attacks utilize micro-architectural covert channels to leak secrets that should not have been accessible during logical program execution. Commonly used micro-architectural covert channels are those that leave lasting footprints in the microarchitectural state, for example, a cache state change, from which the secret is recovered after th

I. M. Son, S. I. Kwak, U. J. Han, J. H. Pak

This paper presents an original method of fuzzy approximate reasoning that can open a new direction of research in the uncertainty inference of Artificial Intelligence(AI) and Computational Intelligence(CI). Fuzzy modus ponens (FMP) and fuzzy modus tollens(FMT) are two fundamental and basic models of general fuzzy approximate reasoning in various fuzzy syste

N. Schunck, J. O'Neal, M. Grosskopf, E. Lawrence

Nuclear density functional theory is the prevalent theoretical framework for accurately describing nuclear properties at the scale of the entire chart of nuclides. Given an energy functional and a many-body scheme (e.g., single- or multireference level), the predictive power of the theory depends strongly on how the parameters of the energy functionals have

Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière

One of the challenges in machine learning research is to ensure that presented and published results are sound and reliable. Reproducibility, that is obtaining similar results as presented in a paper or talk, using the same code and data (when available), is a necessary step to verify the reliability of research findings. Reproducibility is also an important

Huiqiang Zhong, Cunxiang Yin, Xiaohui Wu, Jinchang Luo

Urban air pollution has become a major environmental problem that threatens public health. It has become increasingly important to infer fine-grained urban air quality based on existing monitoring stations. One of the challenges is how to effectively select some relevant stations for air quality inference. In this paper, we propose a novel model based on rei

Xianxin Wu, Wladimir A. Benalcazar, Yinxiang Li, Ronny Thomale

Non-trivial topology and unconventional pairing are two central guiding principles in the contemporary search for and analysis of superconducting materials and heterostructure compounds. Previously, a topological superconductor has been predominantly conceived to result from a topologically non-trivial band subject to intrinsic or external superconducting pr

Kai Zhao, Sheng Di, Sihuan Li, Xin Liang

Convolutional neural networks (CNNs) are becoming more and more important for solving challenging and critical problems in many fields. CNN inference applications have been deployed in safety-critical systems, which may suffer from soft errors caused by high-energy particles, high temperature, or abnormal voltage. Of critical importance is ensuring the stabi

Thanapat Worasaran, Matthias S. Ikeda, Johanna C. Palmstrom, Joshua A. W. Straquadine

Quantum criticality has been invoked as being essential to the understanding of a wide range of exotic electronic behavior, including heavy Fermion and unconventional superconductivity, but conclusive evidence of quantum critical fluctuations has been elusive in many materials of current interest. An expected characteristic feature of quantum criticality is

Rinie N. M. Nasir, Jesni Shamsul Shaari, Stefano Mancini

Analogous to the notion of mutually unbiased bases for Hilbert spaces, we consider mutually unbiased unitary bases (MUUB) for the space of operators, $M(d, \mathbb{C})$, acting on such Hilbert spaces. The notion of MUUB reflects the equiprobable guesses of unitary in one bases of $M(d, \mathbb{C})$ when estimating a unitary operator in another. Though, for p

Tommaso Rigon, Bruno Scarpa, Sonia Petrone

In Bayesian nonparametrics there exists a rich variety of discrete priors, including the Dirichlet process and its generalizations, which are nowadays well-established tools. Despite the remarkable advances, few proposals are tailored for modeling observations lying on product spaces, such as $\mathbb{R}^p$. Indeed, for multivariate random measures, most ava

Jan Macdonald, Maximilian März, Luis Oala, Wojciech Samek

This work investigates the detection of instabilities that may occur when utilizing deep learning models for image reconstruction tasks. Although neural networks often empirically outperform traditional reconstruction methods, their usage for sensitive medical applications remains controversial. Indeed, in a recent series of works, it has been demonstrated t

George Thomas, Azat Gubaydullin, Dmitry S. Golubev, Jukka P. Pekola

We present a theoretical model of an on-chip three-level maser in a superconducting circuit based on a single artificial atom and pumped by a temperature gradient between thermal baths coupled to different interlevel transitions. We show that maser powers of the order of a few femtowatts, well exceeding the resolution of the sensitive bolometry, can be achie

Xingwei Hu

When ranking big data observations such as colleges in the United States, diverse consumers reveal heterogeneous preferences. The objective of this paper is to sort out a linear ordering for these observations and to recommend strategies to improve their relative positions in the ranking. A properly sorted solution could help consumers make the right choices

Joshua J. Engelsma, Anil K. Jain, Vishnu Naresh Boddeti

We present a method to search for a probe (or query) image representation against a large gallery in the encrypted domain. We require that the probe and gallery images be represented in terms of a fixed-length representation, which is typical for representations obtained from learned networks. Our encryption scheme is agnostic to how the fixed-length represe

Yuta Ito

This is the first paper of a series of our works on the self-similar orbit-averaged Fokker-Planck (OAFP) equation for distribution function of stars in dense isotropic star clusters. At the late stage of relaxation evolution of the clusters, standard stellar dynamics predicts that the clusters evolve in a self-similar fashion forming collapsing cores. Howeve

Indrajit Sen, Antony Valentini

We prove that superdeterministic models of quantum mechanics are conspiratorial in a mathematically well-defined sense, by further development of the ideas presented in a previous article $\mathcal{A}$. We consider a Bell scenario where, in each run and at each wing, the experimenter chooses one of $N$ devices to determine the local measurement setting. We p

Philippe Chatigny, Jean-Marc Patenaude, Shengrui Wang

Optimal decision-making in social settings is often based on forecasts from time series (TS) data. Recently, several approaches using deep neural networks (DNNs) such as recurrent neural networks (RNNs) have been introduced for TS forecasting and have shown promising results. However, the applicability of these approaches is being questioned for TS settings

Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang

{\em Hypernetworks} are architectures that produce the weights of a task-specific {\em primary network}. A notable application of hypernetworks in the recent literature involves learning to output functional representations. In these scenarios, the hypernetwork learns a representation corresponding to the weights of a shallow MLP, which typically encodes sha

Nitasha Sahani, Manish Kumar Singh, Chen-Ching Liu

The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable effects include overloading of transformers, rapid voltage fluctuations, and over/under voltages. While this compromises the consumer power quality, it also puts on extra stress o

Sepehr Ehsani

The spike glycoprotein of the SARS-CoV-2 virus, which causes COVID-19, has attracted attention for its vaccine potential and binding capacity to host cell surface receptors. Much of this research focus has centered on the ectodomain of the spike protein. The ectodomain is anchored to a transmembrane region, followed by a cytoplasmic tail. Here we report a di

X. Zhao, S. Marchesi, M. Ajello, M. balokovic

In modeling the X-ray spectra of active galactic nuclei (AGNs), the inclination angle is a parameter that can play an important role in analyzing the X-ray spectra of AGN, but it has never been studied in detail. We present a broadband X-ray spectral analysis of the joint NuSTAR-XMM-Newton observations of 13 sources with [OIII] measured inclinations determin

Giacomo Baggio, Danielle S. Bassett, Fabio Pasqualetti

Our ability to manipulate the behavior of complex networks depends on the design of efficient control algorithms and, critically, on the availability of an accurate and tractable model of the network dynamics. While the design of control algorithms for network systems has seen notable advances in the past few years, knowledge of the network dynamics is a ubi

Zhaoyang Sun, Wenxuan Liu, Feng Liu, Ryan Wen Liu

Facial makeup transfer aims to render a non-makeup face image in an arbitrary given makeup one while preserving face identity. The most advanced method separates makeup style information from face images to realize makeup transfer. However, makeup style includes several semantic clear local styles which are still entangled together. In this paper, we propose

Teruo Nagase, Akiko Shima

Let $\Gamma$ be a chart, and we denote by $\Gamma_m$ the union of all the edges of label $m$. A chart $\Gamma$ is of type $(2,3,2)$ if there exists a label $m$ such that $w(\Gamma)=7$, $w(\Gamma_m\cap\Gamma_{m+1})=2$, $w(\Gamma_{m+1}\cap\Gamma_{m+2})=3$, and $w(\Gamma_{m+2}\cap\Gamma_{m+3})=2$ where $w(G)$ is the number of white vertices in $G$. In this pape

Joel Gard, Greg Morrison

Polymer models describing the statistics of biomolecules under confinement have applications to a wide range of single molecule experimental techniques and give insight into biologically relevant processes {\em{in vivo}}. In this paper, we determine the transverse position and bending correlation functions for a wormlike chain confined within slits and cylin

Jianhua Qin, Ebrahim M. Kolahdouz, Boyce E. Griffith

An immersed interface-lattice Boltzmann method (II-LBM) is developed for modelling fluid-structure systems. The key element of this approach is the determination of the jump conditions that are satisfied by the distribution functions within the framework of the lattice Boltzmann method when forces are imposed along a surface immersed in an incompressible flu

Sathyanarayanan N. Aakur, Sudeep Sarkar

The problem of action recognition involves locating the action in the video, both over time and spatially in the image. The dominant current approaches use supervised learning to solve this problem, and require large amounts of annotated training data, in the form of frame-level bounding box annotations around the region of interest. In this paper, we presen

Fereshte Shahbeigi, David Amaro-Alcalá, Zbigniew Puchała, Karol Życzkowski

We analyze the set ${\cal A}_N^Q$ of mixed unitary channels represented in the Weyl basis and accessible by a Lindblad semigroup acting on an $N$-level quantum system. General necessary and sufficient conditions for a mixed Weyl quantum channel of an arbitrary dimension to be accessible by a semigroup are established. The set ${\cal A}_N^Q$ is shown to be lo

Dongdong Yang, Kevin Dyer, Senzhang Wang

In online advertising, users may be exposed to a range of different advertising campaigns, such as natural search or referral or organic search, before leading to a final transaction. Estimating the contribution of advertising campaigns on the user's journey is very meaningful and crucial. A marketer could observe each customer's interaction with different m

Hongyao Chen, Shi Huang

Recent studies have shown that hybridization between modern and archaic humans was commonplace in the history of our species. After admixture, some individuals with admixed autosomes carried the modern Homo Sapiens uniparental DNAs, while the rest carried the archaic versions. Coevolution of admixed autosomes and uniparental DNAs is expected to cause some of

Andreas A. Malikopoulos, Logan E. Beaver, Ioannis Vasileios Chremos

In this paper, we provide a decentralized theoretical framework for coordination of connected and automated vehicles (CAVs) at different traffic scenarios. The framework includes: (1) an upper-level optimization that yields for each CAV its optimal time trajectory and lane to pass through a given traffic scenario while alleviating congestion; and (2) a low-l

Lorenzo Trapani, Emily Whitehouse

We develop monitoring procedures for cointegrating regressions, testing the null of no breaks against the alternatives that there is either a change in the slope, or a change to non-cointegration. After observing the regression for a calibration sample m, we study a CUSUM-type statistic to detect the presence of change during a monitoring horizon m+1,...,T.

Gopal Sharma, Difan Liu, Subhransu Maji, Evangelos Kalogerakis

We propose a novel, end-to-end trainable, deep network called ParSeNet that decomposes a 3D point cloud into parametric surface patches, including B-spline patches as well as basic geometric primitives. ParSeNet is trained on a large-scale dataset of man-made 3D shapes and captures high-level semantic priors for shape decomposition. It handles a much richer