November 2020 arXiv papers — page 13

Alexander Zlotnik, Olga Kireeva

We consider compact finite-difference schemes of the 4th approximation order for an initial-boundary value problem (IBVP) for the $n$-dimensional non-homogeneous wave equation, $n\geq 1$. Their construction is accomplished by both the classical Numerov approach and alternative technique based on averaging of the equation, together with further necessary impr

Chuang-Shi Shen, Chun-Lin Du, Huan-Fang Wang, Chao Zhang

Two novel single-period cracks were observed in experiments of cutting a folded sheet with a blunt object and tearing a thin brittle sheet under the guidance of a meterstick. Additionally, we observed a period-doubling crack in the tearing experiment. We cut and tore the sheet in different directions. The experimental results suggested that the anisotropy of

Ali Gholami, Hossein S. Aghamiry, Stephane Operto

Extended full-waveform inversion (FWI) has shown promising results for accurate estimation of subsurface parameters when the initial models are not sufficiently accurate. Frequency-domain applications have shown that the augmented Lagrangian (AL) method solves the inverse problem accurately with a minimal effect of the penalty parameter choice. Applying this

Florian Dubost, Erin Hong, Nandita Bhaskhar, Siyi Tang

Labeled data is a critical resource for training and evaluating machine learning models. However, many real-life datasets are only partially labeled. We propose a semi-supervised machine learning training strategy to improve event detection performance on sequential data, such as video recordings, when only sparse labels are available, such as event start ti

Afsaneh Shamsaki, Peyman Niroomand

In this paper, we give the explicit structure of $ \otimes^{3} H $ and $ \wedge^{3} H $ where $ H $ is a generalized Heisenberg Lie algebra of rank at most $ 2. $ Moreover, for a non-abelian nilpotent Lie algebra $ L, $ we obtain an upper bound for the dimension of $ \otimes^{3} L.

Jinxing Li, Hiroya Nishikawa, Junichi Kougo, Junchen Zhou

Super-high-\k{appa} materials that exhibit exceptionally high dielectric permittivity are recognized as potential candidates for a wide range of next-generation photonic and electronic devices. Generally, the high dielectricity for achieving a high-\k{appa} state requires a low symmetry of materials so that most of the discovered high-\k{appa} materials are

Anke Pohl

We provide special cross sections for the Weyl chamber flow on a sample class of Riemannian locally symmetric spaces of higher rank, namely the direct product spaces of Schottky surfaces. We further present multi-parameter transfer operator families for the discrete dynamical systems on Furstenberg boundary that are related to these cross sections.

Shohreh Deldari, Daniel V. Smith, Hao Xue, Flora D. Salim

Change Point Detection (CPD) methods identify the times associated with changes in the trends and properties of time series data in order to describe the underlying behaviour of the system. For instance, detecting the changes and anomalies associated with web service usage, application usage or human behaviour can provide valuable insights for downstream mod

Shunya Saito

A triangulated category $\mathcal{T}$ whose suspension functor $\Sigma$ satisfies $\Sigma^m \simeq \mathrm{Id}_{\mathcal{T}}$ as additive functors is called an $m$-periodic triangulated category. Such a category does not have a tilting object by the periodicity. In this paper, we introduce the notion of an $m$-periodic tilting object in an $m$-periodic trian

Seokchang Hong

We study initial value problem of the $(1+4)$-dimensional Maxwell-Klein-Gordon system (MKG) in the Lorenz gauge. Since (MKG) in the Lorenz gauge does not possess an obvious null structure, it is not easy to handle the nonlinearity. To overcome this obstacle, we impose an additional angular regularity. In this paper, we prove global well-posedness and scatter

Giampiero M. Gallo, Demetrio Lacava, Edoardo Otranto

The financial turmoil surrounding the Great Recession called for unprecedented intervention by Central Banks: unconventional policies affected various areas in the economy, including stock market volatility. In order to evaluate such effects, by including Markov Switching dynamics within a recent Multiplicative Error Model, we propose a model--based classifi

Jiří Doležal, Sofia Canola, Pablo Merino, Martin Švec

Charged optical excitations (trions) generated by charge carrier injection are crucial for emerging optoelectronic technologies as they can be produced and manipulated by electric fields. Trions and neutral excitons can be efficiently induced in single molecules by means of tip-enhanced spectromicroscopic techniques. However, little is known of the exciton-t

Tomoo Yokoyama

We construct topological invariants, called abstract weak orbit spaces, of flows and homeomorphisms on topological spaces, to describe both gradient dynamics and recurrent dynamics. In particular, the abstract weak orbit spaces of flows on topological spaces are generalizations of both Morse graphs of flows on compact metric spaces and Reeb graphs of Hamilto

Lei Zhang, Richard N. Manchester, Andrew D. Cameron, George Hobbs

We report the first wideband monitoring observations of PSR J1803-3002A, a relatively bright millisecond pulsar in the globular cluster NGC 6522 with a spin period of 7.1 ms and no known binary companion. These observations were performed using the Parkes 64-m radio telescope with the Ultra-Wideband Low (UWL) receiver system, which covers 704 to 4032 MHz. We

Liding Huang, Jiaogen Zhang, Xi Zhang

In this paper, we consider the deformed Hermitian-Yang-Mills equation on closed almost Hermitian manifolds. In the case of hypercritical phase, we derive a priori estimates under the existence of an admissible $\mathcal{C}$-subsolution. As an application, we prove the existence of solutions for the deformed Hermitian-Yang-Mills equation under the condition o

Tao Xiong, Wenjun Sun, Yi Shi, Peng Song

In this paper, we will develop a class of high order asymptotic preserving (AP) discontinuous Galerkin (DG) methods for nonlinear time-dependent gray radiative transfer equations (GRTEs). Inspired by the work \cite{Peng2020stability}, in which stability enhanced high order AP DG methods are proposed for linear transport equations, we propose to pernalize the

Baudouin Denis de Senneville, Chrit Moonen, Mario Ries

MRI-guided High Intensity Focused Ultrasound (MRI-HIFU) is a promising method for the non-invasive ablation of pathological tissue in many organs, including mobile organs such as liver and kidney. The possibility to locally deposit thermal energy in a non-invasive way opens a path towards new therapeutic strategies with improved reliability and reduced assoc

Yu Feng, Bingyang Hu, Xiaoqian Xu

We consider following fourth-order parabolic equation with gradient nonlinearity on the two-dimensional torus with and without advection of an incompressible vector field in the case $2<p<3$: \begin{equation*} \partial_t u + (-\Delta)^2 u = -\nabla\cdot(|\nabla u|^{p-2}\nabla u). \end{equation*} The study of this form of equations arises from mathematical mo

Paul Wimmer, Jens Mehnert, Alexandru Condurache

Pruning generates sparse networks by setting parameters to zero. In this work we improve one-shot pruning methods, applied before training, without adding any additional storage costs while preserving the sparse gradient computations. The main difference to pruning is that we do not sparsify the network's weights but learn just a few key parameters and keep

Ki-Seok Choi, K. S. Kim, Myung-Ki Cheoun, W. Y. So

We discuss the role of deformation of the target nucleus in the fusion reaction of the $^{15}$C + $^{232}$Th system at energies around the Coulomb barrier, for which $^{15}$C is a well-known one-neutron halo nucleus. To this end, we construct the potential between $^{15}$C and $^{232}$Th with the double folding procedure, assuming that the projectile nucleus

Ching-Chia Kao, Jhe-Bang Ko, Chun-Shien Lu

Randomized smoothing has established state-of-the-art provable robustness against $\ell_2$ norm adversarial attacks with high probability. However, the introduced Gaussian data augmentation causes a severe decrease in natural accuracy. We come up with a question, "Is it possible to construct a smoothed classifier without randomization while maintaining natur

Ke Shen, Mayank Kejriwal

Acquiring commonsense knowledge and reasoning is recognized as an important frontier in achieving general Artificial Intelligence (AI). Recent research in the Natural Language Processing (NLP) community has demonstrated significant progress in this problem setting. Despite this progress, which is mainly on multiple-choice question answering tasks in limited

Guangze Li, Huangwei Zhang, Longfei Chen

Large eddy simulations with three-dimensional finite-volume Conditional Moment Closure (CMC) model are performed for a hydrogen / nitrogen lifted flame with detailed chemical meachanism. The emphasis is laid on the influences of mesh resolution and convection scheme of finite-volume CMC model on predictions of reactive scalar distribution and unsteady flame

S. Selenu

In this article it will be presented the first attempt made in order to perform gauge invariant calculations of eigenstates of a quantum body in its condensed phase, the latter reacting to an external uniform magnetic field. The target is achieved introducing a new unitary translation operator transforming eigenstates into a new set of eigenstates having dif

Merab Gogberashvili, Alexandre Gurchumelia

The known equivalence of 8-dimensional chiral spinors and vectors, also referred to as triality, is discussed for (4+4)-space. Split octonionic representation of SO(4,4) and Spin(4,4) groups and the trilinear invariant form are explicitly written and compared with Clifford algebraic matrix representation. It is noted that the complete algebra of split octoni

J. S. Bobowski

In this paper we describe a couple of exercises that we developed for our online first-year EM course. The labs that we describe are focused on basic concepts from circuit analysis, namely Ohm's law and charging a capacitor with a constant voltage source and a series resistor. To give students a visual demonstration of these concepts and, simultaneously, pro

Changeez Amini, Paeiz Azmi, Seyed Sadra Kashef

In this paper, an improved channel model of visible light communication (VLC) for ranging in presented. For indoor channel model of VLC, distance is estimated based on received signal strength. In this model, received shot noise as a distance-dependent parameter is considered in range estimation accuracy. Moreover, based on this model, the Cramer-Rao lower b

V. V. Mikhailenko, V. S. Mikhailenko, H. J. Lee

The theory of the nonmodal ion-acoustic instability in the skin layer of the inductively coupled plasma (ICP) is developed. This instability has time dependent growth rate and is driven by the current formed in the skin layer by the accelerated motion of electrons relative to ions under the action of the ponderomotive force. It is found that the development

Sambaran Bandyopadhyay, Vishal Peter

Graph neural networks (GNNs) are able to achieve promising performance on multiple graph downstream tasks such as node classification and link prediction. Comparatively lesser work has been done to design GNNs which can operate directly for community detection on graphs. Traditionally, GNNs are trained on a semi-supervised or self-supervised loss function an

I. A. Rather, A. A. Usmani, S. K. Patra

The properties of the neutron stars are calculated for the hadronic matter within the density-dependent relativistic mean-field model (DD-RMF). The phase transition to the quark matter is studied and the hybrid star matter properties are systematically calculated using the Vector-Enhanced Bag model (vBag). The maximum mass of neutron star with DD-LZ1 and DD-

Aaron Babier, Binghao Zhang, Rafid Mahmood, Kevin L. Moore

The purpose of this work is to advance fair and consistent comparisons of dose prediction methods for knowledge-based planning (KBP) in radiation therapy research. We hosted OpenKBP, a 2020 AAPM Grand Challenge, and challenged participants to develop the best method for predicting the dose of contoured CT images. The models were evaluated according to two se

Benjamin Laufer

In the criminal legal context, risk assessment algorithms are touted as data-driven, well-tested tools. Studies known as validation tests are typically cited by practitioners to show that a particular risk assessment algorithm has predictive accuracy, establishes legitimate differences between risk groups, and maintains some measure of group fairness in trea

Jordan Mitchell Barrett, Valentino Vito

For fixed finite graphs $G$, $H$, a common problem in Ramsey theory is to study graphs $F$ such that $F \to (G,H)$, i.e. every red-blue coloring of the edges of $F$ produces either a red $G$ or a blue $H$. We generalize this study to infinite graphs $G$, $H$; in particular, we want to determine if there is a minimal such $F$. This problem has strong connecti

Animesh Yadav, Chen Quan, Pramod K. Varshney, H. Vincent Poor

In this paper, we study the uplink channel throughput performance of a proposed novel multiple-antenna hybrid-domain non-orthogonal multiple access (MA-HD-NOMA) scheme. This scheme combines the conventional sparse code multiple access (SCMA) and power-domain NOMA (PD-NOMA) schemes in order to increase the number of users served as compared to conventional NO

Rajesh Kumar, Arvind Kumar

We study the $\eta N$ interactions in the hot and dense isospin asymmetric nuclear matter using two different approaches. In the first approach, the in-medium mass and optical potential of $\eta$-meson have been calculated in the chiral SU(3) model, considering the effect of explicit symmetry breaking term and range terms in the $\eta N$ interaction Lagrangi

Sekhar Jyoti Baishya

A finite group $G$ is called an F-group if for every $x, y \in G \setminus Z(G)$, $C(x) \leq C(y)$ implies that $C(x) = C(y)$. On the otherhand, two elements of a group are said to be $z$-equivalent or in the same $z$-class if their centralizers are conjugate in the group. In this paper, for a finite group, we give necessary and sufficient conditions for the

Declan McIntosh, Tunai Porto Marques, Alexandra Branzan Albu, Rodney Rountree

Global warming is predicted to profoundly impact ocean ecosystems. Fish behavior is an important indicator of changes in such marine environments. Thus, the automatic identification of key fish behavior in videos represents a much needed tool for marine researchers, enabling them to study climate change-related phenomena. We offer a dataset of sablefish (Ano

Jean Bertoin

A random walk with counterbalanced steps is a process of partial sums $\check S(n)=\check X_1+ \cdots + \check X_n$ whose steps $\check X_n$ are given recursively as follows. For each $n\geq 2$, with a fixed probability $p$, $\check X_n$ is a new independent sample from some fixed law $\mu$, and with complementary probability $1-p$, $\check X_n= -\check X_{v

Xiaozhong Xu, Shan Liu

In recent years, screen content (SC) video including computer generated text, graphics and animations, have drawn more attention than ever, as many related applications become very popular. To address the need for efficient coding of such contents, a number of coding tools have been specifically developed and achieved great advances in terms of coding effici

Pantea Kiaei, Cees-Bart Breunesse, Mohsen Ahmadi, Patrick Schaumont

Fault injection attacks can cause errors in software for malicious purposes. Oftentimes, vulnerable points of a program are detected after its development. It is therefore critical for the user of the program to be able to apply last-minute security assurance to the executable file without having access to the source code. In this work, we explore two method

Leo K. Tam, Xiaosong Wang, Daguang Xu

Previous work established skip-gram word2vec models could be used to mine knowledge in the materials science literature for the discovery of thermoelectrics. Recent transformer architectures have shown great progress in language modeling and associated fine-tuned tasks, but they have yet to be adapted for drug discovery. We present a RoBERTa transformer-base

Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi

Over-parameterization and adaptive methods have played a crucial role in the success of deep learning in the last decade. The widespread use of over-parameterization has forced us to rethink generalization by bringing forth new phenomena, such as implicit regularization of optimization algorithms and double descent with training progression. A series of rece

André Rafael Cunha, Celso Peres Fernandes, Luís Orlando Emerich dos Santos

We explore the experimental observation that complex networks of porous media exhibit the property that the porous coordination number is proportional to its size. Based in this geometry-topology duality we developed an analytical approach to describe the permeability transport property of the material. That results was compared with 2D networks simulations.

Yingying Zhou, Zhao-Yu Li, Iulia Simion, Juntai Shen

We revisit the stellar velocity distribution in the Galactic bulge/bar region with APOGEE DR16 and {\it Gaia} DR2, focusing in particular on the possible high-velocity (HV) peaks and their physical origin. We fit the velocity distributions with two different models, namely with Gauss-Hermite polynomial and Gaussian mixture model (GMM). The result of the fit

Xuehai Huang, Yuling Shi, Wenqing Wang

A Morley-Wang-Xu (MWX) element method with a simply modified right hand side is proposed for a fourth order elliptic singular perturbation problem, in which the discrete bilinear form is standard as usual nonconforming finite element methods. The sharp error analysis is given for this MWX element method. And the Nitsche's technique is applied to the MXW elem

Pablo Leandro Bonucci, Nicolás Ariel Capitelli

In this article we introduce the notion of weak harmonic labeling of a graph, a generalization of the concept of harmonic labeling defined recently by Benjamini et al. that allows extension to finite graphs and graphs with leaves. We present various families of examples and provide several constructions that extend a given weak harmonic labeling to larger gr

Man-Ling Sung, Tan Lee

Spoken term discovery from untranscribed speech audio could be achieved via a two-stage process. In the first stage, the unlabelled speech is decoded into a sequence of subword units that are learned and modelled in an unsupervised manner. In the second stage, partial sequence matching and clustering are performed on the decoded subword sequences, resulting

Xiaolei Fang, Renjie Jin, Jinquan Luo, Wen Ma

Galois hulls of linear codes have important applications in quantum coding theory. In this paper, we construct some new classes of (extended) generalized Reed-Solomon (GRS) codes with Galois hulls of arbitrary dimensions. We also propose a general method on constructing GRS codes with Galois hulls of arbitrary dimensions from special Euclidean orthogonal GRS

Man-Ling Sung

(Part of the abstract) In this thesis, we investigate the use of unsupervised spoken term discovery in tackling this problem. Unsupervised spoken term discovery aims to discover topic-related terminologies in a speech without knowing the phonetic properties of the language and content. It can be further divided into two parts: Acoustic segment modelling (ASM

Yanhong A. Liu, Matthew Castelllana

Discrete mathematics is the foundation of computer science. It focuses on concepts and reasoning methods that are studied using math notations. It has long been argued that discrete math is better taught with programming, which takes concepts and computing methods and turns them into executable programs. What has been lacking is a principled approach that su

Zhongzhan Huang, Senwei Liang, Mingfu Liang, Wei He

Recently, many plug-and-play self-attention modules are proposed to enhance the model generalization by exploiting the internal information of deep convolutional neural networks (CNNs). Previous works lay an emphasis on the design of attention module for specific functionality, e.g., light-weighted or task-oriented attention. However, they ignore the importa

Hans Riess, Jakob Hansen, Robert Ghrist

Multiparameter persistent homology has been largely neglected as an input to machine learning algorithms. We consider the use of lattice-based convolutional neural network layers as a tool for the analysis of features arising from multiparameter persistence modules. We find that these show promise as an alternative to convolutions for the classification of m

André Rafael Cunha, Celso Peres Fernandes, Luís Orlando Emerich dos Santos, Denise Prado Kronbauer

The interconnectivity of the porous space is an important characteristic in the study of porous media and their transport properties. Hence we propose a way to quantify it and relate it with the intrinsic permeability of rocks. We propose a measure of connectivity based on geometric and topological information of pore-throat network, which are models built f

Anthony D'Arienzo, Vinny Pagano, Ian M. J. McInnis

We make explicit the correspondence between syntax and syntactic categories for coherent first-order logic, providing a categorical characterization of bi-interpretability. This is done by creating a biequivalence between a bicategory of coherent theories and the (strict) bicategory of coherent categories. While the biequivalence concerns the stronger equali

KJ Li, JC Xu, JL Xie, W Feng

Differential rotation is the basis of the solar dynamo theory. Synoptic maps of He I intensity from Carrington rotations 2032 to 2135 are utilized to investigate the differential rotation of the solar chromosphere in the He I absorption line. The chromosphere is surprisingly found to rotate faster than the photosphere below it. The anomalous heating of the c

Junru Wu, Xiang Yu, Buyu Liu, Zhangyang Wang

Face anti-spoofing (FAS) seeks to discriminate genuine faces from fake ones arising from any type of spoofing attack. Due to the wide varieties of attacks, it is implausible to obtain training data that spans all attack types. We propose to leverage physical cues to attain better generalization on unseen domains. As a specific demonstration, we use physicall

Manoj K. Yennapureddy, Fulvio Melia

Inflation drives quantum fluctuations beyond the Hubble horizon, freezing them out before the small-scale modes re-enter during the radiation dominated epoch, and subsequently decay, while large-scale modes re-enter later during the matter dominated epoch and grow. This distinction shapes the matter power spectrum and provides observational evidence in suppo

I. L. V. Roque, W. J. Handley, N. Razavi-Ghods

Detection of millikelvin-level signals from the 'Cosmic Dawn' requires an unprecedented level of sensitivity and systematic calibration. We report the theory behind a novel calibration algorithm developed from the formalism introduced by the EDGES collaboration for use in 21-cm experiments. Improvements over previous approaches are provided through the incor

Jing Li, Ling Ren, Dongning Guo

Bitcoin is a peer-to-peer electronic cash system invented by Nakamoto in 2008. While it has attracted much research interest, its exact latency and security properties remain open. Existing analyses provide security and latency (or confirmation time) guarantees that are too loose for practical use. In fact the best known upper bounds are several orders of ma

Chenxi Ma, Daming Zheng, Dominique Demaille, Bruno Gallas

While perovskite solar cells (PSCs) are now reaching high power conversion efficiencies (PCEs), further performance improvement requires a fine management and an optimization of the light pathway and harvesting in the cells. These go through an accurate understanding, characterization and modelling of the optical processes occurring in these complex, often t

Sungyong Hwang, Myungshin Im, Yoon Chan Taak, Insu Paek

TXS 0506+056 is a blazar that has been recently identified as the counterpart of the neutrino event IceCube-170922A. Understanding blazar type of TXS 0506+056 is important to constrain the neutrino emission mechanism, but the blazar nature of TXS 0506+056 is still uncertain. As an attempt to understand the nature of TXS 0506+056, we report the medium-band ob

Amrith Setlur, Oscar Li, Virginia Smith

Meta-learning is a popular framework for learning with limited data in which an algorithm is produced by training over multiple few-shot learning tasks. For classification problems, these tasks are typically constructed by sampling a small number of support and query examples from a subset of the classes. While conventional wisdom is that task diversity shou

Cesar F. Caiafa, Ziyao Wang, Jordi Solé-Casals, Qibin Zhao

In this paper, the problem of training a classifier on a dataset with incomplete features is addressed. We assume that different subsets of features (random or structured) are available at each data instance. This situation typically occurs in the applications when not all the features are collected for every data sample. A new supervised learning method is

Mandana Samiei, Caroline Weis, Larissa Schiavo, Tatjana Chavdarova

This report is an account of the authors' experiences as organizers of WiML's "Un-Workshop" event at ICML 2020. Un-workshops focus on participant-driven structured discussions on a pre-selected topic. For clarity, this event was different from the "WiML Workshop", which is usually co-located with NeurIPS. In this manuscript, organizers, share their experienc

Chinasa T. Okolo

As AI becomes integrated throughout the world, its potential for impact within low-resource regions around the Global South have grown. AI research labs from tech giants like Microsoft, Google, and IBM have a significant presence in countries such as India, Ghana, and South Africa. The work done by these labs is often motivated by the potential impact it cou

Huo Chen, Daniel A. Lidar

We present an open-source software package called "Hamiltonian Open Quantum System Toolkit" (HOQST), a collection of tools for the investigation of open quantum system dynamics in Hamiltonian quantum computing, including both quantum annealing and the gate-model of quantum computing. It features the key master equations (MEs) used in the field, suitable for

Haojing Shen, Sihong Chen, Ran Wang, Xizhao Wang

In this paper, we propose a defence strategy to improve adversarial robustness by incorporating hidden layer representation. The key of this defence strategy aims to compress or filter input information including adversarial perturbation. And this defence strategy can be regarded as an activation function which can be applied to any kind of neural network. W

Tiago Lopes Soares

In this report, we present the preliminary work developed for our research project for the APDC (\'Area Pr\'atica de Desenvolvimento Curricular) course. The main goal of this project is to develop a framework, on top of the Why3 tool, for the verification of effectful higher-order programs. We use defunctionalization as an intermediate transformation from hi

Eng Leong Tan

This paper presents the generalized formulations of fundamental schemes for efficient unconditionally stable implicit finite-difference time-domain (FDTD) methods. The fundamental schemes constitute a family of implicit schemes that feature similar fundamental updating structures, which are in simplest forms with most efficient right-hand sides. The formulat

Sajjad Mohammadnejad, Qiang An, Patrizio Vena, Sean Yun

Influences of reaction zone thickening and local extinctions on the burning rate of extremely turbulent hydrogen-enriched methane-air flames are investigated using simultaneous planar laser-induced fluorescence of formaldehyde molecule and hydroxyl radical as well as separate stereoscopic particle image velocimetry techniques. Karlovitz numbers upto 76 are e

Deng Su, Dehong Chong

Visual slam technology is one of the key technologies for robot to explore unknown environment independently. Accurate estimation of camera pose based on visual sensor is the basis of autonomous navigation and positioning. However, most visual slam algorithms are based on static environment assumption and cannot estimate accurate camera pose in dynamic envir

Li Tang, Xin Li, Hai-Nan Lin, Liang Liu

Gamma-ray bursts (GRBs) detected at high redshift can be used to trace the Hubble diagram of the Universe. However, the distance calibration of GRBs is not as easily as that of type Ia supernovae (SNe Ia). For the calibrating method based on the empirical luminosity correlations, there is an underlying assumption that the correlations should be universal ove

Samuel Stevens, Yu Su

Pre-trained language models (PLMs) like BERT are being used for almost all language-related tasks, but interpreting their behavior still remains a significant challenge and many important questions remain largely unanswered. In this work, we re-purpose a sentence editing dataset, where faithful high-quality human rationales can be automatically extracted and

N. Ebrahimian, M. Khosrojerdi, R. Afzali

By considering transition-metal (Shiba-Rusinov model) and rare-earth metal impurities (Abrikosov-Gor'kov theory) effect on a many-body system, i.e., a BCS s-wave superconductor, quantum bipartite entanglement of two electrons of the Cooper pairs in terms of the exchange interaction, J, the potential scattering, V (contrary to expectations playing an importan

Jussi Karlgren, Renee Li, Eva M Meyersson Milgrom

We use commercially available text analysis technology to process interview text data from a computational social science study. We find that topical clustering and terminological enrichment provide for convenient exploration and quantification of the responses. This makes it possible to generate and test hypotheses and to compare textual and non-textual var

Taro Makino, Stanislaw Jastrzebski, Witold Oleszkiewicz, Celin Chacko

Deep neural networks (DNNs) show promise in image-based medical diagnosis, but cannot be fully trusted since their performance can be severely degraded by dataset shifts to which human perception remains invariant. If we can better understand the differences between human and machine perception, we can potentially characterize and mitigate this effect. We th

Dimitrios Chamzas, Constantinos Chamzas, Konstantinos Moustakas

During the last years, the emerging field of Augmented & Virtual Reality (AR-VR) has seen tremendousgrowth. At the same time there is a trend to develop low cost high-quality AR systems where computing poweris in demand. Feature points are extensively used in these real-time frame-rate and 3D applications, thereforeefficient high-speed feature detectors are

Jiarong Xie, Xiangrong Wang, Ling Feng, Jin-Hua Zhao

Percolation theory has been widely used to study phase transitions in complex networked systems. It has also successfully explained several macroscopic phenomena across different fields. Yet, the existent theoretical framework for percolation places the focus on the direct interactions among the system's components, while recent empirical observations have s

Priyank Agrawal, Theja Tulabandhula, Vashist Avadhanula

In this paper, we consider the contextual variant of the MNL-Bandit problem. More specifically, we consider a dynamic set optimization problem, where a decision-maker offers a subset (assortment) of products to a consumer and observes the response in every round. Consumers purchase products to maximize their utility. We assume that a set of attributes descri

Sebastiano Barbieri, Suneela Mehta, Billy Wu, Chrianna Bharat

AIMS. This study compared the performance of deep learning extensions of survival analysis models with traditional Cox proportional hazards (CPH) models for deriving cardiovascular disease (CVD) risk prediction equations in national health administrative datasets. METHODS. Using individual person linkage of multiple administrative datasets, we constructed a

Devvrit, Minhao Cheng, Cho-Jui Hsieh, Inderjit Dhillon

Developing robust models against adversarial perturbations has been an active area of research and many algorithms have been proposed to train individual robust models. Taking these pretrained robust models, we aim to study whether it is possible to create an ensemble to further improve robustness. Several previous attempts tackled this problem by ensembling

William B. McKinnon, Christopher R. Glein, Tanguy Bertrand, Alyssa R. Rhoden

The Pluto-Charon system provides a broad variety of constraints on planetary formation, composition, chemistry, and evolution. Pluto was the first body to be discovered in what is now known as the Kuiper belt, its orbit ultimately becoming a major clue that the giant planets underwent substantial orbital migration early in Solar System history. This migratio

Hisay Lama, Ranajit Mondal

Drying of colloidal dispersion and their consolidation into a particulate deposit is a common phenomenon. This process involves various physical processes such as diffusion of liquid molecules into the ambient atmosphere and advection of dispersed particles via evaporation driven flow. The colloidal particles forming a dried deposit exhibits distinct pattern

A. Chávez, K. Khalil, M. Kostić, M. Pinto

In this paper, we analyze multi-dimensional $({\mathrm R}_{X},{\mathcal B})$-almost periodic type functions and multi-dimensional Bohr ${\mathcal B}$-almost periodic type functions. The main structural characterizations and composition principles for the introduced classes of almost periodic functions are established. Several applications of our abstract the

Mohammad Ali Ahmadpoor, Marzieh Shams Yousefi

In this paper one of the possible $p$-operator space structures of the $p$-analog of the Fourier-Stieltjes algebra will be introduced, and to some extend will be studied. This special sort of operator structure will be given from the predual of this Fourier type algebra, that is the algebra of universal $p$-pseudofunctions. Furthermore, some applicable and e

Jack Lanchantin, Tianlu Wang, Vicente Ordonez, Yanjun Qi

Multi-label image classification is the task of predicting a set of labels corresponding to objects, attributes or other entities present in an image. In this work we propose the Classification Transformer (C-Tran), a general framework for multi-label image classification that leverages Transformers to exploit the complex dependencies among visual features a

Chen Chen, Christian S. Fischer, Craig D. Roberts, Jorge Segovia

A symmetry-preserving Poincar\'e-covariant quark+diquark Faddeev equation treatment of the nucleon is used to deliver parameter-free predictions for the nucleon's axial and induced pseudoscalar form factors, $G_A$ and $G_P$, respectively. The result for $G_A$ can reliably be represented by a dipole form factor characterised by an axial charge $g_A=G_A(0)=1.2

C. Dhital, J. F. DiTusa

The entropic signatures of magnetic phase transitions in the skyrmion lattice host compounds MnSi0.962Al0.038 and Fe0.7Co0.3Si were investigated through low field magnetization and ac susceptibility measurements. These data indicate that the conical to skyrmion transition that occurs with the application of magnetic field in MnSi0.962Al0.038 is characterized

Bemali Wickramanayake, Dakshi Kapugama Geeganage, Chun Ouyang, Yue Xu

Card payment fraud is a serious problem, and a roadblock for an optimally functioning digital economy, with cards (Debits and Credit) being the most popular digital payment method across the globe. Despite the occurrence of fraud could be relatively rare, the impact of fraud could be significant, especially on the cardholder. In the research, there have been

João Fernando Nariyoshi

We prove new velocity averaging lemmas for multi-dimensional hyperbolic-parabolic partial differential equations. These theorems may be applied to establish several compactness results for both deterministic and stochastic convection-diffusion equations. Among the strengths of our theory is the criticality of the source term, which may include spatial deriva

Maria E Steinrueck, Adam P. Showman, Panayotis Lavvas, Tommi Koskinen

Photochemical hazes have been suggested as candidate for the high-altitude aerosols observed in the transmission spectra of many hot Jupiters. We present 3D simulations of the hot Jupiter HD 189733b to study how photochemical hazes are transported by atmospheric circulation. The model includes spherical, constant-size hazes particles that gravitationally set

Xingqian Xu, Zhifei Zhang, Zhaowen Wang, Brian Price

Text segmentation is a prerequisite in many real-world text-related tasks, e.g., text style transfer, and scene text removal. However, facing the lack of high-quality datasets and dedicated investigations, this critical prerequisite has been left as an assumption in many works, and has been largely overlooked by current research. To bridge this gap, we propo

Stephen Pietromonaco

For an Abelian surface $A$ with a symplectic action by a finite group $G$, one can define the partition function for $G$-invariant Hilbert schemes \[Z_{A, G}(q) = \sum_{d=0}^{\infty} e(\text{Hilb}^{d}(A)^{G})q^{d}.\] We prove the reciprocal $Z_{A,G}^{-1}$ is a modular form of weight $\frac{1}{2}e(A/G)$ for the congruence subgroup $\Gamma_{0}(|G|)$, and give

Aliaksei Kachanovich

I present new results for the Standard-Model predictions of the differential decay rates for $H\to \ell^{+} \ell^{-} \gamma$, where $\ell=e, \mu$, and the forward-backward asymmetries defined in terms of the flight direction of the photon corresponding to the lepton momenta. The results dependend on the cuts on energies and invariant masses of the final stat

Peipei Lu, Andreas Rupp, Guido Kanschat

We introduce a homogeneous multigrid method in the sense that it uses the same HDG discretization scheme for Poisson's equation on all levels. In particular, we construct a stable injection operator and prove optimal convergence of the method under the assumption of elliptic regularity. Numerical experiments underline our analytical findings.

Laura Dumitrescu, Ioana Schiopu-Kratina

We study the existence, strong consistency and asymptotic normality of estimators obtained from estimating functions, that are p-dimensional martingale transforms. The problem is motivated by the analysis of evolutionary clustered data, with distributions belonging to the exponential family, and which may also vary in terms of other component series. Within

Alan Lindsay, Bart Craenen, Sara Dalzel-Job, Robin L. Hill

Human interaction relies on a wide range of signals, including non-verbal cues. In order to develop effective Explainable Planning (XAIP) agents it is important that we understand the range and utility of these communication channels. Our starting point is existing results from joint task interaction and their study in cognitive science. Our intention is tha

Udai G. Nagpal, David A Knowles

Deep learning models such as Convolutional Neural Networks (CNNs) have demonstrated high levels of effectiveness in a variety of domains, including computer vision and more recently, computational biology. However, training effective models often requires assembling and/or labeling large datasets, which may be prohibitively time-consuming or costly. Pool-bas

Chiara Marletto, Nicetu Tibau Vidal, Vlatko Vedral

We describe the quantum interference of a single photon in the Mach-Zehnder interferometer using the Heisenberg picture. Our purpose is to show that the description is local just like in the case of the classical electromagnetic field, the only difference being that the electric and the magnetic fields are, in the quantum case, operators (quantum observables

Anca Radulescu, Abraham Longbotham

We introduce mutations in replication systems in which the intact copying mechanism is performed by discrete iterations of a complex quadratic map in the family $f_c(z) = z^2+c$. More specifically, we consider a "correct" function $f_{c_1}$ acting on the complex plane (representing the RNA to be copied). A "mutation" $f_{c_0}$ is a different ("erroneous") ma