May 2022 arXiv papers — page 148

Michael Dikshtein, Shirin Saeedi Bidokhti, Shlomo Shamai

A diamond network is considered in which the central processor is connected, via backhaul noiseless links, to multiple conferencing base stations, which communicate with a single user over a multiple access channel. We propose coding techniques along with lower and upper bounds on the capacity. Our achievability scheme uses a common cloud coding strategy bas

George Balla, Ghislain Fourier, Kunda Kambaso

We characterise the symplectic Weyl group elements such that the FFLV basis is compatible with the PBW filtration on symplectic Demazure modules, extending type A results by the second author. Surprisingly, the number of such elements depends not on the type A or C of the Lie algebra but on the rank only.

Jesse A. Miller, Brian D. Fields

The widespread detection of 60Fe in geological and lunar archives provides compelling evidence for recent nearby supernova explosions within $\sim 100$ pc around 3 Myr and 7 Myr ago. The blasts from these explosions had a profound effect on the heliosphere. We perform new calculations to study the compression of the heliosphere due to a supernova blast. Assu

Kai Diethelm, Ha Duc Thai, Hoang The Tuan

This paper is devoted to studying non-commensurate fractional order planar systems. Our contributions are to derive sufficient conditions for the global attractivity of non-trivial solutions to fractional-order inhomogeneous linear planar systems and for the Mittag-Leffler stability of an equilibrium point to fractional order nonlinear planar systems. To ach

Gustavo Amorim, Ran Tao, Sarah Lotspeich, Pamela A. Shaw

Validation studies are often used to obtain more reliable information in settings with error-prone data. Validated data on a subsample of subjects can be used together with error-prone data on all subjects to improve estimation. In practice, more than one round of data validation may be required, and direct application of standard approaches for combining va

Lucia Cipolina-Kun, Simone Caenazzo, Gaston Mazzei

Digital art restoration has benefited from inpainting models to correct the degradation or missing sections of a painting. This work compares three current state-of-the art models for inpainting of large missing regions. We provide qualitative and quantitative comparison of the performance by CoModGANs, LaMa and GLIDE in inpainting of blurry and missing sect

Yihong Liu, Lei Zhang, Feifei Gao, Muhammad Ali Imran

In this paper, we model, analyze and optimize the multi-user and multi-order-reflection (MUMOR) intelligent reflecting surface (IRS) networks. We first derive a complete MUMOR IRS network model applicable for the arbitrary times of reflections, size and number of IRSs/reflectors. The optimal condition for achieving sum-rate upper bound with one IRS in a clos

Benjamin Knorr, Samuel Pirlo, Chris Ripken, Frank Saueressig

The effective action includes all quantum corrections arising in a given quantum field theory. Thus it serves as a powerful generating functional from which quantum-corrected scattering amplitudes can be constructed via tree-level computations. In this work we use this framework for studying gravity-mediated two-to-two scattering processes involving scalars

Iswar Mahato, M. Rajesh Kannan

Let $T$ be a tree on $n$ vertices whose edge weights are positive definite matrices of order $s$. The squared distance matrix of $T$, denoted by $Δ$, is the $ns \times ns$ block matrix with $Δ_{ij}=d(i,j)^2$, where $d(i,j)$ is the sum of the weights of the edges in the unique $(i,j)$-path. In this article, we obtain a formula for the determinant of $Δ$ and f

Chaoran Wang, S. Peng Oh, M. Ruszkowski

There is considerable evidence for widespread subsonic turbulence in galaxy clusters, most notably from {\it Hitomi}. Turbulence is often invoked to offset radiative losses in cluster cores, both by direct dissipation and by enabling turbulent heat diffusion. However, in a stratified medium, buoyancy forces oppose radial motions, making turbulence anisotropi

Yair Neuman, Eden Shalom Erez, Joshua Tschantret, Hayden Weiss

Revenge is a powerful motivating force reported to underlie the behavior of various solo perpetrators, from school shooters to right wing terrorists. In this paper, we develop an automated methodology for identifying vengeful themes in textual data. Testing the model on four datasets (vengeful texts from social media, school shooters, Right Wing terrorist an

Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs'ka, Wenhao Liu

Question generation (QGen) models are often evaluated with standardized NLG metrics that are based on n-gram overlap. In this paper, we measure whether these metric improvements translate to gains in a practical setting, focusing on the use case of helping teachers automate the generation of reading comprehension quizzes. In our study, teachers building a qu

Ruifeng Gu

Lane-change is a fundamental driving behavior and highly associated with various types of collisions, such as rear-end collisions, sideswipe collisions, and angle collisions and the increased risk of a traffic crash. This study investigates effectiveness of different features categories combination in lane-changing intention prediction. Studies related to la

Scott E. Smart, David A. Mazziotti

A contracted quantum eigensolver (CQE) finds a solution to the many-electron Schrödinger equation by solving its integration (or contraction) to the 2-electron space -- a contracted Schrödinger equation (CSE) -- on a quantum computer. When applied to the anti-Hermitian part of the CSE (ACSE), the CQE iterations optimize the wave function with respect to a ge

Scott E. Smart, David A. Mazziotti

Quantum computers potentially have an exponential advantage over classical computers for the quantum simulation of many-fermion quantum systems. Nonetheless, fermions are more expensive to simulate than bosons due to the fermionic encoding -- a mapping by which the qubits are encoded with fermion statistics. Here we generalize the contracted quantum eigensol

Saeed Ranjbar Alvar, Korcan Uyanik, Ivan V. Bajić

Traffic scene analysis is important for emerging technologies such as smart traffic management and autonomous vehicles. However, such analysis also poses potential privacy threats. For example, a system that can recognize license plates may construct patterns of behavior of the corresponding vehicles' owners and use that for various illegal purposes. In

Mohsen Farokhnezhad, W. A. Coish, Reza Asgari, Dimitrie Culcer

We identify a strong photovoltaic response due to the non-linear optical transition between heavy and light hole sub-bands enabled by T_d-symmetry in a quantum well, which we term the quadrupolar photovoltaic effect (QPE). The photovoltaic current exhibits a strong resonance in the vicinity of the heavy hole-light hole splitting, with a magnitude governed by

Z. H. Tin, T. Adachi, A. Takemori, K. Yoshino

We studied the band structure of NdFeAs$_{1-x}$P$_{x}$O$_{0.9}$F$_{0.1}$ ($x$ = 0, 0.2, 0.4 and 0.6) using angle-resolved photoemission spectroscopy (ARPES) measurements. Two of the hole bands, $α_1$ $(d_{xz})$ and $α_3$ $(d_{z^2})$, were observed at the Brillouin zone center in the $P$-polarized light configuration, while the other two hole bands, $α_2$ $(d

Andreas Erhart, Victoria Wagner, Ludwig Klinkenberg, Thierry Lasserre

The NUCLEUS experiment aims at measuring the coherent elastic scattering of nuclear reactor antineutrinos off nuclei using cryogenic calorimeters. Operating at an overburden of 3m.w.e., muon-induced backgrounds are expected to be dominant. It is therefore essential to develop an efficient muon veto, with a detection efficiency of more than 99%. This will be

Rachel Friederich, Matthew Graham, Anirban Ghosh, Brian Hicks

Given a set of $n$ points in the plane, the Unit Disk Cover (UDC) problem asks to compute the minimum number of unit disks required to cover the points, along with a placement of the disks. The problem is NP-hard and several approximation algorithms have been designed over the last three decades. In this paper, we have engineered and experimentally compared

J. Ng, L. -J. Chen, N. Bessho, J. Shuster

Magnetic reconnection has been observed in the transition region of quasi-parallel shocks. In this work, the particle-in-cell method is used to simulate three-dimensional reconnection in a quasi-parallel shock. The shock transition region is turbulent, leading to the formation of reconnecting current sheets with various orientations. Two reconnection sites w

Jonathan Rusert, Padmini Srinivasan

Deep learning (DL) is being used extensively for text classification. However, researchers have demonstrated the vulnerability of such classifiers to adversarial attacks. Attackers modify the text in a way which misleads the classifier while keeping the original meaning close to intact. State-of-the-art (SOTA) attack algorithms follow the general principle o

Priyadarshi Mukherjee, Constantinos Psomas, Ioannis Krikidis

Multiple-input multiple-output (MIMO) technology has significantly impacted wireless communication, by providing extraordinary performance gains. However, a minimum inter-antenna space constraint in MIMO systems does not allow its integration in devices with limited space. In this context, the concept of fluid antenna systems (FASs) appears to be a potent so

Billy K. K. Lee, William R. Coulton, Leander Thiele, Shirley Ho

With the advent of high-resolution, low-noise CMB measurements, the ability to extract cosmological information from thermal Sunyaev-Zel'dovich effect and kinetic Sunyaev-Zel'dovich effect will be limited not by statistical uncertainties but rather by systematic and theoretical uncertainties. The theoretical uncertainty is driven by the lack of knowl

Wenbin Dong, Hansong Tang

We study the computation of coupled advection-diffusion-reaction equations by the Schwarz waveform relaxation method. The study starts with linear equations, and it analyzes the convergence of the computation with a Dirichlet condition, a Robin condition, and a combination of them as the transmission conditions. Then, an optimized algorithm for the Dirichlet

Jonathan Kern, Sébastien Henwood, Gonçalo Mordido, Elsa Dupraz

Memristors enable the computation of matrix-vector multiplications (MVM) in memory and, therefore, show great potential in highly increasing the energy efficiency of deep neural network (DNN) inference accelerators. However, computations in memristors suffer from hardware non-idealities and are subject to different sources of noise that may negatively impact

Mohammad Baradaran, Robert Bergevin

Semi-supervised video anomaly detection (VAD) methods formulate the task of anomaly detection as detection of deviations from the learned normal patterns. Previous works in the field (reconstruction or prediction-based methods) suffer from two drawbacks: 1) They focus on low-level features, and they (especially holistic approaches) do not effectively conside

Basabendu Barman, Ashmita Das, Soumitra Sengupta

The recent observation by CDF collaboration has disclosed a modification in the mass of the $W$ boson. In this regard we show that this modification in the mass of the $W$ boson can be well explained in the background of a 6-dimensional warped geometry model, where the double warping is associated with the two extra spatial dimensions. We consider that all t

V. Akshay, H. Philathong, E. Campos, D. Rabinovich

Variational quantum algorithms are the centerpiece of modern quantum programming. These algorithms involve training parameterized quantum circuits using a classical co-processor, an approach adapted partly from classical machine learning. An important subclass of these algorithms, designed for combinatorial optimization on currrent quantum hardware, is the q

Floor S. Broekgaarden, Simon Stevenson, Eric Thrane

The spins of merging binary black holes offer insights into their formation history. Recently it has been argued that in isolated binary evolution of two massive stars the firstborn black hole is slowly rotating, whilst the progenitor of the second-born black hole can be tidally spun up if the binary is tight enough. Naively, one might therefore expect that

Savvas Constantinou, Nikku Madhusudhan

The upcoming James Webb Space Telescope (JWST) promises a generational shift in the study of temperate mini-Neptune atmospheres using transit spectroscopy. High-altitude clouds however threaten to impede their atmospheric characterisation by muting spectral features. In this study, we systematically investigate JWST instrument configurations for characterisi

Raymond T. Co, Yann Mambrini, Keith A. Olive

We consider the generation of the baryon asymmetry in models with right-handed neutrinos produced through gravitational scattering of the inflaton during reheating. The right-handed neutrinos later decay and generate a lepton asymmetry, which is partially converted to a baryon asymmetry by Standard Model sphaleron processes. We find that a sufficient asymmet

Sajal Saha, Anwar Haque, Greg Sidebottom

Internet traffic in the real world is susceptible to various external and internal factors which may abruptly change the normal traffic flow. Those unexpected changes are considered outliers in traffic. However, deep sequence models have been used to predict complex IP traffic, but their comparative performance for anomalous traffic has not been studied exte

Adarsh Bhandary Panambur, Prathmesh Madhu, Andreas Maier

Early detection and analysis of calcifications in mammogram images is crucial in a breast cancer diagnosis workflow. Management of calcifications that require immediate follow-up and further analyzing its benignancy or malignancy can result in a better prognosis. Recent studies have shown that deep learning-based algorithms can learn robust representations t

Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman

This technical report presents SpineNetV2, an automated tool which: (i) detects and labels vertebral bodies in clinical spinal magnetic resonance (MR) scans across a range of commonly used sequences; and (ii) performs radiological grading of lumbar intervertebral discs in T2-weighted scans for a range of common degenerative changes. SpineNetV2 improves over

Yi Qiu, Ke Wang, Jian-hua He

We investigate the detectability of gravitational waves (GWs) lensed by a system that consists of binary black holes as lenses using time-domain numerical simulations. The gravitational lensing potential of this system is no longer static but evolves with time. When GWs from the source pass through the binary lens, their amplitudes can be modulated, which is

Andrew Brown, Cheng-Yang Fu, Omkar Parkhi, Tamara L. Berg

We consider the targeted image editing problem: blending a region in a source image with a driver image that specifies the desired change. Differently from prior works, we solve this problem by learning a conditional probability distribution of the edits, end-to-end. Training such a model requires addressing a fundamental technical challenge: the lack of exa

Francisco M. Blanco, Éanna É. Flanagan

We consider the motion of a point particle in a stationary spacetime under the influence of a scalar, electromagnetic or gravitational self-force. We show that the conservative piece of the first-order self-force gives rise to Hamiltonian dynamics, and we derive an explicit expression for the Hamiltonian on phase space. Specialized to the Kerr spacetime, our

Abraham Levitan, Riccardo Comin

Lensless imaging methods that account for partial coherence have become very common in the past decade. However, there are no metrics in use for comparing partially coherent light fields, despite the widespread use of such metrics to compare fully coherent objects and wavefields. Here, we show how reformulating the mean squared error and Fourier ring correla

Dalini D. Maharaj, Mina Abbaslou, Sana Tabbassum, Alexander Gottberg

Canada recently lost its major supply of neutron beams with the closure of the National Research Universal reactor at Chalk River Laboratories in March 2018. This issue is further exacerbated by the closure of other reactors abroad, which also served as centers for neutron research. Consequently, there is a demand for new sources, both for Canada and interna

Robert D. Kavanagh, Aline A. Vidotto, Harish K. Vedantham, Moira M. Jardine

The nearby M dwarf WX UMa has recently been detected at radio wavelengths with LOFAR. The combination of its observed brightness temperature and circular polarisation fraction suggests that the emission is generated via the electron-cyclotron maser instability. Two distinct mechanisms have been proposed to power such emission from low-mass stars: either a su

Benjamin Briggs, Lleonard Rubio y Degrassi

Building on work of Gerstenhaber, we show that the space of integrable derivations on an Artin algebra $A$ forms a Lie algebra, and a restricted Lie algebra if $A$ contains a field of characteristic $p$. We deduce that the space of integrable classes in $\HH^1(A)$ forms a (restricted) Lie algebra that is invariant under derived equivalences, and under stable

A. Migliorini, Z. Kanuchova, S. Ioppolo, M. Barbieri

Since its first identification on the surface of Ganymede in 1995, molecular oxygen (O2) ice has been at the center of a scientific debate as the surface temperature of the Jovian moon is on average well above the freezing point of O2. Laboratory evidence suggested that solid O2 may either exist in a cold (<50 K) subsurface layer of the icy surface of Ganyme

Chung-Ching Lin, Kevin Lin, Linjie Li, Lijuan Wang

We present a cross-modal Transformer-based framework, which jointly encodes video data and text labels for zero-shot action recognition (ZSAR). Our model employs a conceptually new pipeline by which visual representations are learned in conjunction with visual-semantic associations in an end-to-end manner. The model design provides a natural mechanism for vi

Pan Ji, Qingan Yan, Yuxin Ma, Yi Xu

We present a robust and accurate depth refinement system, named GeoRefine, for geometrically-consistent dense mapping from monocular sequences. GeoRefine consists of three modules: a hybrid SLAM module using learning-based priors, an online depth refinement module leveraging self-supervision, and a global mapping module via TSDF fusion. The proposed system i

Zvi Bern, Enrico Herrmann, Dimitrios Kosmopoulos, Radu Roiban

Theoretical data obtained from physically sensible field and string theory models suggest that gravitational Effective Field Theories (EFTs) live on islands that are tiny compared to current general bounds determined from unitarity, causality, crossing symmetry, and a good high-energy behavior. In this work, we present explicit perturbative and nonperturbati

Yao Zhou, Peng Ye

The existence of $1/2$ modes in the entanglement spectrum (ES) has been shown to be a powerful quantum-informative signature of boundary states of gapped topological phases of matter, e.g., topological insulators and topological superconductors, where the finite bulk gap allows us to establish a crystal-clear correspondence between $1/2$ modes and boundary s

Rhea Palak Bakshi

This note provides a counterexample to a conjecture by Marché about the structure of the Kauffman bracket skein module for closed compact oriented 3-manifolds over the ring of Laurent polynomials.

Samyak Datta, Sameer Dharur, Vincent Cartillier, Ruta Desai

Egocentric augmented reality devices such as wearable glasses passively capture visual data as a human wearer tours a home environment. We envision a scenario wherein the human communicates with an AI agent powering such a device by asking questions (e.g., where did you last see my keys?). In order to succeed at this task, the egocentric AI assistant must (1

Marie Fortin, Boris Konev, Vladislav Ryzhikov, Yury Savateev

We aim to determine which temporal instance queries can be uniquely characterised by a (polynomial-size) set of positive and negative temporal data examples. We start by considering queries formulated in fragments of propositional linear temporal logic LTL that correspond to conjunctive queries (CQs) or extensions thereof induced by the until operator. Not a

Kinshuk Dua

Recently, there has been a remarkable amount of research being done in both, the fields of Blockchain and Internet of Things (IoT). Blockchain technology synergises well with IoT, solving key problems such as privacy, concerns with interoperability and security. However, the consensus mechanisms that allows trustless parties to maintain an agreement, the sam

Jung-Wan Ryu, Martina Hentschel

While classic quantum chaos originated from the idea to set into context nonlinear physics and Hermitian quantum mechanics, non-Hermitian models have enhanced the field in recent years. At the same time, low-dimensional effective matrix models have proven to be a powerful tool in accessing the physical properties of a system in a semiquantitative manner. Her

Trung-Kien Le, Ping Li

Correspondences estimation or feature matching is a key step in the image-based 3D reconstruction problem. In this paper, we propose two algebraic properties for correspondences. The first is a rank deficient matrix construct from the correspondences of at least nine key-points on two images (two-view correspondences) and the second is also another rank defi

Benjamin Apffel, Christian Wilkinson, Emmanuel Fort

Vibrations can dynamically stabilize otherwise unstable liquid interfaces and produce new dynamic equilibria, called vibro-equilibria. Typically, the vibrations are homogeneous in the liquid and the liquid interface remains approximately flat. Here, we produce controlled vertical vibration gradients by taking advantage of the resonant oscillations of sinking

Marc Duquesnoy, Chaoyue Liu, Diana Zapata Dominguez, Vishank Kumar

The optimization of the electrodes manufacturing process constitutes one of the most critical steps to ensure high-quality Lithium-Ion Battery (LIB) cells, in particular for automotive applications. Because LIB electrode manufacturing is a complex process involving multiple steps and interdependent parameters, we have shown in our previous works that 3D-reso

Di Yang

Dubrovin establishes the relationship between the GUE partition function and the partition function of Gromov--Witten invariants of the complex projective line. In this paper, we give a direct proof of Dubrovin&#39;s result. We also present in a diagram the recent progress on topological gravity and matrix gravity.

Daniel Tang, Nick Malleson

Every day, weather forecasting centres around the world make use of noisy, incomplete observations of the atmosphere to update their weather forecasts. This process is known as data assimilation, data fusion or state estimation and is best expressed as Bayesian inference: given a set of observations, some prior beliefs and a model of the target system, what

Yuxi Han

We focus on the global semiconcavity of solutions to first-order Hamilton--Jacobi equations with state constraints, especially for the Hamiltonian $H(x, β):=|β|^p-f(x)$ with $p \in (1, 2]$. We first show that the solution is locally semiconcave, and the semiconcavity constant at each point depends on the first time a corresponding minimizing curve emanating

Axel Masó-Puigdellosas, Daniel Campos, Vicenç Méndez

Stochastic resetting can be naturally understood as a renewal process governing the evolution of an underlying stochastic process. In this work, we formally derive well-known results of diffusion with resets from a renewal theory perspective. Parallel to the concepts from renewal theory, we introduce the conditioned backward and forward times for stochastic

Wenjing Chen, Chao Tian

The study of the fundamental limits of information systems is a central theme in information theory. Both the traditional analytical approach and the recently proposed computational approach have significant limitations, where the former is mainly due to its reliance on human ingenuity, and the latter due to its exponential memory and computational complexit

Chengyuan Qian, Ruida Zhou, Chao Tian, Tie Liu

We study the problem of weakly private information retrieval (W-PIR), where a user wishes to retrieve a desired message from $N$ non-colluding servers in a way that the privacy leakage regarding the desired message&#39;s identity is less than or equal to a threshold. We propose a new code construction which significantly improves upon the best known result i

Andrés Anabalón, Patrick Concha, Julio Oliva, Constanza Quijada

In this work we study the phase transitions between the planar charged AdS black hole and the planar charged soliton. The planar soliton is obtained as a double analytic continuation of the charged black hole metric, which also involves analytically continuing the electric charge. We show that there are phase transitions between both solutions depending on t

Junyi Li, Feihu Huang, Heng Huang

Bilevel Optimization has witnessed notable progress recently with new emerging efficient algorithms and has been applied to many machine learning tasks such as data cleaning, few-shot learning, and neural architecture search. However, little attention has been paid to solve the bilevel problems under distributed setting. Federated learning (FL) is an emergin

Bhupendra Sharma, Anirudh Agarwal, Deepak Mishra, Soumitra Debnath

Graphene-based intelligent reflecting surface (GIRS) has been proved to provide a promising propagation environment to enhance the quality of high frequency terahertz (THz) wireless communication. In this paper, we characterize GIRS for THz communication (GITz) using material specific parameters of graphene to tune the reflection of the incident wave at IRS.

Vivek Kulkarni, Kenny Leung, Aria Haghighi

Automatically associating social media posts with topics is an important prerequisite for effective search and recommendation on many social media platforms. However, topic classification of such posts is quite challenging because of (a) a large topic space (b) short text with weak topical cues, and (c) multiple topic associations per post. In contrast to mo

Felipe Giraldo Mejia, Aishwarya Kumar, Tsung-Yao Wu, Peng Du

We propose a way to measure the qubit state of an arbitrary sub-ensemble of atoms in an array without significantly disturbing the quantum information in the unmeasured atoms. The idea is to first site-selectively transfer atoms out of the qubit basis so that one of the two states at a time is put into an auxiliary state. Electromagnetically induced transpar

V. A. S. V. Bittencourt, M. Blasone, S. De Siena, C. Matrella

We analyze quantum correlations and quantum coherence in neutrino oscillations. To this end, we exploit complete complementarity relations (CCR) that fully characterize the interplay between different correlations encoded in a quantum system both for pure and mixed states. We consider the CCR for neutrino oscillations both in the case of plane-waves (pure st

Sandra Wankmüller

One of the first steps in many text-based social science studies is to retrieve documents that are relevant for the analysis from large corpora of otherwise irrelevant documents. The conventional approach in social science to address this retrieval task is to apply a set of keywords and to consider those documents to be relevant that contain at least one of

M. Fabian, A. Ioffe, J. P. Revalski

We propose a general scheme for studying separably reducible properties in metric spaces and then apply it to obtain separable determinacy of Lipschitz property and the separable determinacy of slopes

Christie L. Alappat, Georg Hager, Olaf Schenk, Gerhard Wellein

The multiplication of a sparse matrix with a dense vector (SpMV) is a key component in many numerical schemes and its performance is known to be severely limited by main memory access. Several numerical schemes require the multiplication of a sparse matrix polynomial with a dense vector, which is typically implemented as a sequence of SpMVs. This results in

K. G. Arun, Enis Belgacem, Robert Benkel, Laura Bernard

The Laser Interferometer Space Antenna (LISA) has the potential to reveal wonders about the fundamental theory of nature at play in the extreme gravity regime, where the gravitational interaction is both strong and dynamical. In this white paper, the Fundamental Physics Working Group of the LISA Consortium summarizes the current topics in fundamental physics

Hunter Dinkins

One of the fundamental objects in the $K$-theoretic enumerative geometry of Nakajima quiver varieties is known as the the capping operator. It is uniquely determined as the fundamental solution to a system of $q$-difference equations. Such difference equations involve shifts of two sets of variables, the variables arising as equivariant parameters for a toru

Zhicheng Cao, Jiaxuan Zhang, Liaojun Pang

Face recognition in the infrared (IR) band has become an important supplement to visible light face recognition due to its advantages of independent background light, strong penetration, ability of imaging under harsh environments such as nighttime, rain and fog. However, cross-spectral face recognition (i.e., VIS to IR) is very challenging due to the dramat

Sajal Saha, Anwar Haque, Greg Sidebottom

Real-world IP network traffic is susceptible to external and internal factors such as new internet service integration, traffic migration, internet application, etc. Due to these factors, the actual internet traffic is non-linear and challenging to analyze using a statistical model for future prediction. In this paper, we investigated and evaluated the perfo

H. Liu, W. Maimaitiyiming

A dynamic mass-transport method is proposed for approximately solving the Poisson-Nernst-Planck(PNP) equations. The semi-discrete scheme based on the JKO type variational formulation naturally enforces solution positivity and the energy law as for the continuous PNP system. The fully discrete scheme is further formulated as a constrained minimization problem

Zijian Zhang, Vinay Setty, Avishek Anand

We introduce SparcAssist, a general-purpose risk assessment tool for the machine learning models trained for language tasks. It evaluates models&#39; risk by inspecting their behavior on counterfactuals, namely out-of-distribution instances generated based on the given data instance. The counterfactuals are generated by replacing tokens in rational subsequen

Zixiang Xu, Abraham G. Campbell, Soumyabrata Dev, Yuan Liang

Virtual Reality (VR) technology has been shown to achieve remarkable results in multiple fields. Due to the nature of the immersive medium of Virtual Reality it logically follows that it can be used as a high-quality educational tool as it offers potentially a higher bandwidth than other mediums such as text, pictures and videos. This short paper illustrates

Lucas Beyer, Xiaohua Zhai, Alexander Kolesnikov

It is commonly accepted that the Vision Transformer model requires sophisticated regularization techniques to excel at ImageNet-1k scale data. Surprisingly, we find this is not the case and standard data augmentation is sufficient. This note presents a few minor modifications to the original Vision Transformer (ViT) vanilla training setting that dramatically

Tony J. G. Apollaro, Salvatore Lorenzo, Francesco Plastina, Mirko Consiglio

The transfer of quantum information between different locations is key to many quantum information processing tasks. Whereas, the transfer of a single qubit state has been extensively investigated, the transfer of a many-body system configuration has insofar remained elusive. We address the problem of transferring the state of n interacting qubits. Both the

John W. Niman, Benjamin S. Kamerin, Vitaly V. Kresin, Jan Krohn

Abundance spectra of (CO$_2$)$_N$ clusters (up to $N \approx$ 500) acquired under a wide range of adiabatic expansion conditions are analyzed within the evaporative ensemble framework. Analysis reveals that cluster stability functions display strikingly universal patterns for all expansion conditions. These patterns reflect the inherent properties of individ

Sara Giuliani, Giuseppe Romana, Massimiliano Rossi

In recent years, pangenomes received increasing attention from the scientific community for their ability to incorporate population variation information and alleviate reference genome bias. Maximal Exact Matches (MEMs) and Maximal Unique Matches (MUMs) have proven themselves to be useful in multiple bioinformatic contexts, for example short-read alignment a

Jacob W. Isbell, Klaus Meisenheimer, Jörg-Uwe Pott, Marko Stalevski

Active galactic nuclei play a key role in the evolution of galaxies, but their inner workings and physical connection to the host are poorly understood due to a lack of angular resolution. Infrared interferometry makes it possible to resolve the circumnuclear dust in the nearby Seyfert 2 galaxy, Circinus. Previous observations have revealed complex structure

Bayram Bayramli, Junhwa Hur, Hongtao Lu

Learning scene flow from a monocular camera still remains a challenging task due to its ill-posedness as well as lack of annotated data. Self-supervised methods demonstrate learning scene flow estimation from unlabeled data, yet their accuracy lags behind (semi-)supervised methods. In this paper, we introduce a self-supervised monocular scene flow method tha

Peter Chudinov

A classic problem of the motion of a projectile thrown at an angle to the horizon in a medium with a quadratic resistance law is studied. An approximate analytical solution of the equations of projectile motion is presented, which has a high accuracy. The proposed formulas are universal, that is, they can be used for any initial conditions of throwing over a

Sally Dong, Yu Gao, Gramoz Goranci, Yin Tat Lee

We present a nearly-linear time algorithm for finding a minimum-cost flow in planar graphs with polynomially bounded integer costs and capacities. The previous fastest algorithm for this problem is based on interior point methods (IPMs) and works for general sparse graphs in $O(n^{1.5}\text{poly}(\log n))$ time [Daitch-Spielman, STOC&#39;08]. Intuitively, $Ω

Ahad Hamednia, Nikolce Murgovski, Jonas Fredriksson, Jimmy Forsman

This paper addresses optimal battery thermal management (BTM), charging, and eco-driving of a battery electric vehicle (BEV) with the goal of improving its grid-to-meter energy efficiency. Thus, an optimisation problem is formulated, aiming at finding the optimal trade-off between trip time and charging cost. The formulated problem is then transformed into a

Marco Palla, Pablo Santos-Peral, Alejandra Recio-Blanco, Francesca Matteucci

Context. The [Mg/Fe] abundance ratios are a fundamental fossil signature to trace the chemical evolution of the disc. Despite of the huge observational and theoretical effort, discrepancies between models and data are still present and several explanations have been put forward to explain the [$α$/Fe] bimodality. Aims. In this work, we take advantage of a ne

Peyman Passban, Tanya Roosta, Rahul Gupta, Ankit Chadha

Training mixed-domain translation models is a complex task that demands tailored architectures and costly data preparation techniques. In this work, we leverage federated learning (FL) in order to tackle the problem. Our investigation demonstrates that with slight modifications in the training process, neural machine translation (NMT) engines can be easily a

Burak Hasircioglu, Deniz Gunduz

Running a randomized algorithm on a subsampled dataset instead of the entire dataset amplifies differential privacy guarantees. In this work, in a federated setting, we consider random participation of the clients in addition to subsampling their local datasets. Since such random participation of the clients creates correlation among the samples of the same

Skye Kychenthal

Through online anecdotal evidence and online communities, there is an in-group idea of trans people (specifically trans-feminine individuals) disproportionately entering computer science education & fields. Existing data suggests this is a plausible trend, yet no research has been done into exactly why. As computer science education (traditional schooling or

Arsenia Chorti

Sixth generations (6G) systems will be required to meet diverse constraints in an integrated ground-air-space global network. In particular, meeting overly aggressive latency constraints, operating in massive connectivity regimes, with low energy footprint and low computational effort, while providing explicit security guarantees, can be challenging. In this

Qi Zhang, Wei Lin, Antoni B. Chan

Multi-view crowd counting has been previously proposed to utilize multi-cameras to extend the field-of-view of a single camera, capturing more people in the scene, and improve counting performance for occluded people or those in low resolution. However, the current multi-view paradigm trains and tests on the same single scene and camera-views, which limits i

Nafise Sadat Moosavi, Quentin Delfosse, Kristian Kersting, Iryna Gurevych

State-of-the-art pretrained NLP models contain a hundred million to trillion parameters. Adapters provide a parameter-efficient alternative for the full finetuning in which we can only finetune lightweight neural network layers on top of pretrained weights. Adapter layers are initialized randomly. However, existing work uses the same adapter architecture --

Giuseppe Bevilacqua, Ennio Arimondo

We investigated the Autler-Townes splitting produced by microwave transitions between atomic Rydberg states explored by optical spectroscopy from the ground electronic state. The laser-atom Hamiltonian describing the double irradiation of such a multilevel system is analysed on the basis of the Morris-Shore transformation. The application of this transformat

Yukun Feng, Feng Li, Ziang Song, Boyuan Zheng

The Transformer architecture has led to significant gains in machine translation. However, most studies focus on only sentence-level translation without considering the context dependency within documents, leading to the inadequacy of document-level coherence. Some recent research tried to mitigate this issue by introducing an additional context encoder or t

Danilo Vucetic, Mohammadreza Tayaranian, Maryam Ziaeefard, James J. Clark

Resource-constrained devices are increasingly the deployment targets of machine learning applications. Static models, however, do not always suffice for dynamic environments. On-device training of models allows for quick adaptability to new scenarios. With the increasing size of deep neural networks, as noted with the likes of BERT and other natural language

Bradley J. Nelson

A challenge in computational topology is to deal with large filtered geometric complexes built from point cloud data such as Vietoris-Rips filtrations. This has led to the development of schemes for parallel computation and compression which restrict simplices to lie in open sets in a cover of the data. We extend the method of acyclic carriers to the setting

Jingfeng Yang, Le Zhang, Diyi Yang

Although sequence-to-sequence models often achieve good performance in semantic parsing for i.i.d. data, their performance is still inferior in compositional generalization. Several data augmentation methods have been proposed to alleviate this problem. However, prior work only leveraged superficial grammar or rules for data augmentation, which resulted in l

Woo Hyun Kang, Jahangir Alam, Abderrahim Fathan

The main objective of the spoofing countermeasure system is to detect the artifacts within the input speech caused by the speech synthesis or voice conversion process. In order to achieve this, we propose to adopt an attentive activation function, more specifically attention rectified linear unit (AReLU) to the end-to-end spoofing countermeasure system. Sinc

Jagdeep Singh, Jahrul Alam

In large wind farms, wake distribution behind a wind turbine causes a considerable reduction of wind velocity for downstream wind turbines, resulting in a significant amount of power loss. Therefore, it is very crucial to predict wind turbine wakes efficiently. Thus, we propose a large-eddy simulation (LES) methodology, which takes the vorticity stretching t