March 2020 arXiv papers — page 135

Rafatul Faria, Jan Kaiser, Kerem Y. Camsari, Supriyo Datta

Directed acyclic graphs or Bayesian networks that are popular in many AI related sectors for probabilistic inference and causal reasoning can be mapped to probabilistic circuits built out of probabilistic bits (p-bits), analogous to binary stochastic neurons of stochastic artificial neural networks. In order to satisfy standard statistical results, individua

Giorgio Severi, Jim Meyer, Scott Coull, Alina Oprea

Training pipelines for machine learning (ML) based malware classification often rely on crowdsourced threat feeds, exposing a natural attack injection point. In this paper, we study the susceptibility of feature-based ML malware classifiers to backdoor poisoning attacks, specifically focusing on challenging "clean label" attacks where attackers do no

Gilles Lancien, Matias Raja

The notion of super weak compactness for subsets of Banach spaces is a strengthening of the weak compactness that can be described as a local version of super-reflexivity. A recent result of K. Tu which establishes that the closed convex hull of a super weakly compact set is super weakly compact has removed the main obstacle to further development of the the

Qiugang Lu, Sungho Shin, Victor M. Zavala

Dynamic mode decomposition (DMD) is a versatile approach that enables the construction of low-order models from data. Controller design tasks based on such models require estimates and guarantees on predictive accuracy. In this work, we provide a theoretical analysis of DMD model errors that reveals impact of model order and data availability. The analysis a

Aurélien Velleret

The purpose of this paper is to ensure the conditions of Gärtner-Ellis Theorem for evaluations of the empirical measure. We show that up-to-date conditions for ensuring the convergence to a quasi-stationary distribution can be applied efficiently. By this mean, we are able to prove Large Deviation results even with a conditioning that the process is not exti

Haoran Su, Kejian Shi, Joseph. Y. J. Chow, Li Jin

Emergency vehicle (EMV) service is a key function of cities and is exceedingly challenging due to urban traffic congestion. The main reason behind EMV service delay is the lack of communication and cooperation between vehicles blocking EMVs. In this paper, we study the improvement of EMV service under V2X connectivity. We consider the establishment of dynami

Govind Menon

In this paper we formulate the relationship between force-free electrodynamics and foliations. The background metric, is considered predetermined and electrically neutral, but otherwise arbitrary. As it turns out, solutions to force-free electrodynamics is intimately connected to the existence of foliations of a spacetime with prescribed properties. We also

Stepan Sidorov

We construct SU$(2|1)$, $d=1$ supersymmetric models based on the coupling of dynamical and semi-dynamical (spin) multiplets, where the interaction term of both multiplets is defined on the generalized chiral superspace. The dynamical multiplet is defined as a chiral multiplet ${\bf (2,4,2)}$, while the semi-dynamical multiplet is associated with a multiplet

Hongsheng Liu, Enrico Bianchetti, Paulo Siani, Cristiana Di Valentin

In this work we investigate the Fe$_3$O$_4$(001) surface/water interface by combining several theoretical approaches, ranging from a hybrid functional method (HSE06) to density-functional tight-binding (DFTB) to molecular mechanics (MM). First, we assess the accuracy of the DFTB method to reproduce correctly HSE06 results on structural details and energetics

James Xiao, Yun Liu, Violette Steinmetz, Mustafa Çağlar

Luminescent colloidal CdSe nanorings are a new type of semiconductor structure that have attracted interest due to the potential for unique physics arising from their non-trivial toroidal shape. However, the exciton properties and dynamics of these materials with complex topology are not yet well understood. Here, we use a combination of femtosecond vibratio

Grigori Avramidi, Boris Okun, Kevin Schreve

We compute the mod $p$ homology growth of residual sequences of finite index normal subgroups of right-angled Artin groups. We find examples where this differs from the rational homology growth, which implies the homology of subgroups in the sequence has lots of torsion. More precisely, the homology torsion grows exponentially in the index of the subgroup. F

Paul Kairys, Andrew D. King, Isil Ozfidan, Kelly Boothby

Frustration represents an essential feature in the behavior of magnetic materials when constraints on the microscopic Hamiltonian cannot be satisfied simultaneously. This gives rise to exotic phases of matter including spin liquids, spin ices, and stripe phases. Here we demonstrate an approach to understanding the microscopic effects of frustration by comput

Axel Kröner, Heiko Kröner

This paper proves error estimates for $H^2$ conforming finite elements for equations which model the flow of surfaces by different powers of the mean curvature (this includes mean curvature flow). for an adapted scheme originally proposed in [17] for the inverse mean curvature flow. The scheme is based on a known regularization procedure and produces differe

Holger Drees, Sebastian Neblung

Drees and Rootzén (2010) have established limit theorems for a general class of empirical processes of statistics that are useful for the extreme value analysis of time series, but do not apply to statistics of sliding blocks, including so-called runs estimators. We generalize these results to empirical processes which cover both the class considered by Dree

Nicoletta Cantarini, Fabrizio Caselli, Victor Kac

We construct a duality functor on the category of continuous representations of linearly compact Lie superalgebras, using representation theory of Lie conformal superalgebras. We compute the dual representations of the generalized Verma modules.

Mathias Butenschoen, Bernd A. Kniehl

We compare two approaches to evaluate cross sections of heavy-quarkonium production at next-to-leading order in nonrelativistic QCD involving $S$- and $P$-wave Fock states: the customary approach based on phase space slicing and the approach based on dipole subtraction recently elaborated by us. We find reasonable agreement between the numerical results of t

A. R. Kuzmak, V. M. Tkachuk

We implement a protocol to determine the degree of entanglement between a qubit and the rest of the system on a quantum computer. The protocol is based on results obtained in paper [Frydryszak et al. (2017)]. This protocol is tested on a 5-qubit superconducting quantum processor called ibmq-ourense provided by the IBM company. We determine the values of enta

Daniel Koch, Brett Martin, Saahil Patel, Laura Wessing

As superconducting qubits continue to advance technologically, the realization of quantum algorithms from theoretical abstraction to physical implementation requires knowledge of both quantum circuit construction as well as hardware limitations. In this study we present results from experiments run on IBM's 20-qubit `Poughkeepsie' architecture, with

Takol Tangphati, Auttakit Chatrabhuti, Daris Samart, Phongpichit Channuie

In this work, the study of traversable wormholes in $f(R)$-massive gravity with the function $f(R)=R+α_{1} R^{n}$, where $α_{1}$ and $n$ are arbitrary constants, is considered. We choose the modified shape function $b(r)$. We consider a spherically symmetric and static wormhole metric and derive field equations. Moreover, we visualize the wormhole geometry u

David Leturcq

The Bott-Cattaneo-Rossi invariant $(Z_k)_{k\in \mathbb N\setminus\{0,1\}}$ is an invariant of long knots $\mathbb R^n\hookrightarrow\mathbb R^{n+2}$ for odd $n$, which reads as a combination of integrals over configuration spaces. In this article, we compute such integrals and prove explicit formulas for (generalized) $Z_k$ in terms of Alexander polynomials,

Jennifer D'Souza, Anett Hoppe, Arthur Brack, Mohamad Yaser Jaradeh

We introduce the STEM (Science, Technology, Engineering, and Medicine) Dataset for Scientific Entity Extraction, Classification, and Resolution, version 1.0 (STEM-ECR v1.0). The STEM-ECR v1.0 dataset has been developed to provide a benchmark for the evaluation of scientific entity extraction, classification, and resolution tasks in a domain-independent fashi

Md Ferdous Pervej, Shih-Chun Lin

This paper introduces an energy-efficient, software-defined vehicular edge network for the growing intelligent connected transportation system. A joint user-centric virtual cell formation and resource allocation problem is investigated to bring eco-solutions at the edge. This joint problem aims to combat against the power-hungry edge nodes while maintaining

Javier Garcia-Barcos, Ruben Martinez-Cantin

Complex robot navigation and control problems can be framed as policy search problems. However, interactive learning in uncertain environments can be expensive, requiring the use of data-efficient methods. Bayesian optimization is an efficient nonlinear optimization method where queries are carefully selected to gather information about the optimum location.

María Esteban, Ramon Jansana

We first present a Priestley-style dualitiy for the classes of algebras that are the algebraic counterpart of some congruential, finitary and filter-distributive logic with theorems. Then we analyze which properties of the dual spaces correspond to properties that the logic might enjoy, like the deduction theorem or the existence of a disjunction.

Jinxi Xiang, Yonggui Dong, Yunjie Yang

Imaging the bio-impedance distribution of the brain can provide initial diagnosis of acute stroke. This paper presents a compact and non-radiative tomographic modality, i.e. multi-frequency Electromagnetic Tomography (mfEMT), for the initial diagnosis of acute stroke. The mfEMT system consists of 12 channels of gradiometer coils with adjustable sensitivity a

Donatella Danielli, Rohit Jain

In this paper we are concerned with a two-penalty boundary obstacle problem of interest in thermics, fluid dynamics and electricity. Specifically, we prove existence, uniqueness and optimal regularity of the solutions, and we establish structural properties of the free boundary.

Nina Andrejevic, Jovana Andrejevic, B. Andrei Bernevig, Nicolas Regnault

Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands of candidate topological materials, experimental determination of materials' topology often poses significant technical challenges. X-ray absorption spectroscopy (XAS) is a wide

K. Zarembo

The circular Wilson loop in the two-node quiver CFT is computed at large-N and strong 't Hooft coupling by solving the localization matrix model.

Edric Tam, David Dunson

We introduce a novel regularization approach for deep learning that incorporates and respects the underlying graphical structure of the neural network. Existing regularization methods often focus on dropping/penalizing weights in a global manner that ignores the connectivity structure of the neural network. We propose to use the Fiedler value of the neural n

Enrico Ubaldi, Raffaella Burioni, Vittorio Loreto, Fancesca Tria

The interactions among human beings represent the backbone of our societies. How people interact, establish new connections, and allocate their activities among these links can reveal a lot of our social organization. Despite focused attention by very diverse scientific communities, we still lack a first-principles modeling framework able to account for the

Matthew Ondrus, Emilie Wiesner

The Lie algebra $sl_2 ( \mathbb{C} )$ may be regarded in a natural way as a subalgebra of the infinite-dimensional Virasoro Lie algebra, and this suggests there may be connections between the representation theory of the two algebras. In this paper, we explore the restriction to $sl_2 ( \mathbb{C} )$ of certain induced modules for the Virasoro algebra. Speci

Pascal Pernot, Andreas Savin

The comparison of benchmark error sets is an essential tool for the evaluation of theories in computational chemistry. The standard ranking of methods by their Mean Unsigned Error is unsatisfactory for several reasons linked to the non-normality of the error distributions and the presence of underlying trends. Complementary statistics have recently been prop

Sarod Yatawatta

With ever increasing data rates produced by modern radio telescopes like LOFAR and future telescopes like the SKA, many data processing steps are overwhelmed by the amount of data that needs to be handled using limited compute resources. Calibration is one such operation that dominates the overall data processing computational cost, nonetheless, it is an ess

Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent

In the last few years, graph neural networks (GNNs) have become the standard toolkit for analyzing and learning from data on graphs. This emerging field has witnessed an extensive growth of promising techniques that have been applied with success to computer science, mathematics, biology, physics and chemistry. But for any successful field to become mainstre

X. Miao, D. J. Gosztola, X. Ma, D. Czaplewski

Quenching of fluorescence (FL) at the vicinity of conductive surfaces, and in particular, near a 2-D graphene layer has become an important biochemical sensing tool. The quenching is attributed to fast non-radiative energy transfer between a chromophore and the lossy conductor. Increased emission rate is also observed when the chromophore is coupled to a res

Isaac Sunseri, Joseph Hart, Bart van Bloemen Waanders, Alen Alexanderian

High fidelity models used in many science and engineering applications couple multiple physical states and parameters. Inverse problems arise when a model parameter cannot be determined directly, but rather is estimated using (typically sparse and noisy) measurements of the states. The data is usually not sufficient to simultaneously inform all of the parame

Kristopher Ambrose, Steve Huntsman, Michael Robinson, Matvey Yutin

We introduce topological differential testing (TDT), an approach to extracting the consensus behavior of a set of programs on a corpus of inputs. TDT uses the topological notion of a simplicial complex (and implicitly draws on richer topological notions such as sheaves and persistence) to determine inputs that cause inconsistent behavior and in turn reveal \

Caillou Philippe, Renault Jonas, Fekete Jean-Daniel, Letournel Anne-Catherine

We describe CARTOLABE, a web-based multi-scale system for visualizing and exploring large textual corpora based on topics, introducing a novel mechanism for the progressive visualization of filtering queries. Initially designed to represent and navigate through scientific publications in different disciplines, CARTOLABE has evolved to become a generic framew

Ashish Dandekar, Debabrota Basu, Stephane Bressan

The calibration of noise for a privacy-preserving mechanism depends on the sensitivity of the query and the prescribed privacy level. A data steward must make the non-trivial choice of a privacy level that balances the requirements of users and the monetary constraints of the business entity. We analyse roles of the sources of randomness, namely the explicit

Tobias Fischer, Meng-Ru Wu, Benjamin Wehmeyer, Niels-Uwe F. Bastian

Supernova explosions of massive stars are one of the primary sites for the production of the elements in the universe. Up to now, stars with zero-age main-sequence masses in the range of 35--50~$M_\odot$ had mostly been representing the failed supernova explosion branch. In contrast, it has been demonstrated recently that the appearance of exotic phases of h

Cody Buntain, Richard Bonneau, Jonathan Nagler, Joshua A. Tucker

In January 2019, YouTube announced it would exclude potentially harmful content from video recommendations but allow such videos to remain on the platform. While this step intends to reduce YouTube's role in propagating such content, continued availability of these videos in other online spaces makes it unclear whether this compromise actually reduces th

Sajad Abbar

Neutrinos propagating in dense neutrino media such as those in core-collapse supernovae can experience fast flavor conversions on scales much shorter than those expected in vacuum. It is believed that a necessary condition for the occurrence of fast modes is that the angular distributions of $ν_e$ and $\barν_e$ cross each other. However, most of the state-of

Helmut Abels, Christine Pfeuffer

In this paper we show the invariance of the Fredholm index of non-smooth pseudodifferential operators with coefficients in Hölder spaces. By means of this invariance we improve previous spectral invariance results for non-smooth pseudodifferential operators $P$ with coefficients in Hölder spaces. For this purpose we approximate $P$ with smooth pseudodifferen

Yuji Yanagihara, Kazuhiko Minami

A one-dimensional cluster model with next-nearest-neighbor interactions and two additional composite interactions is solved; the free energy is obtained and a correlation function is derived exactly. The model is diagonalized by a transformation obtained automatically from its interactions, which is an algebraic generalization of the Jordan-Wigner transforma

Sofia Kostoglou, Hannes Bartosik, Yannis Papaphilippou, Guido Sterbini

Several transverse noise sources, such as power supply ripples, can potentially act as an important limiting mechanism for the luminosity production of the Large Hadron Collider (LHC) and its future High-Luminosity upgrade (HL-LHC). In the presence of non-linearities, depending on the spectral components of the power supply noise and the nature of the source

Yueting Chen, Xiaohui Yu, Nick Koudas

Recent advances in Computer Vision and Deep Learning made possible the efficient extraction of a schema from frames of streaming video. As such, a stream of objects and their associated classes along with unique object identifiers derived via object tracking can be generated, providing unique objects as they are captured across frames. In this paper we initi

Jary Pomponi, Simone Scardapane, Aurelio Uncini

Bayesian Neural Networks (BNNs) are trained to optimize an entire distribution over their weights instead of a single set, having significant advantages in terms of, e.g., interpretability, multi-task learning, and calibration. Because of the intractability of the resulting optimization problem, most BNNs are either sampled through Monte Carlo methods, or tr

Okan Köpüklü, Thomas Ledwon, Yao Rong, Neslihan Kose

The use of hand gestures provides a natural alternative to cumbersome interface devices for Human-Computer Interaction (HCI) systems. However, real-time recognition of dynamic micro hand gestures from video streams is challenging for in-vehicle scenarios since (i) the gestures should be performed naturally without distracting the driver, (ii) micro hand gest

Noah Mendelson, Dipankar Chugh, Jeffrey R. Reimers, Tin S. Cheng

Single photon emitters (SPEs) in hexagonal boron nitride (hBN) have garnered significant attention over the last few years due to their superior optical properties. However, despite the vast range of experimental results and theoretical calculations, the defect structure responsible for the observed emission has remained elusive. Here, by controlling the inc

Yan-Cheng Wei, Bo-Han Wu, Ya-Fen Hsiao, Pin-Ju Tsai

Quantum memories, devices that can store and retrieve photonic quantum states on demand, are essential components for scalable quantum technologies. It is desirable to push the memory towards the broadband regime in order to increase the data rate. Here, we present a theoretical and experimental study on the broadband optical memory based on electromagnetica

Steve Huntsman

Cyclomatic complexity is an incompletely specified but mathematically principled software metric that can be usefully applied to both source and binary code. We consider the application of path homology as a stronger analogue of cyclomatic complexity. We have implemented an algorithm to compute path homology in arbitrary dimension and applied it to several c

Adrià Arbués-Sangüesa, Adrián Martín, Javier Fernández, Carlos Rodríguez

Although orientation has proven to be a key skill of soccer players in order to succeed in a broad spectrum of plays, body orientation is a yet-little-explored area in sports analytics' research. Despite being an inherently ambiguous concept, player orientation can be defined as the projection (2D) of the normal vector placed in the center of the upper-t

Ayan Banerjee, M. K. Jasim, Sushant G. Ghosh

We consider $f(R, T)$ theory of gravity, in which the gravitational Lagrangian is given by an arbitrary function of the Ricci scalar and the trace of the energy-momentum tensor, to study static spherically symmetric wormhole geometries sustained by matter sources with isotropic pressure. According to restrictions on the wormhole geometries, we carefully adop

Luisa Bonolis, Juan-Andres Leon

On the occasion of the 50th anniversary since the beginning of the search for gravitational waves at the Max Planck Society, and in coincidence with the 25th anniversary of the foundation of the Albert Einstein Institute, we explore the interplay between the renaissance of general relativity and the advent of relativistic astrophysics following the German ea

H. Albers, A. Herbst, L. L. Richardson, H. Heine

We report on an improved test of the Universality of Free Fall using a rubidium-potassium dual-species matter wave interferometer. We describe our apparatus and detail challenges and solutions relevant when operating a potassium interferometer, as well as systematic effects affecting our measurement. Our determination of the Eötvös ratio yields $η_{\,\text{R

Yi-Rui Yang, Wu-Jun Li

Distributed learning has become a hot research topic due to its wide application in clusterbased large-scale learning, federated learning, edge computing and so on. Most traditional distributed learning methods typically assume no failure or attack. However, many unexpected cases, such as communication failure and even malicious attack, may happen in real ap

Lorenzo Taggi

We prove that in wide generality the critical curve of the activated random walk model is a continuous function of the deactivation rate, and we provide a bound on its slope which is uniform with respect to the choice of the graph. Moreover, we derive strict monotonicity properties for the probability of a wide class of `increasing' events,extending previous

Lourdes Cruz, Yuriko Pitones, Enrique Reyes

Let $D=(G,\mathcal{O},w)$ be a weighted oriented graph whose edge ideal is $I(D)$. In this paper, we characterize the unmixed property of $I(D)$ for each one of the following cases: $G$ is an $SCQ$ graph; $G$ is a chordal graph; $G$ is a simplicial graph; $G$ is a perfect graph; $G$ has no $4$- or $5$-cycles; $G$ is a graph without $3$- and $5$-cycles; and $

Bertram Düring, Nicos Georgiou, Sara Merino-Aceituno, Enrico Scalas

We discuss various limits of a simple random exchange model that can be used for the distribution of wealth. We start from a discrete state space - discrete time version of this model and, under suitable scaling, we show its functional convergence to a continuous space - discrete time model. Then, we show a thermodynamic limit of the empirical distribution t

Ilaria Castellano, Dikran Dikranjan, Domenico Freni, Anna Giordano Bruno

We introduce the notion of intrinsic semilattice entropy $\widetilde h$ in the category $\mathcal L_{qm}$ of generalized quasimetric semilattices and contractive homomorphisms. By using appropriate categories $\mathfrak X$ and functors $F:\mathfrak X\to\mathcal L_{qm}$ we find specific known entropies $\widetilde h_\mathfrak X$ on $\mathfrak X$ as intrinsic

Dmitry Khangulyan, Felix Aharonian, Carlo Romoli, Andrew Taylor

The synchrotron cooling of relativistic electrons is one of the most effective radiation mechanisms in astrophysics. It not only accompanies the process of particle acceleration but also has feedback on the formation of the energy distribution of the parent electrons. The radiative cooling time of electrons decreases with energy as $t_{\rm syn} \propto 1/E$;

Lukas Schaupp, Patrick Pfreundschuh, Mathias Buerki, Cesar Cadena

Visually poor scenarios are one of the main sources of failure in visual localization systems in outdoor environments. To address this challenge, we present MOZARD, a multi-modal localization system for urban outdoor environments using vision and LiDAR. By extending our preexisting key-point based visual multi-session local localization approach with the use

Xiaojian He, Jinfu Lin, Junming Shen

Few-shot learning (FSL) aims to learn novel visual categories from very few samples, which is a challenging problem in real-world applications. Many methods of few-shot classification work well on general images to learn global representation. However, they can not deal with fine-grained categories well at the same time due to a lack of subtle and local info

Okan K. Orhan, David D. O'Regan

Titanium dioxide (TiO$_2$) presents a long-standing challenge for approximate Kohn-Sham density-functional theory (KS-DFT), as well as to its Hubbard-corrected extension, DFT+$U$. We find that a previously proposed extension of first-principles DFT+$U$ to incorporate a Hund's $J$ correction, termed DFT+$U$+$J$, in combination with parameters calculated u

Vivien Cabannes, Alessandro Rudi, Francis Bach

Annotating datasets is one of the main costs in nowadays supervised learning. The goal of weak supervision is to enable models to learn using only forms of labelling which are cheaper to collect, as partial labelling. This is a type of incomplete annotation where, for each datapoint, supervision is cast as a set of labels containing the real one. The problem

G. E. Volovik

Two different sources of emergent gravity lead to the inverse square of length dimension of metric field, $[g_{μν}]=1/[l]^2$, as distinct from the conventional dimensionless metric, $[g_{μν}]=1$, for $c = 1$. In both scenarios all the physical quantities, which obey diffeomorphism invariance, such as the Newton constant, the scalar curvature, the cosmologica

Laurence J. Cooper, Christine T. H. Davies, Judd Harrison, Javad Komijani

We present results of the first lattice QCD calculations of $B_c \to B_s$ and $B_c \to B_d$ weak matrix elements. Form factors across the entire physical $q^2$ range are then extracted and extrapolated to the physical-continuum limit before combining with CKM matrix elements to predict the semileptonic decay rates $Γ(B_c^+ \to B_s^0 \overline{\ell} ν_{\ell})

Geoffroy J. Aubry, Luis S. Froufe-Pérez, Ulrich Kuhl, Olivier Legrand

We present wave transport experiments in hyperuniform disordered arrays of cylinders with high dielectric permittivity. Using microwaves, we show that the same material can display transparency, photon diffusion, Anderson localization, or a full band gap, depending on the frequency $ν$ of the electromagnetic wave. Interestingly, we find a second weaker band

Martin Balko, Manfred Scheucher, Pavel Valtr

For $d\in\mathbb{N}$, let $S$ be a set of points in $\mathbb{R}^d$ in general position. A set $I$ of $k$ points from $S$ is a $k$-island in $S$ if the convex hull $\mathrm{conv}(I)$ of $I$ satisfies $\mathrm{conv}(I) \cap S = I$. A $k$-island in $S$ in convex position is a $k$-hole in $S$. For $d,k\in\mathbb{N}$ and a convex body $K\subseteq\mathbb{R}^d$ of

Xinyi Zhang, Hang Dong, Zhe Hu, Wei-Sheng Lai

Single image super resolution aims to enhance image quality with respect to spatial content, which is a fundamental task in computer vision. In this work, we address the task of single frame super resolution with the presence of image degradation, e.g., blur, haze, or rain streaks. Due to the limitations of frame capturing and formation processes, image degr

Theo Odijk

A statistical theory is presented of the magnesium ion interacting with lysozyme under conditions where the latter is positively charged. Temporarily assuming magnesium is not noncovalently bound to the protein, I solve the nonlinear Poisson-Boltzmann equation accurately and uniformly in a perturbative fashion. The resulting expression for the effective char

Jon Chaika, Giovanni Forni

We prove that there exists a residual set of (non-rational) polygons such the billiard flow is weakly mixing with respect to the Liouville measure (on the unit tangent bundle to the billiard). This follows, via a Baire category argument, from showing that for any translation surface the product of the flows in almost every pair of directions is ergodic with

Guus Engels, Nerea Aranjuelo, Ignacio Arganda-Carreras, Marcos Nieto

This paper presents a new approach to 3D object detection that leverages the properties of the data obtained by a LiDAR sensor. State-of-the-art detectors use neural network architectures based on assumptions valid for camera images. However, point clouds obtained from LiDAR are fundamentally different. Most detectors use shared filter kernels to extract fea

Myeongjin Kim, Hyeran Byun

Since annotating pixel-level labels for semantic segmentation is laborious, leveraging synthetic data is an attractive solution. However, due to the domain gap between synthetic domain and real domain, it is challenging for a model trained with synthetic data to generalize to real data. In this paper, considering the fundamental difference between the two do

Catarina Botelho, Francisco Teixeira, Thomas Rolland, Alberto Abad

The potential of speech as a non-invasive biomarker to assess a speaker's health has been repeatedly supported by the results of multiple works, for both physical and psychological conditions. Traditional systems for speech-based disease classification have focused on carefully designed knowledge-based features. However, these features may not represent

Chong Qi, Roberto Liotta, Ramon Wyss

A salient feature of quantum mechanics is the inherent property of collective quantum motion, when apparent independent quasiparticles move in highly correlated trajectories, resulting in strongly enhanced transition probabilities. To assess the extend of a collective quantity requires an appropriate definition of the uncorrelated average motion, often expre

Qiaolin Xia, Xiujun Li, Chunyuan Li, Yonatan Bisk

Learning to navigate in a visual environment following natural language instructions is a challenging task because natural language instructions are highly variable, ambiguous, and under-specified. In this paper, we present a novel training paradigm, Learn from EveryOne (LEO), which leverages multiple instructions (as different views) for the same trajectory

Chen Haoyu, Teng Minggui, Shi Boxin, Wang YIzhou

Event cameras are bio-inspired cameras which can measure the change of intensity asynchronously with high temporal resolution. One of the event cameras' advantages is that they do not suffer from motion blur when recording high-speed scenes. In this paper, we formulate the deblurring task on traditional cameras directed by events to be a residual learnin

Stephan Rave, Jens Saak

In this contribution we aim to satisfy the demand for a publicly available benchmark for parametric model order reduction that is scalable both in degrees of freedom as well as parameter dimension.

Saneem Ahmed Chemmengath, Soumava Paul, Samarth Bharadwaj, Suranjana Samanta

Zero-shot learning (ZSL) algorithms typically work by exploiting attribute correlations to be able to make predictions in unseen classes. However, these correlations do not remain intact at test time in most practical settings and the resulting change in these correlations lead to adverse effects on zero-shot learning performance. In this paper, we present a

Andrea Loi, Roberto Mossa

Let $(g, X)$ be a Kähler-Ricci soliton on a complex manifold $M$. We prove that if the Kähler manifold $(M, g)$ can be Kähler immersed into a definite or indefinite complex space form of constant holomorphic sectional curvature $2c$, then $g$ is Einstein. Moreover, its Einstein constant is a rational multiple of $c$.

Bin Fang, Xingming Long, Yifan Zhang, GuoYi Luo

This paper introduces a new type of system for fabric defect detection with the tactile inspection system. Different from existed visual inspection systems, the proposed system implements a vision-based tactile sensor. The tactile sensor, which mainly consists of a camera, four LEDs, and an elastic sensing layer, captures detailed information about fabric su

Cécile Armana, Fu-Tsun Wei

In this paper, we obtain two analogues of the Sturm bound for modular forms in the function field setting. In the case of mixed characteristic, we prove that any harmonic cochain is uniquely determined by an explicit finite number of its first Fourier coefficients where our bound is much smaller than the ones in the literature. A similar bound is derived for

V. Giménez-Alventosa, V. Giménez Gómez, S. Oliver Gil

Monte Carlo methods provide detailed and accurate results for radiation transport simulations. Unfortunately, the high computational cost of these methods limits its usage in real-time applications. Moreover, existing computer codes do not provide a methodology for adapting these kind of simulations to specific problems without advanced knowledge of the corr

David Felce, Vlatko Vedral

We propose a thermodynamic refrigeration cycle which uses Indefinite Causal Orders to achieve non-classical cooling. The cycle cools a cold reservoir while consuming purity in a control qubit. We first show that the application to an input state of two identical thermalizing channels of temperature $T$ in an indefinite causal order can result in an output st

Andreas Lubatsch, Regine Frank

We implement externally excited ZnO Mie resonators in a framework of a generalized Hubbard Hamiltonian to investigate the lifetimes of excitons and exciton-polaritons out of thermodynamical equilibrium. Our results are derived by a Floquet-Keldysh-Green's formalism with Dynamical Mean Field Theory (DMFT) and a second order iterative perturbation theory s

Yalong Cao, Yukinobu Toda

The Gopakumar-Vafa type invariants on Calabi-Yau 4-folds (which are non-trivial only for genus zero and one) are defined by Klemm-Pandharipande from Gromov-Witten theory, and their integrality is conjectured. In a previous work of Cao-Maulik-Toda, $\mathrm{DT}_4$ invariants with primary insertions on moduli spaces of one dimensional stable sheaves are used t

Nikola Andrejic, Ravi Kunjwal

Measurements in quantum theory exhibit incompatibility, i.e., they can fail to be jointly measurable. An intuitive way to represent the (in)compatibility relations among a set of measurements is via a hypergraph representing their joint measurability structure: its vertices represent measurements and its hyperedges represent (all and only) subsets of compati

Michał Bednarek, Piotr Kicki, Jakub Bednarek, Krzysztof Walas

Soft grippers are gaining significant attention in the manipulation of elastic objects, where it is required to handle soft and unstructured objects which are vulnerable to deformations. A crucial problem is to estimate the physical parameters of a squeezed object to adjust the manipulation procedure, which is considered as a significant challenge. To the be

Alexandros Tanzanakis, John Lygeros

We consider the problem of discounted optimal state-feedback regulation for general unknown deterministic discrete-time systems. It is well known that open-loop instability of systems, non-quadratic cost functions and complex nonlinear dynamics, as well as the on-policy behavior of many reinforcement learning (RL) algorithms, make the design of model-free op

Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas

The expressivity of neural networks as a function of their depth, width and type of activation units has been an important question in deep learning theory. Recently, depth separation results for ReLU networks were obtained via a new connection with dynamical systems, using a generalized notion of fixed points of a continuous map $f$, called periodic points.

Ildikó Pethes, Imre Bakó, László Pusztai

Hydrogen bonding to chloride ions has been frequently discussed over the past 5 decades. Still, the possible role of such secondary intermolecular bonding interactions in hydrogen bonded networks has not been investigated in any detail. Here we consider computer models of concentrated aqueous LiCl solutions and compute usual hydrogen bond network characteris

Pedro Forton, Jose M Saldana, Julian Fernandez-Navajas, Jose Ruiz-Mas

This paper presents a graphical interface for the management of a wireless local area network that integrates a set of coordinated Wi-Fi access points. The interface interacts with a network application that is responsible for load balancing and mobility management. The graphical application is able to obtain and display the information stored in a system th

Ziliang Lai, Chenxia Han, Chris Liu, Pengfei Zhang

The impressive accuracy of deep neural networks (DNNs) has created great demands on practical analytics over video data. Although efficient and accurate, the latest video analytic systems have not supported analytics beyond selection and aggregation queries. In data analytics, Top-K is a very important analytical operation that enables analysts to focus on t

Ildikó Pethes, Andrea Piarristeguy, Annie Pradel, Stefan Michalik

Chemical short range order and topology of Ge$_{x}$Ga$_{x}$Te$_{100-2x}$ glasses was investigated by neutron- and x-ray diffraction as well as Ge and Ga K-edge extended x-ray absorption fine structure (EXAFS) measurements. Large scale structural models were obtained by fitting experimental datasets simultaneously with the reverse Monte Carlo simulation techn

Mehmet Yamac, Mete Ahishali, Serkan Kiranyaz, Moncef Gabbouj

Support estimation (SE) of a sparse signal refers to finding the location indices of the non-zero elements in a sparse representation. Most of the traditional approaches dealing with SE problem are iterative algorithms based on greedy methods or optimization techniques. Indeed, a vast majority of them use sparse signal recovery techniques to obtain support s

Guangming Wang, Chi Zhang, Hesheng Wang, Jingchuan Wang

In autonomous driving, monocular sequences contain lots of information. Monocular depth estimation, camera ego-motion estimation and optical flow estimation in consecutive frames are high-profile concerns recently. By analyzing tasks above, pixels in the middle frame are modeled into three parts: the rigid region, the non-rigid region, and the occluded regio

Reggie C. Pantig, Emmanuel T. Rodulfo

In this paper, we present the weak deflection angle in a Schwarzschild black hole of mass $m$ surrounded by the dark matter of mass $M$ and thickness $Δr_{s}$. The Gauss-Bonnet theorem, formulated for asymptotic spacetimes, is found to be ill-behaved in the third-order of $1/Δr_{s}$ for very large $Δr_{s}$. Using the finite-distance for the radial locations

Pham Huu Thanh Binh, Cristóvão Cruz, Karen Egiazarian

This paper proposes a learning-based denoising method called FlashLight CNN (FLCNN) that implements a deep neural network for image denoising. The proposed approach is based on deep residual networks and inception networks and it is able to leverage many more parameters than residual networks alone for denoising grayscale images corrupted by additive white G

Fouad Elmouhib, Mohamed Talbi, Abdelmalek Azizi

Let $k \,=\, \mathbb{Q}(\sqrt[5]{n},ζ_5)$, where $n$ is a positive integer, $5^{th}$ power-free, whose $5-$class group is isomorphic to $\mathbb{Z}/5\mathbb{Z}\times\mathbb{Z}/5\mathbb{Z}$. Let $k_0\,=\,\mathbb{Q}(ζ_5)$ be the cyclotomic field containing a primitive $5^{th}$ root of unity $ζ_5$. Let $C_{k,5}^{(σ)}$ the group of the ambiguous classes under th