arXiv papers from March 2021

Kenneth Stewart, Andreea Danielescu, Timothy Shea, Emre Neftci

Neuromorphic hardware equipped with learning capabilities can adapt to new, real-time data. While models of Spiking Neural Networks (SNNs) can now be trained using gradient descent to reach an accuracy comparable to equivalent conventional neural networks, such learning often relies on external labels. However, real-world data is unlabeled which can make sup

Fatoumata Dama, Christine Sinoquet

Time series modeling for predictive purpose has been an active research area of machine learning for many years. However, no sufficiently comprehensive and meanwhile substantive survey was offered so far. This survey strives to meet this need. A unified presentation has been adopted for entire parts of this compilation. A red thread guides the reader from ti

Faraz Torabi, Garrett Warnell, Peter Stone

In imitation learning from observation IfO, a learning agent seeks to imitate a demonstrating agent using only observations of the demonstrated behavior without access to the control signals generated by the demonstrator. Recent methods based on adversarial imitation learning have led to state-of-the-art performance on IfO problems, but they typically suffer

Ming Ng, Steven Vickers

We define a point-free construction of real exponentiation and logarithms, i.e.\ we construct the maps $\exp\colon (0, \infty)\times \mathbb{R} \rightarrow \!(0,\infty),\, (x, \zeta) \mapsto x^\zeta$ and $\log\colon (1,\infty)\times (0, \infty) \rightarrow\mathbb{R},\, (b, y) \mapsto \log_b(y)$, and we develop familiar algebraic rules for them. The point-fre

Andres Baloian, Nils Murrugarra-Llerena, Jose M. Saavedra

Visual attributes play an essential role in real applications based on image retrieval. For instance, the extraction of attributes from images allows an eCommerce search engine to produce retrieval results with higher precision. The traditional manner to build an attribute extractor is by training a convnet-based classifier with a fixed number of classes. Ho

Víctor Sotomayor

Let $G$ be a finite group, and let $\Delta(G)$ be the prime graph built on its set of conjugacy class sizes: this is the (simple undirected) graph whose vertices are the prime numbers dividing some conjugacy class size of $G$, and two distinct vertices $p, q$ are adjacent if and only if $pq$ divides some class size of $G$. In this paper, we characterise the

Daniel Reusche, Nicolás Della Penna

Designing truthful, revenue maximizing auctions is a core problem of auction design. Multi-item settings have long been elusive. Recent work (arXiv:1706.03459) introduces effective deep learning techniques to find such auctions for the prior-dependent setting, in which distributions about bidder preferences are known. One remaining problem is to obtain prior

Nikos Katzouris, Alexander Artikis, Georgios Paliouras

Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event patte

L. B. Pires, D. S. Ether, B. Spreng, G. R. S. Araújo

We measure the colloidal interaction between two silica microspheres in aqueous solution in the distance range from $0.2\,\mu$m to $0.5\,\mu$m with the help of optical tweezers. When employing a sample with a low salt concentration, the resulting interaction is dominated by the repulsive double-layer interaction which is fully characterized. The double-layer

Daniël Kroes, Brendon Rhoades

The coinvariant algebra is a quotient of the polynomial ring $\mathbb{Q}[x_1,\ldots,x_n]$ whose algebraic properties are governed by the combinatorics of permutations of length $n$. A word $w = w_1 \dots w_n$ over the positive integers is packed if whenever $i > 2$ appears as a letter of $w$, so does $i-1$. We introduce a quotient $S_n$ of $\mathbb{Q}[x_1,\l

M. M. Almarashi

We study the $a_1a_1$ and $Za_1$ decay channels of the next-to-lightest CP-even Higgs boson $h_2$ of the NMSSM at the LHC, where the $h_2$ is produced in gluon fusion. It is found that while the $h_2$ discovery is impossible through the latter channel, the former one in the $ 4\tau$ final state is a promising channel to discover the $h_2$ with masses up to a

Vladimir S. Gerdjikov, Rossen I. Ivanov

Multi-component integrable generalizations of the Fokas-Lenells equation, associated with each irreducible Hermitian symmetric space are formulated. Description of the underlying structures associated to the integrability, such as the Lax representation and the bi-Hamiltonian formulation of the equations is provided. Two reductions are considered as well, on

Nao Komiyama

In this paper, we settle the problem posed by Singer which is on a comparison problem between the renormalized values of shuffle type and of harmonic type of multiple zeta functions.

Vitor Guizilini, Igor Vasiljevic, Rares Ambrus, Greg Shakhnarovich

Self-supervised monocular depth and ego-motion estimation is a promising approach to replace or supplement expensive depth sensors such as LiDAR for robotics applications like autonomous driving. However, most research in this area focuses on a single monocular camera or stereo pairs that cover only a fraction of the scene around the vehicle. In this work, w

Lam Si Tung Ho, Edward Susko

Likelihood-based methods are widely considered the best approaches for reconstructing ancestral states. Although much effort has been made to study properties of these methods, previous works often assume that both the tree topology and edge lengths are known. In some scenarios the tree topology might be reasonably well known for the taxa under study. When s

Xuye Liu, Dakuo Wang, April Wang, Yufang Hou

Jupyter notebook allows data scientists to write machine learning code together with its documentation in cells. In this paper, we propose a new task of code documentation generation (CDG) for computational notebooks. In contrast to the previous CDG tasks which focus on generating documentation for single code snippets, in a computational notebook, one docum

Jason Garver

Content: Qualitative and ad-hoc descriptions of observations of the "undergraduate" and "graduate" effects. Comparisons between the classical models of both undergraduate and graduate systems separately lead to the conclusion that a quantized model is inevitably required to explain certain effects such as "Spooky Action At A Seminar" and the FTR (Food Travel

Filip Ficek

The Schr\"odinger equation with a harmonic potential coupled to the Poisson equation, called the Schr\"odinger-Newton-Hooke (SNH) system, has been considered in a variety of physical contexts, ranging from quantum mechanics to general relativity. Our work is directly motivated by the fact that the SNH system describes the nonrelativistic limit of the Einstei

Gonzalo Gabriel Méndez, Luis Galárraga, Katherine Chiluiza

Course selection is a crucial activity for students as it directly impacts their workload and performance. It is also time-consuming, prone to subjectivity, and often carried out based on incomplete information. This task can, nevertheless, be assisted with computational tools, for instance, by predicting performance based on historical data. We investigate

Marianne Cowherd, Isaac Malsky

While the presence of ghosts has been known for decades, the impact of these apparitions on remote sensing observations has gone unquantified, leaving atmospheric corrections susceptible to ghosting. In this work, we present the first spectral characterization of three common ghost types and provide a framework for incorporating these properties into atmosph

Zekun Zhuang, V. F. Mitrović, J. B. Marston

Electron spins in edge or surface modes of topological insulators (TIs) with strong spin-orbit coupling cannot be directly manipulated with microwaves due to the locking of electron spin to its momentum. We show by contrast that a resistively detected nuclear magnetic resonance (RDNMR) based technique can be used to probe the helical nature of surface conduc

R. Becket Ebitz, Benjamin Y. Hayden

A major shift is happening within neurophysiology: a population doctrine is drawing level with the single-neuron doctrine that has long dominated the field. Population-level ideas have so far had their greatest impact in motor neuroscience, but they hold great promise for resolving open questions in cognition as well. Here, we codify the population doctrine

Paolo Personnettaz, Steffen Landgraf, Michael Nimtz, Norbert Weber

Liquid metal electrodes are one of the key components of different electrical energy storage technologies. The understanding of transport phenomena in liquid electrodes is mandatory in order to ensure efficient operation. In the present study we focus our attention on the positive electrode of the Li||Bi liquid metal battery. Starting from a real experimenta

Hossam El-Rewaidy, Rui Guo, Amanda Paskavitz, Tuyen Yankama

Purpose: To develop and evaluate MyoMapNet, a rapid myocardial T1 mapping approach that uses neural networks (NN) to estimate voxel-wise myocardial T1 and extracellular (ECV) from T1-weighted images collected after a single inversion pulse over 4-5 heartbeats. Method: MyoMapNet utilizes a simple fully-connected NN to estimate T1 values from 5 (native) or 4 (

Yufeng Chen

Node.js is one of the most popular frameworks for building web applications. As software systems mature, the cost of running their entire regression test suite can become significant. Selective Regression Testing (SRT) is a technique that executes only a subset of tests the regression test suite can detect software failures more efficiently. Previous SRT stu

Oscar A. Douglas-Gallardo, Connor L. Box, Reinhard J. Maurer

Light-driven plasmonic enhancement of chemical reactions on metal catalysts is a promising strategy to achieve highly selective and efficient chemical transformations. The study of plasmonic catalyst materials has traditionally focused on late transition metals such as Au, Ag, and Cu. In recent years, there has been increasing interest in the plasmonic prope

Wouter Dekens, Jordy de Vries, Tom Tong

Charged currents are probed in low-energy precision $\beta$-decay experiments and at high-energy colliders, both of which aim to measure or constrain signals of beyond-the-Standard-Model physics. In light of future $\beta$-decay and LHC measurements that will further explore these non-standard interactions, we investigate what neutrinoless double-$\beta$ dec

Gerda Bortsova, Florian Dubost, Laurens Hogeweg, Ioannis Katramados

Adversarial attacks consist in maliciously changing the input data to mislead the predictions of automated decision systems and are potentially a serious threat for automated medical image analysis. Previous studies have shown that it is possible to adversarially manipulate automated segmentations produced by neural networks in a targeted manner in the white

Kajetan Grodecki, Aditya Killekar, Andrew Lin, Sebastien Cadet

Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease (COVID-19) patients, but are not part of the clinical routine since required manual segmentation of lung lesions is prohibitively time-consuming. We propose a new fully automated deep learning framework for rapid quantific

Chien-Lun Chen, Leana Golubchik, Ranjan Pal

An accountable algorithmic transparency report (ATR) should ideally investigate the (a) transparency of the underlying algorithm, and (b) fairness of the algorithmic decisions, and at the same time preserve data subjects' privacy. However, a provably formal study of the impact to data subjects' privacy caused by the utility of releasing an ATR (that investig

Alex M. Wilhelm, David D. Schmidt, Daniel E. Adams, Charles G. Durfee

We present a phase retrieval algorithm for dispersion scan (d-scan), inspired by ptychography, which is capable of characterizing multiple mutually-incoherent ultrafast pulses (or modes) in a pulse train simultaneously from a single d-scan trace. In addition, a form of Newton's method is employed as a solution to the square root problem commonly encountered

Amie Albrecht, Phil Howlett, Peter Pudney

We propose an analytic solution to the problem of finding optimal driving strategies that minimize total tractive energy consumption for a fleet of trains travelling on the same track in the same direction subject to clearance-time equality constraints that ensure safe separation and compress the line-occupancy timespan. We assume the track is divided into s

H. Monteiro, D. A. Barros, W. S. Dias, J. R. D. Lépine

In this work we explore the new catalog of galactic open clusters that became available recently, containing 1750 clusters that have been re-analysed using the Gaia DR2 catalog to determine the stellar memberships. We used the young open clusters as tracers of spiral arms and determined the spiral pattern rotation speed of the Galaxy and the corotation radiu

Maximilian Klumpp, Guido Schneider

Time-harmonic electromagnetic waves in vacuum are described by the Helmholtz equation $\Delta u+\omega ^{2}u=0 $ for $ (x,y,z) \in \mathbb{R}^3 $. For the evolution of such waves along the $z$-axis a Schr\"odinger equation can be derived through a multiple scaling ansatz. It is the purpose of this paper to justify this formal approximation by proving bounds

Li Li

We study the well-posedness of a semilinear fractional diffusion equation and formulate an associated inverse problem. We determine fractional power type nonlinearities from the exterior partial measurements of the Dirichlet-to-Neumann map. Our arguments are based on a first order linearization as well as the parabolic Runge approximation property.

Francisco L. Andrade, Mário A. T. Figueiredo, João Xavier

The Banach-Picard iteration is widely used to find fixed points of locally contractive (LC) maps. This paper extends the Banach-Picard iteration to distributed settings; specifically, we assume the map of which the fixed point is sought to be the average of individual (not necessarily LC) maps held by a set of agents linked by a communication network. An add

Thomas Beckers, Sandra Hirche, Leonardo Colombo

Formation control algorithms for multi-agent systems have gained much attention in the recent years due to the increasing amount of mobile and aerial robotic swarms. The design of safe controllers for these vehicles is a substantial aspect for an increasing range of application domains. However, parts of the vehicle's dynamics and external disturbances are o

Matthias Bahr, Leif Laszig

Tis paper is a literature review focusing on human capital, skills of employees, demographic change, management, training and their impact on productivity growth. Intrafirm behaviour has been recognized as a potentially important driver for productivity. Results from surveys show that management practices have become more structured, in the sense of involvin

Jianhui Li, Tongou Yang

We prove decoupling inequalities for mixed-homogeneous bivariate polynomials, which partially answers a conjecture of Bourgain, Demeter and Kemp.

Raunak Dey, Avijit Kundu, Biswajit Das, Ayan Banerjee

A large number of processes in the mesoscopic world occur out of equilibrium, where the time course of a system evolution becomes immensely important since it is driven principally by dissipative effects. Non-equilibrium steady states (NESS) represent a crucial category in such systems, where relaxation timescales are comparable to the operational timescales

Susan Kempinger, Yu-Sheng Huang, Paul Lammert, Michael Vogel

Artificial spin ice systems have opened experimental windows into a range of model magnetic systems through the control of interactions among nanomagnet moments. This control has previously been enabled by altering the nanomagnet size and the geometry of their placement. Here we demonstrate that the interactions in artificial spin ice can be further controll

Farnoosh Faraji, Faraz Lotfi, Javad Khorramdel, Ali Najafi

Driver drowsiness detection has been the subject of many researches in the past few decades and various methods have been developed to detect it. In this study, as an image-based approach with adequate accuracy, along with the expedite process, we applied YOLOv3 (You Look Only Once-version3) CNN (Convolutional Neural Network) for extracting facial features a

Peter Nabende, David Kabiito, Claire Babirye, Hewitt Tusiime

The increasing occurrence, forms, and negative effects of misinformation on social media platforms has necessitated more misinformation detection tools. Currently, work is being done addressing COVID-19 misinformation however, there are no misinformation detection tools for any of the 40 distinct indigenous Ugandan languages. This paper addresses this gap by

Zachary E. Lee, K. Max Zhang

Advanced building control methods such as model predictive control (MPC) offer significant potential benefits to both consumers and grid operators, but the high computational requirements have acted as barriers to more widespread adoption. Local control computation requires installation of expensive computational hardware, while cloud computing introduces da

Dia'aaldin J. Bisharat, Robert J. Davis, Yun Zhou, Prabhakar R. Bandaru

Control and manipulation of electromagnetic waves has reached a new level with the recent understanding of topological states of matter. These metamaterials have the potential to revolutionize many areas in traditional electromagnetic design, from highly robust cavities to small footprint waveguides. Much of the past literature has been on the cutting edge o

Vera Könyves, Derek Ward-Thompson, Kate Pattle, James Di Francesco

We present the first 850 $\mu$m polarization observations in the most active star-forming site of the Rosette Molecular Cloud (RMC, $d\sim$1.6 kpc) in the wall of the Rosette Nebula, imaged with the SCUBA-2/POL-2 instruments of the JCMT, as part of the B-Fields In Star-Forming Region Observations 2 (BISTRO-2) survey. From the POL-2 data we find that the pola

Timo Lohrenz, Zhengyang Li, Tim Fingscheidt

Stream fusion, also known as system combination, is a common technique in automatic speech recognition for traditional hybrid hidden Markov model approaches, yet mostly unexplored for modern deep neural network end-to-end model architectures. Here, we investigate various fusion techniques for the all-attention-based encoder-decoder architecture known as the

A. Philip Dawid, Monica Musio

We describe and contrast two distinct problem areas for statistical causality: studying the likely effects of an intervention ("effects of causes"), and studying whether there is a causal link between the observed exposure and outcome in an individual case ("causes of effects"). For each of these, we introduce and compare various formal frameworks that have

Peipei Lu, Andreas Rupp, Guido Kanschat

Uniform convergence of the geometric multigrid V-cycle is proven for HDG methods with a new set of assumptions on the injection operators from coarser to finer meshes. The scheme involves standard smoothers and local solvers which are bounded, convergent, and consistent. Elliptic regularity is used in the proofs. The new assumptions admit injection operators

J. Sadeghi, S. Noori Gashti

In this paper, we study a constant-roll inflationary model in the presence of a noncommutative parameter with a homogeneous scalar field minimally coupled to gravity. The specific noncommutative inflation conditions proposed new consequences. On the other hand, we use anisotropic conditions and find new anisotropic constant-roll solutions with respect to non

G. Modanese

We have run numerical simulations of Euclidean lattice quantum gravity for metrics which are time-independent and spherically symmetric. The radial variable is discretized as $r=hL_{Planck}$, with $h=0,1,...,N$ and $N$ up to $10^5$. The Lagrangian is of the form $\sqrt{g}(R+\alpha R^2)$ (in units $c=\hbar=G=1$) and the action is positive-definite, allowing t

Christian Pfeifer, Sebastian Schuster

With the advent of gravitational wave astronomy and first pictures of the "shadow" of the central black hole of our milky way, theoretical analyses of black holes (and compact objects mimicking them sufficiently closely) have become more important than ever. The near future promises more and more detailed information about the observable black holes and blac

M. Khanahmadi, A. T. Rezakhani

For heat engines working between two heat baths, functionality is often conditioned on a set of fixed constraints such as given internal structure of the engine and given temperatures for the baths. It is, however, important to devise heat engines which can function adaptively, in particular when the engine is a quantum system and the baths are subject to fl

Suraj Pawar, Omer San, Adil Rasheed, Ionel M. Navon

This work presents a hybrid modeling approach to data-driven learning and representation of unknown physical processes and closure parameterizations. These hybrid models are suitable for situations where the mechanistic description of dynamics of some variables is unknown, but reasonably accurate observational data can be obtained for the evolution of the st

Tarek Mealy, Ahmed F. Abdelshafy, Filippo Capolino

The concept of exceptional point of degeneracy (EPD) is used to conceive a degenerate synchronization regime that is able to enhance the level of output power and power conversion efficiency for backward wave oscillators (BWOs) operating at millimeter-wave and Terahertz frequencies. Standard BWOs operating at such high frequency ranges typically generate out

Sandro Mattarei, Marco Pizzato

We study and partially classify cubic rational expressions $g(x)/h(x)$ over a finite field $\mathbb{F}_q$, up to pre- and post-composition with independent M\"obius transformations. In particular, we obtain a full classification when $q$ is even, and prove an upper bound of $4q$ for the number of equivalence classes when $q$ is odd.

Łukasz Cholewa, Piotr Oprocha

The paper deals with dynamics of expanding Lorenz maps, which appear in a natural way as Poincar\`e maps in geometric models of well-known Lorenz attractor. Using both analytical and symbolic approaches, we study connections between periodic points, completely invariant sets and renormalizations. We show that some renormalizations may be connected with compl

I. Abt, F. Fischer, F. Hagemann, L. Hauertmann

The open-source software package SolidStateDetectors$.$jl to calculate the fields and simulate the drifts of charge carriers in solid state detectors, together with the corresponding pulses, is introduced. The package can perform all calculations in full 3D while it can also make use of detector symmetries. The effect of the surroundings of a detector can al

Jamie Yap, John J. Dziak, Raju Maiti, Kevin G. Lynch

Dynamic treatment regimens (DTRs), also known as treatment algorithms or adaptive interventions, play an increasingly important role in many health domains. DTRs are motivated to address the unique and changing needs of individuals by delivering the type of treatment needed, when needed, while minimizing unnecessary treatment. Practically, a DTR is a sequenc

Abhinav Khattar, Aviral Joshi, Har Simrat Singh, Pulkit Goel

We tackle the challenge of Visual Question Answering in multi-image setting for the ISVQA dataset. Traditional VQA tasks have focused on a single-image setting where the target answer is generated from a single image. Image set VQA, however, comprises of a set of images and requires finding connection between images, relate the objects across images based on

Aviral Joshi, Chengzhi Huang, Har Simrat Singh

This work focuses on comparing different solutions for machine translation on low resource language pairs, namely, with zero-shot transfer learning and unsupervised machine translation. We discuss how the data size affects the performance of both unsupervised MT and transfer learning. Additionally we also look at how the domain of the data affects the result

Emanuel Carneiro, Mithun Kumar Das, Alexandra Florea, Angel V. Kumchev

We improve the current bounds for an inequality of Erd\H{o}s and Tur\'an from 1950 related to the discrepancy of angular equidistribution of the zeros of a given polynomial. Building upon a recent work of Soundararajan, we establish a novel connection between this inequality and an extremal problem in Fourier analysis involving the maxima of Hilbert transfor

Jason Li, Danupon Nanongkai, Debmalya Panigrahi, Thatchaphol Saranurak

The vertex connectivity of an $m$-edge $n$-vertex undirected graph is the smallest number of vertices whose removal disconnects the graph, or leaves only a singleton vertex. In this paper, we give a reduction from the vertex connectivity problem to a set of maxflow instances. Using this reduction, we can solve vertex connectivity in $\tilde O(m^{\alpha})$ ti

Yijian Zou

Given a critical quantum spin chain, we show how universal information about its quantum critical point can be extracted from wavefunction overlaps. More specifically, we consider overlap between low-energy eigenstates of the spin chain Hamiltonian with different boundary conditions, namely periodic boundary conditions and open boundary conditions. We show t

Farzad Pourbabaee

We study the experimentation dynamics of a decision maker (DM) in a two-armed bandit setup (Bolton and Harris (1999)), where the agent holds ambiguous beliefs regarding the distribution of the return process of one arm and is certain about the other one. The DM entertains Multiplier preferences a la Hansen and Sargent (2001), thus we frame the decision makin

Xiao Tan, Wenceslao Shaw Cortez, Dimos V. Dimarogonas

In this paper, we propose a notion of high-order (zeroing) barrier functions that generalizes the concept of zeroing barrier functions and guarantees set forward invariance by checking their higher order derivatives. The proposed formulation guarantees asymptotic stability of the forward invariant set, which is highly favorable for robustness with respect to

Shuo Han, Samuel Remedios, Aaron Carass, Michael Schär

To super-resolve the through-plane direction of a multi-slice 2D magnetic resonance (MR) image, its slice selection profile can be used as the degeneration model from high resolution (HR) to low resolution (LR) to create paired data when training a supervised algorithm. Existing super-resolution algorithms make assumptions about the slice selection profile s

Hudson M. S. Bruno, Esther L. Colombini

The Simultaneous Localization and Mapping (SLAM) problem addresses the possibility of a robot to localize itself in an unknown environment and simultaneously build a consistent map of this environment. Recently, cameras have been successfully used to get the environment's features to perform SLAM, which is referred to as visual SLAM (VSLAM). However, classic

Devansh Jalota, Kiril Solovey, Matthew Tsao, Stephen Zoepf

System optimum (SO) routing, wherein the total travel time of all users is minimized, is a holy grail for transportation authorities. However, SO routing may discriminate against users who incur much larger travel times than others to achieve high system efficiency, i.e., low total travel times. To address the inherent unfairness of SO routing, we study the

Marcelo Lopes Pereira Junior, Luiz Antonio Ribeiro Junior

Graphene-based nanofolds (GNFs) are edge-connected 2D stacked monolayers originated from single-layer graphene. Graphene-based nanoscrolls (GNSs) are nanomaterials with geometry resembling graphene layers rolled up into a spiral (papyrus-like) form. Both GNSs and GNFs structures induce significant changes in the mechanical and optoelectronic properties of si

Christina N. Harrington, Ben Jelen, Amanda Lazar, Aqueasha Martin-Hammond

Technology has the opportunity to assist older adults as they age in place, coordinate caregiving resources, and meet unmet needs through access to resources. Currently, older adults use consumer technologies to support everyday life, however these technologies are not always accessible or as useful as they can be. Indeed, industry has attempted to create sm

Yuexia L. Lin, Nicholas J. Derr, Chris H. Rycroft

We present a numerical method specifically designed for simulating three-dimensional fluid--structure interaction (FSI) problems based on the reference map technique (RMT). The RMT is a fully Eulerian FSI numerical method that allows fluids and large-deformation elastic solids to be represented on a single fixed computational grid. This eliminates the need f

Lea A. Shanley, Lucy Fortson, Tanya Berger-Wolf, Kevin Crowston

Machine learning, artificial intelligence, and deep learning have advanced significantly over the past decade. Nonetheless, humans possess unique abilities such as creativity, intuition, context and abstraction, analytic problem solving, and detecting unusual events. To successfully tackle pressing scientific and societal challenges, we need the complementar

Hanan Herzig Sheinfux, Matteo Ceccanti, Iacopo Torre, Lorenzo Orsini

Light in hyperbolic dispersion media is known to exhibit an intriguing ray-like character. However, detailed understanding of ray-like excitations in hyperbolic media is surprisingly limited, mostly based on numerical simulations. In our work, we analytically describe the formation of multimodal ray-like excitations in a planar slab of hyperbolic media. We d

Xiaodong Wei

We present a novel method named truncated hierarchical unstructured splines (THU-splines) that supports both local $h$-refinement and unstructured quadrilateral meshes. In a THU-spline construction, an unstructured quadrilateral mesh is taken as the input control mesh, where the degenerated-patch method [18] is adopted in irregular regions to define $C^1$-co

Richard I. Anderson, Sherry H. Suyu, Antoine Mérand

From 22 to 26 June 2020, we hosted ESO's first live e-conference, #H02020, from within ESO headquarters in Garching, Germany. Every day, between 200 and 320 researchers around the globe tuned in to discuss the nature and implications of the discord between precise determinations of the Universe's expansion rate, H0. Originally planned as an in-person meeting

Sebastian Mežnar, Nada Lavrač, Blaž Škrlj

Understanding how information propagates in real-life complex networks yields a better understanding of dynamic processes such as misinformation or epidemic spreading. The recently introduced branch of machine learning methods for learning node representations offers many novel applications, one of them being the task of spreading prediction addressed in thi

Yupeng Fu, Chinmay Soman

Uber's business is highly real-time in nature. PBs of data is continuously being collected from the end users such as Uber drivers, riders, restaurants, eaters and so on everyday. There is a lot of valuable information to be processed and many decisions must be made in seconds for a variety of use cases such as customer incentives, fraud detection, machine l

Carine Rognon, Taylor Bunge, Meiyuzi Gao, Chip Connor

Social touch is essential for our social interactions, communication, and well-being. It has been shown to reduce anxiety and loneliness; and is a key channel to transmit emotions for which words are not sufficient, such as love, sympathy, reassurance, etc. However, direct physical contact is not always possible due to being remotely located, interacting in

Hudson M. S. Bruno, Esther L. Colombini

Classical Visual Simultaneous Localization and Mapping (VSLAM) algorithms can be easily induced to fail when either the robot's motion or the environment is too challenging. The use of Deep Neural Networks to enhance VSLAM algorithms has recently achieved promising results, which we call hybrid methods. In this paper, we compare the performance of hybrid mon

Li Zhang, Faezeh Tafazzoli, Gunther Krehl, Runsheng Xu

The majority of current approaches in autonomous driving rely on High-Definition (HD) maps which detail the road geometry and surrounding area. Yet, this reliance is one of the obstacles to mass deployment of autonomous vehicles due to poor scalability of such prior maps. In this paper, we tackle the problem of online road map extraction via leveraging the s

Girmaw Abebe Tadesse, Hamza Javed, Yong Liu, Jin Liu

Myocardial Infarction (MI) has the highest mortality of all cardiovascular diseases (CVDs). Detection of MI and information regarding its occurrence-time in particular, would enable timely interventions that may improve patient outcomes, thereby reducing the global rise in CVD deaths. Electrocardiogram (ECG) recordings are currently used to screen MI patient

Clebson Cruz, M. F. Anka, M. S. Reis, Romain Bachelard

The study of advanced quantum devices for energy storage has attracted the attention of the scientific community in the past few years. Although several theoretical progresses have been achieved recently, experimental proposals of platforms operating as quantum batteries under ambient conditions are still lacking. In this context, this work presents a feasib

Rajeev Singh

We study and analyse the conformal transformations of different conservation laws in the spin hydrodynamics framework.

Y. Shen, G. Fabbris, H. Miao, Y. Cao

Revealing the predominant driving force behind symmetry breaking in correlated materials is sometimes a formidable task due to the intertwined nature of different degrees of freedom. This is the case for La2-xSrxNiO4+{\delta} in which coupled incommensurate charge and spin stripes form at low temperatures. Here, we use resonant X-ray photon correlation spect

Tao Li, Min Soo Choi

There is a growing privacy concern due to the popularity of social media and surveillance systems, along with advances in face recognition software. However, established image obfuscation techniques are either vulnerable to re-identification attacks by human or deep learning models, insufficient in preserving image fidelity, or too computationally intensive

Gabriel Fernandes

We obtain results on the condensation principle called local club condensation. We prove that in extender models an equivalence between the failure of local club condensation and subcompact cardinals holds. This gives a characterization of $\square_{\kappa}$ in terms of local club condensation in extender models. Assuming $\gch$, given an interval of ordinal

Jérôme Williame, Joo-Von Kim

We propose a time-delay oscillator with Mackey-Glass nonlinearity based on a pinned magnetic domain wall in a thin film nanostrip. Through spin transfer torques, electric currents applied along the strip cause the domain wall to deform and displace away from a geometrical pinning site, which can be converted into a nonlinear transfer function through a suita

Youness Azimzade, Abbas Ali Saberi, Robert A. Gatenby

Integrating experimental data into ecological models plays a central role in understanding biological mechanisms that drive tumor progression where such knowledge can be used to develop new therapeutic strategies. While the current studies emphasize the role of competition among tumor cells, they fail to explain recently observed super-linear growth dynamics

Mengxi Li, Alper Canberk, Dylan P. Losey, Dorsa Sadigh

When personal, assistive, and interactive robots make mistakes, humans naturally and intuitively correct those mistakes through physical interaction. In simple situations, one correction is sufficient to convey what the human wants. But when humans are working with multiple robots or the robot is performing an intricate task often the human must make several

Jiyo Palatti, Andrei Aksjonov, Gokhan Alcan, Ville Kyrki

Overtaking is one of the most challenging tasks in driving, and the current solutions to autonomous overtaking are limited to simple and static scenarios. In this paper, we present a method for behaviour and trajectory planning for safe autonomous overtaking. The proposed method optimizes the trajectory by simultaneously enforcing safety and minimizing intru

S. A. Mikhailov

We present a nonperturbative quasi-classical theory of graphene photoconductivity. We consider the influence of low-frequency (microwave, terahertz, mid-infrared) radiation on the static conductivity of a uniform graphene layer and calculate its photoconductivity as a function of frequency, polarization and strength of the external ac electric field, as well

Mehdi Naderi Soorki, Walid Saad, Mehdi Bennis, Choong Seon Hong

In this paper, a novel framework for guaranteeing ultra-reliable millimeter wave (mmW) communications using multiple artificial intelligence (AI)-enabled reconfigurable intelligent surfaces (RISs) is proposed. The use of multiple AI-powered RISs allows changing the propagation direction of the signals transmitted from a mmW access point (AP) thereby improvin

Mostafizur Rahman, Arpan Bhattacharyya

Although the black holes are an integral part of the standard model of astrophysics and cosmology, their existence poses some serious fundamental problems. In recent years, several horizonless compact object models were proposed to address those issues. As the gravitational wave detectors started to observe more and more merger events with a large signal-to-

Khoi Nguyen, Sinisa Todorovic

This paper is about few-shot instance segmentation, where training and test image sets do not share the same object classes. We specify and evaluate a new few-shot anchor-free part-based instance segmenter FAPIS. Our key novelty is in explicit modeling of latent object parts shared across training object classes, which is expected to facilitate our few-shot

Shmuel Friedland

We characterize the infimum of a matrix norm of a square matrix A induced by an absolute norm, over the fields of real and complex numbers. Usually this infimum is greater than the spectral radius of A. If A is sign equivalent to a nonnegative matrix B then this infimum is the spectral radius of B.

Lucien Hardy

The standard operational probabilistic framework (within which we can formulate Operational Quantum Theory) is time asymmetric. This is clear because the conditions on allowed operations are time asymmetric. It is odd, though, because Schoedinger's equation is time symmetric and probability theory does not care about time direction. In this work we provide a

Jorge A. Anaya-Contreras, Arturo Zúñiga-Segundo, D. Sánchez-de-la-Llave, Héctor M. Moya-Cessa

We present an integral of diffraction based on particular eigenfunctions of the Laplacian in two dimensions. We show how to propagate some fields, in particular a Bessel field, a superposition of Airy beams, both over the square root of the radial coordinate, and show how to construct a field that reproduces itself periodically in propagation, i.e., a field

Biagio Ricceri

In this paper, we present a more complete version of the minimax theorem established in [7]. As a consequence, we get, for instance, the following result: Let $X$ be a compact, not singleton subset of a normed space $(E,\|\cdot\|)$ and let $Y$ be a convex subset of $E$ such that $X\subseteq \overline {Y}$. Then, for every convex set $S\subseteq Y$ dense in $

Emilio Ojeda

This thesis extends a previously found relation between the integrable KdV hierarchy and the boundary dynamics of pure gravity on AdS$_3$ described in the highest weight gauge, to a more general class of integrable systems associated to three-dimensional gravity on AdS$_3$ and higher spin gravity with gauge group $SL(N,\mathbb{R})\times SL(N,\mathbb{R})$ in