arXiv papers from September 2019

Xiaoxin Fan, Jian Li, Yini Yang, Zhongqiang Yang

For $a\in [0,+\infty)$, the function space $E_{\geq a}$ ($E_{>a}$; $E_{\leq a}$; $E_{<a}$) of all continuous maps from $[0,1]$ to itself whose topological entropies are larger than or equal to $a$ (larger than $a$; smaller than or equal to $a$; smaller than $a$) with the supremum metric is investigated. It is shown that the spaces $E_{\geq a}$ and $E_{>a}$ a

Xiwei Liu, Zihan Li

In this paper, we studied the finite time anti-synchronization of master-slave coupled complex-valued neural networks (CVNNs) with bounded asynchronous time-varying delays. With the decomposing technique and the generalized $\{\xi,\infty\}$-norm, several criteria for ensuring the finite-time anti-synchronization are obtained. The whole anti-synchronization p

Ali Sadeghian, Shervin Minaee, Ioannis Partalas, Xinxin Li

We propose a neural network architecture for learning vector representations of hotels. Unlike previous works, which typically only use user click information for learning item embeddings, we propose a framework that combines several sources of data, including user clicks, hotel attributes (e.g., property type, star rating, average user rating), amenity info

Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan

We study the complexity of approximating the multimarginal optimal transport (MOT) distance, a generalization of the classical optimal transport distance, considered here between $m$ discrete probability distributions supported each on $n$ support points. First, we show that the standard linear programming (LP) representation of the MOT problem is not a mini

Hailiang Liu, Wumaier Maimaitiyiming

In this paper, we design and analyze second order positive and free energy satisfying schemes for solving diffusion equations with interaction potentials. The semi-discrete scheme is shown to conserve mass, preserve solution positivity, and satisfy a discrete free energy dissipation law for nonuniform meshes. These properties for the fully-discrete scheme (f

Faten S. Alamri, Edward L. Boone, David J. Edwards

Toxicologists are often concerned with determining the dosage to which an individual can be exposed with an acceptable risk of adverse effect. These types of studies have been conducted widely in the past, and many novel approaches have been developed. Parametric techniques utilizing ANOVA and nonlinear regression models are well represented in the literatur

Daiyaan Arfeen, Jesse Zhang

We propose the use of unsupervised learning to train projection networks that project onto the latent space of an already trained generator. We apply our method to a trained StyleGAN, and use our projection network to perform image super-resolution and clustering of images into semantically identifiable groups.

Peter Sheridan Dodds, Joshua R. Minot, Michael V. Arnold, Thayer Alshaabi

When building a global brand of any kind -- a political actor, clothing style, or belief system -- developing widespread awareness is a primary goal. Short of knowing any of the stories or products of a brand, being talked about in whatever fashion -- raw fame -- is, as Oscar Wilde would have it, better than not being talked about at all. Here, we measure, e

José Barrientos, Fabrizio Cordonier-Tello, Cristóbal Corral, Fernando Izaurieta

Scalar-tensor gravity theories with a nonminimal Gauss-Bonnet coupling typically lead to an anomalous propagation speed for gravitational waves, and have therefore been tightly constrained by multimessenger observations such as GW170817/GRB170817A. In this paper we show that this is not a general feature of scalar-tensor theories, but rather a consequence of

André L. G. Mandolesi

The Grassmann angle improves upon similar angles between subspaces that measure volume contraction in orthogonal projections. It works in real or complex spaces, with important differences, and is asymmetric, what makes it more efficient when dimensions are distinct. It can be seen as an angle in Grassmann algebra, being related to its products and those of

Tatsuhiko N. Ikeda, Masahiro Sato

High-harmonic generation (HHG), a typical nonlinear optical effect, has been actively studied in electron systems such as semiconductors and superconductors. As a natural extension, we theoretically study HHG from electric polarization, spin current and magnetization in magnetic insulators under terahertz (THz) or gigahertz (GHz) electromagnetic waves. We us

Venkatraman Gopalan

It is shown that there are 41 types of multivectors representing physical quantitites in non-relativistic physics in arbitrary dimensions within the formalism of Clifford Algebra. The classification is based on the action of three symmetry operations on a general multivector, namely, spatial inversion, time reversal, and a third that is introduced here, wedg

Benjamin J. Dringoli, Ksenia Kolosova, Thomas J. Rademaker, Juliann Wray

We investigate the impact of content sequencing on student learning outcomes in a first-year university electromagnetism course. Using a custom-built online system, the McGill Learning Platform (McLEAP), we test student problem-solving performance as a function of the sequence in which the students are presented aspects of new material. New material was divi

J. Marcus Hughes, Vicki W. Hsu, Daniel B. Seaton, Hazel M. Bain

In order to utilize solar imagery for real-time feature identification and large-scale data science investigations of solar structures, we need maps of the Sun where phenomena, or themes, are labeled. Since solar imagers produce observations every few minutes, it is not feasible to label all images by hand. Here, we compare three machine learning algorithms

Bo Li, Alexander Mook, Aldo Raeliarijaona, Alexey A. Kovalev

We investigate the nonequilibrium spin polarization due to a temperature gradient in antiferromagnetic insulators, which is the magnonic analogue of the inverse spin-galvanic effect of electrons. We derive a linear response theory of a temperature-gradient-induced spin polarization for collinear and noncollinear antiferromagnets, which comprises both extrins

Nicholas L. Adamski, Cyrus E. Dreyer, Chris G. Van de Walle

Rocksalt ScN is a semiconductor with a small lattice mismatch to wurtzite GaN. Within the modern theory of polarization, ScN has a nonvanishing formal polarization along the [111] direction. As a result, we demonstrate that an interface between (0001) GaN and (111) ScN exihibts a large polarization discontinuity of $-$1.358 $\rm Cm^{-2}$. Interfaces between

Mohammadmehdi Ezzatabadipour, Weibin Zhang, Kevin E. Bassler, R. K. P. Zia

Unlike typical phase transitions of first and second order, a system displaying the Thouless effect exhibits characteristics of both at the critical point (jumps in the order parameter and anomalously large fluctuations). An $extreme$ Thousless effect was observed in a recently introduced model of social networks consisting of `introverts and extroverts' ($X

Matthew Kerr

We present an unbinned likelihood analysis formalism employing photon weights -- the probabilities that events are associated with a particular source. This approach is applicable to any photon-resolving instrument, and thus well suited to high-energy observations; we focus here on GeV $\gamma$-ray data from the Fermi Large Area Telescope. Weights connect in

Pooya Moradi, Nishant Kambhatla, Anoop Sarkar

Attention models have become a crucial component in neural machine translation (NMT). They are often implicitly or explicitly used to justify the model's decision in generating a specific token but it has not yet been rigorously established to what extent attention is a reliable source of information in NMT. To evaluate the explanatory power of attention for

Victor Bogdan, Cosmin Bonchiş, Ciprian Orhei

Edge detection is widely and fundamental feature used in various algorithms in computer vision to determine the edges in an image. The edge detection algorithm is used to determine the edges in an image which are further used by various algorithms from line detection to machine learning that can determine objects based on their contour. Inspired by new convo

Alberto Baiardi, Markus Reiher

In the past two decades, the density matrix renormalization group (DMRG) has emerged as an innovative new method in quantum chemistry relying on a theoretical framework very different from that of traditional electronic structure approaches. The development of the quantum chemical DMRG has been remarkably fast: it has already become one of the reference appr

Ioannis Caragiannis, George Christodoulou, Nicos Protopapas

Impartial selection has recently received much attention within the multi-agent systems community. The task is, given a directed graph representing nominations to the members of a community by other members, to select the member with the highest number of nominations. This seemingly trivial goal becomes challenging when there is an additional impartiality co

Johnathan Alsop, Matthew D. Sinclair, Srikant Bharadwaj, Alexandru Dutu

In recent years, machine intelligence (MI) applications have emerged as a major driver for the computing industry. Optimizing these workloads is important but complicated. As memory demands grow and data movement overheads increasingly limit performance, determining the best GPU caching policy to use for a diverse range of MI workloads represents one importa

C. Adams, G. Ambrosi, M. Ambrosio, C. Aramo

The Schwarzschild-Couder Telescope (SCT) is a candidate technology for a medium-sized telescope within the Cherenkov Telescope Array, the next generation ground based observatory for very high energy gamma ray astronomy. The SCT uses a novel two-mirror design and is expected to yield improvements in field of view and image resolution compared to traditional

Kevin Duarte, Yogesh S Rawat, Mubarak Shah

In this work we propose a capsule-based approach for semi-supervised video object segmentation. Current video object segmentation methods are frame-based and often require optical flow to capture temporal consistency across frames which can be difficult to compute. To this end, we propose a video based capsule network, CapsuleVOS, which can segment several f

Dominik Liebl, Matthew Reimherr

Quantifying uncertainty using confidence regions is a central goal of statistical inference. Despite this, methodologies for confidence bands in Functional Data Analysis are still underdeveloped compared to estimation and hypothesis testing. In this work, we present a new methodology for constructing simultaneous confidence bands for functional parameter est

Jonathon Luiten, Tobias Fischer, Bastian Leibe

Object tracking and 3D reconstruction are often performed together, with tracking used as input for reconstruction. However, the obtained reconstructions also provide useful information for improving tracking. We propose a novel method that closes this loop, first tracking to reconstruct, and then reconstructing to track. Our approach, MOTSFusion (Multi-Obje

Miroslav Urbanek, Benjamin Nachman, Wibe A. de Jong

A major milestone of quantum error correction is to achieve the fault-tolerance threshold beyond which quantum computers can be made arbitrarily accurate. This requires extraordinary resources and engineering efforts. We show that even without achieving full fault tolerance, quantum error detection is already useful on the current generation of quantum hardw

Max Bajracharya, James Borders, Dan Helmick, Thomas Kollar

We describe a mobile manipulation hardware and software system capable of autonomously performing complex human-level tasks in real homes, after being taught the task with a single demonstration from a person in virtual reality. This is enabled by a highly capable mobile manipulation robot, whole-body task space hybrid position/force control, teaching of par

Dmitry Kleinbock, Anurag Rao

We study a norm sensitive Diophantine approximation problem arising from the work of Davenport and Schmidt on the improvement of Dirichlet's theorem. Its supremum norm case was recently considered by the first-named author and Wadleigh, and here we extend the set-up by replacing the supremum norm with an arbitrary norm. This gives rise to a class of shrinkin

Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola

This paper introduces Meta-Q-Learning (MQL), a new off-policy algorithm for meta-Reinforcement Learning (meta-RL). MQL builds upon three simple ideas. First, we show that Q-learning is competitive with state-of-the-art meta-RL algorithms if given access to a context variable that is a representation of the past trajectory. Second, a multi-task objective to m

Sabah Al-Fedaghi, MennatAllah Bayoumi

Conceptual modeling is an essential tool in many fields of study, including security specification in information technology systems. As a model, it restricts access to resources and identifies possible threats to the system. We claim that current modeling languages (e.g., Unified Modeling Language, Business Process Model and Notation) lack the notion of gen

D. Kalliecharan, J. S. R. McCoombs, M. M. E. Cormier, B. D. MacNeil

Investigations into the magnetic properties of sputtered Mn$_{x}$CoGe films in the range $0.8 \leq x \leq 2.5$ uncovered ferrimagnetic order, unlike the ferromagnetic order reported in bulk samples. These films formed hexagonal Ni$_{2}$In-type structures when annealed at temperatures below 600$^{\circ}$C. While the Curie temperatures of the films are compara

Sumit R. Das, Shaun Hampton, Sinong Liu

We consider quantum quench in large-N singlet sector quantum mechanics of a single hermitian matrix in the double scaling limit. The time dependent parameter is the self-coupling of the matrix. We find exact classical solutions of the collective field theory of eigenvalue density with abrupt smooth quench profiles which asymptote to constant couplings at ear

Katarzyna Kozdon, Peter Bentley

Maintaining the ability to fire sparsely is crucial for information encoding in neural networks. Additionally, spiking homeostasis is vital for spiking neural networks with changing numbers of weights and neurons. We discuss a range of network stabilisation approaches, inspired by homeostatic synaptic plasticity mechanisms reported in the brain. These includ

Christan Beck, Arnulf Jentzen, Benno Kuckuck

Deep learning algorithms have been applied very successfully in recent years to a range of problems out of reach for classical solution paradigms. Nevertheless, there is no completely rigorous mathematical error and convergence analysis which explains the success of deep learning algorithms. The error of a deep learning algorithm can in many situations be de

Dimitri Bertsekas

We consider finite and infinite horizon dynamic programming problems, where the control at each stage consists of several distinct decisions, each one made by one of several agents. We introduce an approach, whereby at every stage, each agent's decision is made by executing a local rollout algorithm that uses a base policy, together with some coordinating in

Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti

In this paper we prove the existence of a fundamental trade-off between accuracy and robustness in perception-based control, where control decisions rely solely on data-driven, and often incompletely trained, perception maps. In particular, we consider a control problem where the state of the system is estimated from measurements extracted from a high-dimens

Geoff Boeing

Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, propose designs, compare alternatives, and engage the public. Classic urban form visualizations - from Giambattista Nolli's ichnographic maps of Rome to Allan Jacobs's figure-ground diagrams of city streets - have c

G. Bélanger, N. Desai, A. Goudelis, J. Harz

We present a class of dark matter models, in which the dark matter particle is a feebly interacting massive particle (FIMP) produced via the decay of an electrically charged and/or colored parent particle. Given the feeble interaction, dark matter is produced via the freeze-in mechanism and the parent particle is long-lived. The latter leads to interesting c

Yuanlu Xu, Song-Chun Zhu, Tony Tung

We present DenseRaC, a novel end-to-end framework for jointly estimating 3D human pose and body shape from a monocular RGB image. Our two-step framework takes the body pixel-to-surface correspondence map (i.e., IUV map) as proxy representation and then performs estimation of parameterized human pose and shape. Specifically, given an estimated IUV map, we dev

Tuomo Valkonen

We provide an overview of primal-dual algorithms for nonsmooth and non-convex-concave saddle-point problems. This flows around a new analysis of such methods, using Bregman divergences to formulate simplified conditions for convergence.

Yang He, Jingwei Ling, Mingxiao Li, Qiang Lin

Recent advance of soliton microcombs has shown great promise to revolutionize many important areas such as optical communication, spectroscopic sensing, optical clock, and frequency synthesis. A largely tunable comb line spacing is crucial for the practical application of soliton microcombs, which unfortunately is challenging to realize for an on-chip monoli

Chinmay Khandekar, Liping Yang, Alejandro W. Rodriguez, Zubin Jacob

Nearly all thermal radiation phenomena involving materials with linear response can be accurately described via semi-classical theories of light. Here, we go beyond these traditional paradigms to study a nonlinear system which, as we show, necessarily requires quantum theory of damping. Specifically, we analyze thermal radiation from a resonant system contai

S. Aiello, F. Ameli, M. Andre, G. Androulakis

The KM3NeT Collaboration runs a multi-site neutrino observatory in the Mediterranean Sea. Water Cherenkov particle detectors, deep in the sea and far off the coasts of France and Italy, are already taking data while incremental construction progresses. Data Acquisition Control software is operating off-shore detectors as well as testing and qualification sta

Andrew J. Lohn

Given that individual defenses are rarely sufficient, defense-in-depth is nearly universal and options for individual defensive layers abound. We develop a simple mathematical theory that can help in selecting the type and quantity of defenses for two different defense-in-depth strategies: Blockade and Delay. This theoretical approach accounts for budgetary

Zlatko Drmač, Benjamin Peherstorfer

Loewner rational interpolation provides a versatile tool to learn low-dimensional dynamical-system models from frequency-response measurements. This work investigates the robustness of the Loewner approach to noise. The key finding is that if the measurements are polluted with Gaussian noise, then the error due to noise grows at most linearly with the standa

Arseniy Sheydvasser

An Ulam sequence U(1,n) is defined as the sequence starting with integers 1,n such that n > 1, and such that every subsequent term is the smallest integer that can be written as the sum of distinct previous terms in exactly one way. This family of sequences is notable for being the subject of several remarkable rigidity conjectures. We introduce an analogous

Tixian Wang, Amirhossein Taghvaei, Prashant G. Mehta

This paper presents a Q-learning framework for learning optimal locomotion gaits in robotic systems modeled as coupled rigid bodies. Inspired by prevalence of periodic gaits in bio-locomotion, an open loop periodic input is assumed to (say) affect a nominal gait. The learning problem is to learn a new (modified) gait by using only partial noisy measurements

Joe T. Rexwinkle, Gregory Lieberman, Matthew Jaswa, Brent J. Lance

Brain-computer interfaces (BCIs) have the potential to significantly change the ways in which humans interact with technology, the environment, and even each other. Unfortunately, BCI technologies are seldom robust enough for use in real-world applications, in part due to the large amount of data that must be collected, processed, and classified in order to

Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao

We study the question of how to imitate tasks across domains with discrepancies such as embodiment, viewpoint, and dynamics mismatch. Many prior works require paired, aligned demonstrations and an additional RL step that requires environment interactions. However, paired, aligned demonstrations are seldom obtainable and RL procedures are expensive. We formal

Victor Kalvin

We present and prove Polyakov-Alvarez type comparison formulas for the determinants of Friederichs extensions of Laplacians corresponding to conformally equivalent metrics on a compact Riemann surface with conical singularities. In particular, we find how the determinants depend on the orders of conical singularities. We also illustrate these general results

Lin Zhang, Andrew DiLernia, Karina Quevedo, Jazmin Camchong

This paper considers a novel problem, bi-level graphical modeling, in which multiple individual graphical models can be considered as variants of a common group-level graphical model and inference of both the group- and individual-level graphical models are of interest. Such problem arises from many applications including multi-subject neuroimaging and genom

Adal Sabri, Xinran Xu, Diego Krapf, Matthias Weiss

Diffusion of tracer particles in the cytoplasm of mammalian cells is often anomalous with a marked heterogeneity even within individual particle trajectories. Despite considerable efforts, the mechanisms behind these observations have remained largely elusive. To tackle this problem, we performed extensive single-particle tracking experiments on quantum dots

Thomas Brihaye, Gilles Geeraerts, Marion Hallet, Benjamin Monmege

We consider multi-player games played on graphs, in which the players aim at fulfilling their own (not necessarily antagonistic) objectives. In the spirit of evolutionary game theory, we suppose that the players have the right to repeatedly update their respective strategies (for instance, to improve the outcome w.r.t. the current strategy profile). This gen

Felix Grimminger, Avadesh Meduri, Majid Khadiv, Julian Viereck

We present a new open-source torque-controlled legged robot system, with a low-cost and low-complexity actuator module at its core. It consists of a high-torque brushless DC motor and a low-gear-ratio transmission suitable for impedance and force control. We also present a novel foot contact sensor suitable for legged locomotion with hard impacts. A 2.2 kg q

Jiayi Zhang, Emil Björnson, Michail Matthaiou, Derrick Wing Kwan Ng

Multiple antenna technologies have attracted large research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are used. Now that multiple antenna

Howard Baer, Vernon Barger, Dibyashree Sengupta

In a fertile patch of the string landscape which includes the Minimal Supersymmetric Standard Model (MSSM) as the low energy effective theory, rather general arguments from Douglas suggest a power-law statistical selection of soft breaking terms (m(soft)^n where n=2n_F+n_D-1 with n_F the number of hidden sector F-SUSY breaking fields and n_D the number of D-

HanYi Wang

Understanding the behavior of fluid-driven hydraulic fracture in naturally fractured reservoirs is crucial in the development of geothermal energy and unconventional reservoirs. This study presents a fully-coupled numerical model to investigate hydraulic propagation in naturally fractured reservoirs, along with a comprehensive discussion on field observation

Robion Kirby, Abigail Thompson

We examine questions about surgery on links which arise naturally from the trisection decomposition of 4-manifolds developed by Gay and Kirby. These links lie on Heegaard surfaces in $\#^j S^1 \times S^2$ and have surgeries yielding $\#^k S^1 \times S^2$. We describe families of links which have such surgeries. One can ask whether all links with such surgeri

Hailiang Liu, Peimeng Yin

A novel discontinuous Galerkin (DG) method is developed to solve time-dependent bi-harmonic type equations involving fourth derivatives in one and multiple space dimensions. We present the spatial DG discretization based on a mixed formulation and central interface numerical fluxes so that the resulting semi-discrete schemes are $L^2$ stable even without int

Gengchen Mai, Krzysztof Janowicz, Bo Yan, Rui Zhu

Recently, several studies have explored methods for using KG embedding to answer logical queries. These approaches either treat embedding learning and query answering as two separated learning tasks, or fail to deal with the variability of contributions from different query paths. We proposed to leverage a graph attention mechanism to handle the unequal cont

A. S. Ribeiro, F. N. Lima

In this paper, we consider a spherically curved symmetric spacetime to exact solving the orbit equation of a massive particle by using Jacobi's elliptic functions. Generally, the solution of the orbit equation provides the relativistic effects on the massive particle, absents in Newtonian mechanics. Besides, we investigate the additional physical information

Marco Centini, Maria Cristina Larciprete, Roberto Li Voti, Mario Bertolotti

We investigate the possibility of spatially and spectrally controlling the thermal infrared emission by exploitation of the Yagi-Uda antenna design. Hybrid antennas composed of both SiC and Au rods are considered and the contributions of emission from all the elements, at a given equilibrium temperature, are taken into account. We show that the detrimental e

Benito Hernández-Bermejo

A new family of solutions of the Jacobi partial differential equations for finite-dimensional Poisson systems is investigated. This family is mathematically remarkable, as the functional dependences of the solutions appear to be associated to the distinguished invariants of the solutions themselves. This kind of Poisson structure (termed distinguished soluti

Nitant Upasani, Krishnendra Shekhawat, Garv Sachdeva

This paper proposes a methodology for the automated construction of rectangular floorplans (RFPs) while addressing dimensional constraints and adjacency relations. Here, adjacency relations are taken in the form of a dimensionless rectangular arrangement (RA) ensuring the existence of a RFP, while dimensional constraints are given in terms of minimum width a

Jean Schneider

The NASA mission Kepler has detected 28 transits with depths and durations hours in the light curve of HD139139 during a 87 days campaign . Their arrival times are erratic. Rappaport et al. (2019) discard ten explanations. It is not clear if the transits are for HD 139139 or for a star B at 3.3 arcsec. New radial velocity variation data give RV for HD139139

Alison Sills, Emanuele Dalessandro, Mario Cadelano, Mayte Alfaro-Cuello

The cluster M54 lies at the centre of the Sagittarius dwarf spheroidal galaxy, and therefore may be the closest example of a nuclear star cluster. Either in-situ star formation, inspiralling globular clusters, or a combination have been invoked to explain the wide variety of stellar sub-populations in nuclear star clusters. Globular clusters are known to exh

CMS Collaboration

Methods are presented for calibrating the hadron calorimeter system of the CMS detector at the LHC. The hadron calorimeters of the CMS experiment are sampling calorimeters of brass and scintillator, and are in the form of one central detector and two endcaps. These calorimeters cover pseudorapidities $|\eta| <$ 3 and are positioned inside a solenoidal magnet

Jehandad Khan, Paul Fultz, Artem Tamazov, Daniel Lowell

Deep Learning has established itself to be a common occurrence in the business lexicon. The unprecedented success of deep learning in recent years can be attributed to: abundance of data, availability of gargantuan compute capabilities offered by GPUs, and adoption of open-source philosophy by the researchers and industry. Deep neural networks can be decompo

Linda Forster, Anthony B. Davis, David J. Diner, Bernhard Mayer

For passive satellite imagers, current retrievals of cloud optical thickness and effective particle size fail for convective clouds with 3D morphology. Indeed, being based on 1D radiative transfer (RT) theory, they work well only for horizontally homogeneous clouds. A promising approach for treating clouds as fully 3D objects is cloud tomography, and this ha

Natasha E. Batalha, Taylor Lewis, Jonathan J. Fortney, Natalie M. Batalha

Two of TESS's major science goals are to measure masses for 50 planets smaller than 4 Earth radii and to discover high-quality targets for atmospheric characterization efforts. It is important that these two goals are linked by quantifying what precision of mass constraint is required to yield robust atmospheric properties of planets. Here, we address this b

K. C. Erb, J. Hlinka

The 212 species of structural phase transitions which break macroscopic symmetry are analyzed with respect to the occurrence of time-reversal invariant vector and bidirector order parameters. The possibility of discerning the orientational domain states of the low-symmetry phase by these `vectorlike' physical properties has been derived using a computer algo

Jiří Chaloupka, Giniyat Khaliullin

We study the orbitally frustrated singlet-triplet models that emerge in the context of spin-orbit coupled Mott insulators with $t_{2g}^4$ electronic configuration. In these compounds, low-energy magnetic degrees of freedom can be cast in terms of three-flavor "triplon" operators describing the transitions between spin-orbit entangled $J=0$ ionic ground state

Consuelo Nava, Maria Grazia Zoia

Price indexes in time and space is a most relevant topic in statistical analysis from both the methodological and the application side. In this paper a price index providing a novel and effective solution to price indexes over several periods and among several countries, that is in both a multi-period and a multilateral framework, is devised. The reference b

Irina Grigorescu, Lucilio Cordero-Grande, A David Edwards, Jo Hajnal

The use of convolutional neural networks (CNNs) for classification tasks has become dominant in various medical imaging applications. At the same time, recent advances in interpretable machine learning techniques have shown great potential in explaining classifiers' decisions. Layer-wise relevance propagation (LRP) has been introduced as one of these novel m

Piotr T. Chruściel, Gregory J. Galloway, Yohan Potaux

We show that Wang's proof of uniqueness of Anti-de Sitter spacetime can be adapted to provide uniqueness results for strictly static asymptotically locally hyperbolic vacuum metrics with toroidal infinity, and to prove negativity of the free energy $E-TS$ of asymptotically AdS black holes with higher-genus horizons.

Simone Rusconi, Denys Dutykh, Arghir Zarnescu, Dmitri Sokolovski

In modelling of chemical, physical or biological systems it may occur that the coefficients, multiplying various terms in the equation of interest, differ greatly in magnitude, if a particular system of units is used. Such is, for instance, the case of the Population Balance Equations (PBE) proposed to model the Latex Particles Morphology formation. The obvi

Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt

Variational inference has become one of the most widely used methods in latent variable modeling. In its basic form, variational inference employs a fully factorized variational distribution and minimizes its KL divergence to the posterior. As the minimization can only be carried out approximately, this approximation induces a bias. In this paper, we revisit

Aniruddha Saha, Akshayvarun Subramanya, Koninika Patil, Hamed Pirsiavash

The benefits of utilizing spatial context in fast object detection algorithms have been studied extensively. Detectors increase inference speed by doing a single forward pass per image which means they implicitly use contextual reasoning for their predictions. However, one can show that an adversary can design adversarial patches which do not overlap with an

Cory Stephenson, Gokce Keskin, Anil Thomas, Oguz H. Elibol

In this work we introduce a semi-supervised approach to the voice conversion problem, in which speech from a source speaker is converted into speech of a target speaker. The proposed method makes use of both parallel and non-parallel utterances from the source and target simultaneously during training. This approach can be used to extend existing parallel da

Ruhi Shah, Jonathan Gorard

This paper introduces a new formalism for quantum cellular automata (QCAs), based on evolving tensor products of qubits using local unitary operators. It subsequently uses this formalism to analyze and validate several conjectures, stemming from a formal analogy between quantum computational complexity theory and classical thermodynamics, that have arisen re

Pierre Pizzochero, Alessandro Montoli, Marco Antonelli

During the spin-up phase of a large pulsar glitch - a sudden decrease of the rotational period of a neutron star - the angular velocity of the star may overshoot, namely reach values greater than that observed for the new post-glitch equilibrium. These transient phenomena are expected on the basis of theoretical models for pulsar internal dynamics and their

Jekaterina Novikova, Aparna Balagopalan, Ksenia Shkaruta, Frank Rudzicz

Understanding the vulnerability of linguistic features extracted from noisy text is important for both developing better health text classification models and for interpreting vulnerabilities of natural language models. In this paper, we investigate how generic language characteristics, such as syntax or the lexicon, are impacted by artificial text alteratio

Mutaz Y. Melhem, Laszlo B. Kish

A new attack against the Kirchhoff Law Johnson Noise (KLJN) secure key distribution system is studied with unknown parasitic DC voltage sources at both Alices and Bobs ends. This paper is the generalization of our earlier investigation with a single end parasitic source. Under the assumption that Eve does not know the values of the parasitic sources, a new a

Shawkat Sabah Khairullah

Digital Embedded Devices of next-generation safety-critical industrial automation systems require high levels of survivability and resilience against the hardware and software failure. One of the concepts for achieving this requirement is the design of resilient and survivable digital embedded systems. In the last two decades, development of self-healing dig

Daniel T. Larsson, Dipankar Maity, Panagiotis Tsiotras

In this paper, we develop a framework to obtain graph abstractions for decision-making by an agent where the abstractions emerge as a function of the agent's limited computational resources. We discuss the connection of the proposed approach with information-theoretic signal compression, and formulate a novel optimization problem to obtain tree-based abstrac

Maxine Calle, Sam Ginnett, Harry Chen, Xinling Chen

This paper explores the Tambara functor structure of the trace ideal of a Galois extension. In the case of a (pro-)cyclic extension, we are able to explicitly determine the generators of the ideal. Furthermore, we show that the absolute trace ideal of a cyclic group is strongly principal when viewed as an ideal of the Burnside Tambara Functor. Applying our r

Georgi Nalbantov, Svetoslav Ivanov

Implied posterior probability of a given model (say, Support Vector Machines (SVM)) at a point $\bf{x}$ is an estimate of the class posterior probability pertaining to the class of functions of the model applied to a given dataset. It can be regarded as a score (or estimate) for the true posterior probability, which can then be calibrated/mapped onto expecte

Vedant Bhatia, Prateek Rawat, Ajit Kumar, Rajiv Ratn Shah

The ever-increasing number of applications to job positions presents a challenge for employers to find suitable candidates manually. We present an end-to-end solution for ranking candidates based on their suitability to a job description. We accomplish this in two stages. First, we build a resume parser which extracts complete information from candidate resu

Edlyn V. Levine, Matthew J. Turner, Pauli Kehayias, Connor A. Hart

We provide an overview of the experimental techniques, measurement modalities, and diverse applications of the Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) color centers near the surface of a transparent diamond chip on which a sample of interest is placed. NV electronic spins are coherently probed with

Pan Li, Alexander Tuzhilin

In this paper, we propose a novel model RevGAN that automatically generates controllable and personalized user reviews based on the arbitrarily given sentimental and stylistic information. RevGAN utilizes the combination of three novel components, including self-attentive recursive autoencoders, conditional discriminators, and personalized decoders. We test

Jiguang He, Henk Wymeersch, Long Kong, Olli Silvén

Millimeter-wave (mmWave) multiple-input multiple-output (MIMO) system for the fifth generation (5G) cellular communications can also enable single-anchor positioning and object tracking due to its large bandwidth and inherently high angular resolution. In this paper, we introduce the newly invented concept, large intelligent surface (LIS), to mmWave position

Alexandre Kirilov, Wagner Augusto Almeida de Moraes, Michael Ruzhansky

We present necessary and sufficient conditions to have global hypoellipticity and global solvability for a class of vector fields defined on a product of compact Lie groups. In view of Greenfield's and Wallach's conjecture, about the non-existence of globally hypoelliptic vector fields on compact manifolds different from tori, we also investigate different n

Po-Yao Huang, Xiaojun Chang, Alexander Hauptmann

With the aim of promoting and understanding the multilingual version of image search, we leverage visual object detection and propose a model with diverse multi-head attention to learn grounded multilingual multimodal representations. Specifically, our model attends to different types of textual semantics in two languages and visual objects for fine-grained

Goutham Ramakrishnan, Yun Chan Lee, Aws Albarghouthi

When a model makes a consequential decision, e.g., denying someone a loan, it needs to additionally generate actionable, realistic feedback on what the person can do to favorably change the decision. We cast this problem through the lens of program synthesis, in which our goal is to synthesize an optimal (realistically cheapest or simplest) sequence of actio

Sadegh M. Milajerdi, Birhanu Eshete, Rigel Gjomemo, V. N. Venkatakrishnan

Cyber threat intelligence (CTI) is being used to search for indicators of attacks that might have compromised an enterprise network for a long time without being discovered. To have a more effective analysis, CTI open standards have incorporated descriptive relationships showing how the indicators or observables are related to each other. However, these rela

Uri Alon, Roy Sadaka, Omer Levy, Eran Yahav

We address the problem of any-code completion - generating a missing piece of source code in a given program without any restriction on the vocabulary or structure. We introduce a new approach to any-code completion that leverages the strict syntax of programming languages to model a code snippet as a tree - structural language modeling (SLM). SLM estimates

Kalpana Biswas, Jyoti Prasad Saha, Pinaki Patra

Noncommutivity of position and momentum makes it difficult to formulate the unambiguous structure of the kinetic part of Hamiltonian for the position-dependent effective mass (PDEM). Various existing proposals of writing the viable kinetic part of the Hamiltonian for PDEM, conceptually lack from first principle calculation. Starting from the first principle

Morgan André, Léo Planche

We consider a continuous-time stochastic model of spiking neurons. In this model, we have a finite or countable number of neurons which are vertices in some graph $G$ where the edges indicate the synaptic connection between them. We focus on metastability, understood as the property for the time of extinction of the network to be asymptotically memory-less,