October 2022 arXiv papers — page 31

Martin Groenewegen

(abridged)Multiple systems for which the astrometric and spectroscopic orbit are known offer the unique possibility of determining the distance to these systems directly without any assumptions. They are therefore ideal objects for a comparison of Gaia data release 3 (GDR3) parallax data, especially since GDR3 presents the results of the non-single star (NSS

Patrick Ingram, David Jaramillo-Martinez, Jorge Mello

Let f_t be a meromorphic family of endomorphisms of P^N_C of degree at least 2, and let L(f_t) be the sum of Lyapunov exponents associated to f_t. Favre showed that L(f_t)=L(f)\log|t^{-1}|+o(\log|t^{-1}|) as t -> 0, where L(f) is the sum of Lyapunov exponents on the generic fibre, interpreted as an endomorphism of some projective Berkovich space. Under some

Miguel Á. Berbel, Marco Castrillón López

Given a Hamiltonian system on a fiber bundle, there is a Poisson covariant formulation of the Hamilton equations. When a Lie group G acts freely, properly, preserving the fibers of the bundle and the Hamiltonian density is G-invariant, we study the reduction of this formulation to obtain an analogue of Poisson-Poincar\'e reduction for field theories. This pr

Gabriel Margiani, Javier del Pino, Toni L. Heugel, Nicholas E. Bousse

The vision of building computational hardware for problem optimization has spurred large efforts in the physics community. In particular, networks of Kerr parametric oscillators (KPOs) are envisioned as simulators for finding the ground states of Ising Hamiltonians. It was shown, however, that KPO networks can feature large numbers of unexpected solutions th

Ben Kenwright

An effective 3D stepping control algorithm that is computationally fast, robust, and easy to implement is extremely important and valuable to character animation research. In this paper, we present a novel technique for generating dynamic, interactive, and controllable biped stepping motions. Our approach uses a low-dimensional physics-based model to create

Shunya Adachi

We study the unitarity of monodromies of rank two Fuchsian systems of SL type with $(n+1)$ regular singularities on the Riemann sphere, namely, we give a sufficient and necessary condition for the monodromy group to be conjugate to a subgroup of a special unitary group $\mathrm{SU}(p,q)$. When $n\ge 3$, the moduli space of irreducible monodromies can be real

Samaneh Jozashoori, Enrique Iglesias, Maria-Esther Vidal

In recent years, there have been valuable efforts and contributions to make the process of RDF knowledge graph creation traceable and transparent; extending and applying declarative mapping languages is an example. One challenging step is the traceability of procedures that aim to overcome interoperability issues, a.k.a. data-level integration. In most pipel

Sören Dörscher, Joshua Klose, Sarath Maratha Palli, Christian Lisdat

To operate an optical lattice clock at a fractional uncertainty below $10^{-17}$, one must typically consider not only electric-dipole (E1) interaction between an atom and the lattice light field when characterizing the resulting lattice light shift of the clock transition but also higher-order multipole contributions, such as electric-quadrupole (E2) and ma

Yusuke Kawamoto

The main theme of this paper is to use toric degeneration to produce distinct homogeneous quasimorphisms on the group of Hamiltonian diffeomorphisms. We focus on the (complex $n$-dimensional) quadric hypersurface and the del Pezzo surfaces, and study two classes of distinguished Lagrangian submanifolds that appear naturally in a toric degeneration, namely th

Anirudh Pradhan, Gopikant Goswami, Rita Rani, Aroonkumar Beesham

We attempt to construct a Friedmann-Lemaitre-Robertson-Walker(FLRW) cosmological model in $f(R, T)$ gravity which exhibits a phase transition from deceleration to acceleration at present. We take $f(R,T) = R + 2 \lambda T$, $\lambda$ being an arbitrary constant. In our model, the $\lambda$ parameter develops a negative pressure in the universe whose Equation

Evripidis Bampis, Bruno Escoffier, Niklas Hahn, Michalis Xefteris

In this paper, we consider the Online Traveling Salesperson Problem (OLTSP) where the locations of the requests are known in advance, but not their arrival times. We study both the open variant, in which the algorithm is not required to return to the origin when all the requests are served, as well as the closed variant, in which the algorithm has to return

Zunwei Fu, Xianming Hou, Qingyan Wu

In this paper, we introduce the fractional Fourier series on the fractional torus and study some basic facts of fractional Fourier series, such as fractional convolution and fractional approximation. Meanwhile, fractional Fourier inversion and Poisson summation formula are also given. We further discuss the relationship between the decay of fractional Fourie

Davide Gambino, Johan Klarbring, Björn Alling

The calculation of free energies from first principles in materials is a formidable task which enables the prediction of phase stability with high accuracy; these calculations are complicated in magnetic materials by the interplay of electronic, magnetic, and vibrational degrees of freedom. In this work, we show the feasibility and accuracy of the calculatio

Antoine Boniface, Florian Maitre, Jorge Madrid-Wolff, Christophe Moser

3D printing has revolutionized the manufacturing of volumetric components and structures for various fields. Thanks to the advent of photocurable resins, several fully volumetric light-based techniques have been recently developed to overcome the current limitations of 3D printing. Although fast, this new generation of printers cannot fabricate objects whose

Marcelo Matheus Gauy, Marcelo Finger

The goal of speech emotion recognition (SER) is to identify the emotional aspects of speech. The SER challenge for Brazilian Portuguese speech was proposed with short snippets of Portuguese which are classified as neutral, non-neutral female and non-neutral male according to paralinguistic elements (laughing, crying, etc). This dataset contains about $50$ mi

Laura Caputo, Viet-Hung Nguyen, Jean-Christophe Charlier

Since advanced Silicon-based device components are moderately chemically tunable, doped graphene has emerged as a promising candidate to replace this semiconducting material in flexible miniaturized electronic devices. Indeed, heteroatom co-doping (i.e. with boron and/or nitrogen) is an appealing strategy to tune both its structural and electronic properties

Nada Osman, Guglielmo Camporese, Lamberto Ballan

Human intention prediction is a growing area of research where an activity in a video has to be anticipated by a vision-based system. To this end, the model creates a representation of the past, and subsequently, it produces future hypotheses about upcoming scenarios. In this work, we focus on pedestrians' early intention prediction in which, from a current

Jeyhan S. Kartaltepe, Caitlin Rose, Brittany N. Vanderhoof, Elizabeth J. McGrath

We present a comprehensive analysis of the evolution of the morphological and structural properties of a large sample of galaxies at z=3-9 using early JWST CEERS NIRCam observations. Our sample consists of 850 galaxies at z>3 detected in both CANDELS HST imaging and JWST CEERS NIRCam images to enable a comparison of HST and JWST morphologies. Our team conduc

Colin Leong, Joshua Nemecek, Jacob Mansdorfer, Anna Filighera

We present Bloom Library, a linguistically diverse set of multimodal and multilingual datasets for language modeling, image captioning, visual storytelling, and speech synthesis/recognition. These datasets represent either the most, or among the most, multilingual datasets for each of the included downstream tasks. In total, the initial release of the Bloom

Shoichi Koyama, Kazuyuki Arikawa

A sound field reproduction method called weighted pressure matching is proposed. Sound field reproduction is aimed at synthesizing the desired sound field using multiple loudspeakers inside a target region. Optimization-based methods are derived from the minimization of errors between synthesized and desired sound fields, which enable the use of an arbitrary

Pierre Berger, Dmitry Turaev

We prove that analytic Hamiltonian dynamics on tori, annuli, or Euclidean space can be approximated by a composition of nonlinear shear maps where each of the shears depends only on the position or only on the momentum.

Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan

This paper studies learning on text-attributed graphs (TAGs), where each node is associated with a text description. An ideal solution for such a problem would be integrating both the text and graph structure information with large language models and graph neural networks (GNNs). However, the problem becomes very challenging when graphs are large due to the

Sandeep Dalal, Sanjay Mukherjee, Kamal Lochan Patra

For a finite group $G$, let $B$ be an equivalence (equality, conjugacy or order) relation on $G$ and let $A$ be a (power, enhanced power or commuting) graph with vertex set $G$. The $B$ super $A$ graph is a simple graph with vertex set $G$ and two vertices are adjacent if either they are in the same $B$-equivalence class or there are elements in their $B$-eq

Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic

Analytics of financial data is inherently a Big Data paradigm, as such data are collected over many assets, asset classes, countries, and time periods. This represents a challenge for modern machine learning models, as the number of model parameters needed to process such data grows exponentially with the data dimensions; an effect known as the Curse-of-Dime

Luca Beurer-Kellner, Martin Vechev, Laurent Vanbever, Petar Veličković

We present a new method for scaling automatic configuration of computer networks. The key idea is to relax the computationally hard search problem of finding a configuration that satisfies a given specification into an approximate objective amenable to learning-based techniques. Based on this idea, we train a neural algorithmic model which learns to generate

Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong

Supervised learning aims to train a classifier under the assumption that training and test data are from the same distribution. To ease the above assumption, researchers have studied a more realistic setting: out-of-distribution (OOD) detection, where test data may come from classes that are unknown during training (i.e., OOD data). Due to the unavailability

Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski

Discovering causal relationships between different variables from time series data has been a long-standing challenge for many domains such as climate science, finance, and healthcare. Given the complexity of real-world relationships and the nature of observations in discrete time, causal discovery methods need to consider non-linear relations between variab

Davide De Biasio, Julian Freigang, Dieter Lust, Toby Wiseman

Ricci flow is a natural gradient flow of the Einstein-Hilbert action. Here we consider the analog for the Einstein-Maxwell action, which gives Ricci flow with a stress tensor contribution coupled to a Yang-Mills flow for the Maxwell field. We argue that this flow is well-posed for static spacetimes with pure electric or magnetic potentialsand show it preserv

Diego Ulisse Pizzagalli, Ilaria Arini, Mauro Prevostini

Educational robots allow experimenting with a variety of principles from mechanics, electronics, and informatics. Here we propose ClipBot, a low-cost, do-it-yourself, robot whose skeleton is made of two paper clips. An Arduino nano microcontroller actuates two servo motors that move the paper clips. However, such mechanical configuration confers physical imp

Tingfeng Yu, James Henderson, Alwen Tiu, Thomas Haines

We present a detailed privacy analysis of Samsung's Offline Finding (OF) protocol, which is part of Samsung's Find My Mobile (FMM) location tracking system for locating Samsung mobile devices, such as Samsung smartphones and Bluetooth trackers (Galaxy SmartTags). The OF protocol uses Bluetooth Low Energy (BLE) to broadcast a unique beacon for a lost device.

Duong Nguyen Nguyen, Min-Cheol Kim, Unbeom Baeck, Jaehyoung Lim

Development of cost-effective hydrogen evolution reaction (HER) catalysts with outstanding catalytic activity, replacing cost-prohibitive noble metal-based catalysts, is critical for practical green hydrogen production. A popular strategy for promoting the catalytic performance of noble metal-free catalysts is to incorporate earth-abundant transition metal (

Xiumei Deng, Jun Li, Chuan Ma, Kang Wei

Federated Learning (FL) empowers Industrial Internet of Things (IIoT) with distributed intelligence of industrial automation thanks to its capability of distributed machine learning without any raw data exchange. However, it is rather challenging for lightweight IIoT devices to perform computation-intensive local model training over large-scale deep neural n

Jean-Baptiste Döderlein, Nguessan Hermann Kouadio, Mathieu Acher, Djamel Eddine Khelladi

Language models are promising solutions for tackling increasing complex problems. In software engineering, they recently gained attention in code assistants, which generate programs from a natural language task description (prompt). They have the potential to save time and effort but remain poorly understood, limiting their optimal use. In this article, we i

Tianyu Liu, Yuchen Jiang, Nicholas Monath, Ryan Cotterell

Recent years have seen a paradigm shift in NLP towards using pretrained language models ({PLM}) for a wide range of tasks. However, there are many difficult design decisions to represent structures (e.g. tagged text, coreference chains) in a way such that they can be captured by PLMs. Prior work on structured prediction with PLMs typically flattens the struc

Leonardo A. Perez Ramirez, Gianluca Rizzi, Angela Madeo

Exploring the dynamical response of mechanical metamaterials has gathered increasing attention in the last decades, enabling the design of microstructures exotically interacting with elastic waves (focusing, channeling, band-gaps, negative refraction, cloaking, and many more). Yet, the application and use of such metamaterials in engineering practice is stil

Gökhan Öztarhan, E. Bulut Kul, Emre Okcu, A. D. Güçlü

Semiconductor artificial graphene nanostructures where Hubbard model parameter $U/t$ can be of the order of 100, provide a highly controllable platform to study strongly correlated quantum many-particle phases. We use accurate variational and diffusion Monte Carlo methods to demonstrate a transition from antiferromagnetic to metallic phases for experimentall

Jin Yan, Christian Beck

Recent mathematical investigations have shown that under very general conditions exponential mixing implies the Bernoulli property. As a concrete example of a statistical mechanics which is exponentially mixing we consider a Bernoulli shift dynamics by Chebyshev maps of arbitrary order $N\geq 2$, which maximizes Tsallis $q=3$ entropy rather than the ordinary

Péter Kevei, Kata Kubatovics

We investigate Galton--Watson processes in varying environment, for which $\bar f_n \uparrow 1$ and $\sum_{n=1}^\infty (1-\bar f_n) = \infty$, where $\bar f_n$ stands for the offspring mean in generation $n$. Since the process dies out almost surely, to obtain nontrivial limit we consider two scenarios: conditioning on non-extinction, or adding immigration.

K. Castillo

It is proved that $$\left(\frac{x^n}{1-e^{-x}}\right)^{(n)}>0$$ for all $x\in (\log 2, \infty)$ and $n\in \mathbb{N}$, which improves the result of [Al-Musallam and Bustoz in Ramanujan J. 11 (2006) 399-402].

Yee Ching Tok, Sudipta Chattopadhyay

Technological advances have enabled multiple countries to consider implementing Smart City Infrastructure to provide in-depth insights into different data points and enhance the lives of citizens. Unfortunately, these new technological implementations also entice adversaries and cybercriminals to execute cyber-attacks and commit criminal acts on these modern

Wei Wang, Chao Zhang, Xiaopei Wu

Code-Switching refers to the phenomenon of switching languages within a sentence or discourse. However, limited code-switching , different language phoneme-sets and high rebuilding costs throw a challenge to make the specialized acoustic model for code-switching speech recognition. In this paper, we make use of limited code-switching data as driving material

Y. Jin, P. Cristaudo, A. Gabrielli

Single-crystal synthetic diamond sensors have been widely used in radiation dosimetry and beam diagnostics. The foreseen harsh radiation environment in electron-positron colliders at the luminosity frontier requires a thorough investigation of diamond's response to large radiation burst, in particular, to intense high-energy electron pulses. In this article,

Cindy Tsang

We determine the finite non-abelian simple groups which occur as the type of a Hopf-Galois structure on a solvable extension. In the language of skew braces, our result gives a complete list of finite non-abelian simple groups which occur as the additive group of a skew brace with solvable multiplicative group.

Ziyue Wang, Ya-Feng Liu, Zhaorui Wang, Wei Yu

This paper studies the covariance based activity detection problem in a multi-cell massive multiple-input multiple-output (MIMO) system, where the active devices transmit their signature sequences to multiple base stations (BSs), and the BSs cooperatively detect the active devices based on the received signals. The scaling law of covariance based activity de

Gonzalo Nápoles, Isel Grau, Çiçek Güven, Orçun Özdemir

In this paper, we tackle the problem of selecting the optimal model for a given structured pattern classification dataset. In this context, a model can be understood as a classifier and a hyperparameter configuration. The proposed meta-learning approach purely relies on machine learning and involves four major steps. Firstly, we present a concise collection

Bin Cheng, Yuezu Lv, Zhongkui Li, Zhisheng Duan

This paper studies the consensus control problem faced with three essential demands, namely, discrete control updating for each agent, discrete-time communications among neighboring agents, and the fully distributed fashion of the controller implementation without requiring any global information of the whole network topology. Noting that the existing relate

Narima Eerqing, Hsin-Yu Wu, Sivaraman Subramanian, Serge Vincent

Observing the hybridisation kinetics of DNA probes immobilised on plasmonic nanoparticles is key in plamon enhanced fluorescence detection from weak emitting species, and refractive index based single-molecule detection on optoplasmonic sensors. The role of the local field in providing plasmonic signal enhancements for single-molecule detection has been stud

Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause

Demonstrations provide insight into relevant state or action space regions, bearing great potential to boost the efficiency and practicality of reinforcement learning agents. In this work, we propose to leverage demonstration datasets by combining skill learning and sequence modeling. Starting with a learned joint latent space, we separately train a generati

Anna Wigren, Johan Wågberg, Fredrik Lindsten, Adrian Wills

Identification of nonlinear systems is a challenging problem. Physical knowledge of the system can be used in the identification process to significantly improve the predictive performance by restricting the space of possible mappings from the input to the output. Typically, the physical models contain unknown parameters that must be learned from data. Class

Venus Rai, Subhadip Jana, Martin Meven, Rajesh Dutta

Weyl semimetals are well known for their anomalous transport effects caused by a large fictitious magnetic field generated by the non-zero Berry curvature. We performed the analysis of the electrical transport measurements of the magnetic Weyl semimetal Mn$_{3}$Ge in the a-b and a-c plane. We have observed negative longitudinal magneto-resistance (LMR) at a

Jee-weon Jung, Hee-Soo Heo, Bong-Jin Lee, Jaesung Huh

Speaker embedding extractors (EEs), which map input audio to a speaker discriminant latent space, are of paramount importance in speaker diarisation. However, there are several challenges when adopting EEs for diarisation, from which we tackle two key problems. First, the evaluation is not straightforward because the features required for better performance

Nitish Mehta, Cristiano Ciuti, Roman Kuzmin, Vladimir E. Manucharyan

We revisit the superstrong coupling regime of multi-mode cavity quantum electrodynamics (QED), defined to occur when the frequency of vacuum Rabi oscillations between the qubit and the nearest cavity mode exceeds the cavity's free spectral range. A novel prediction is made that the cavity's linear spectrum, measured in the vanishing power limit, can acquire

Larisa Beilina, Eric Lindström

A new domain decomposition method for Maxwell's equations in conductive media is presented. Using this method reconstruction algorithms are developed for determination of dielectric permittivity function using time-dependent scattered data of electric field. All reconstruction algorithms are based on optimization approach to find stationary point of the Lagr

V. Cherniavskyi, G. Dennis, S. R. Kingan

The graph invariant examined in this paper is the largest eigenvalue of the adjacency matrix of a graph. Previous work demonstrates the tight relationship between this invariant, the birth and death rate of a contagion spreading on the graph, and the trajectory of the contagion over time. We begin by conducting a simulation confirming this and explore bounds

Yuchen Eleanor Jiang, Ryan Cotterell, Mrinmaya Sachan

Centering theory (CT; Grosz et al., 1995) provides a linguistic analysis of the structure of discourse. According to the theory, local coherence of discourse arises from the manner and extent to which successive utterances make reference to the same entities. In this paper, we investigate the connection between centering theory and modern coreference resolut

Rosana El Jurdi, Olivier Colliot

An important issue in medical image processing is to be able to estimate not only the performances of algorithms but also the precision of the estimation of these performances. Reporting precision typically amounts to reporting standard-error of the mean (SEM) or equivalently confidence intervals. However, this is rarely done in medical image segmentation st

Benjamin Fraser, Patrick Ingram

The second author proved that the set of post-critically finite polynomials of given degree is a set of bounded height, up to change of variables. Motivated by an observation about unicritical polynomials, we complement this by proving that the set of monic polynomials g(z) of given degree with the property that there exists a d > 1 such that g(z^d) is post-

Hugo Melchers, Daan Crommelin, Barry Koren, Vlado Menkovski

Neural closure models have recently been proposed as a method for efficiently approximating small scales in multiscale systems with neural networks. The choice of loss function and associated training procedure has a large effect on the accuracy and stability of the resulting neural closure model. In this work, we systematically compare three distinct proced

Min Wang, Hua Zhu

In this paper, we investigate the $L^{p}$-boundedness of the Riesz means and the $L^{p_{1}}\times L^{p_{2}}\rightarrow L^{p}$ boundedness of the bilinear Riesz means on M\'{e}tivier groups. M\'{e}tivier groups are generalization of Heisenberg groups and general H-type groups. Because general M\'{e}tivier groups only satisfy the non-degeneracy condition and h

Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra

Neural Ordinary Differential Equations (NODEs) have proven successful in learning dynamical systems in terms of accurately recovering the observed trajectories. While different types of sparsity have been proposed to improve robustness, the generalization properties of NODEs for dynamical systems beyond the observed data are underexplored. We systematically

Tyler Maunu, Thibaut Le Gouic, Philippe Rigollet

We revisit the problem of recovering a low-rank positive semidefinite matrix from rank-one projections using tools from optimal transport. More specifically, we show that a variational formulation of this problem is equivalent to computing a Wasserstein barycenter. In turn, this new perspective enables the development of new geometric first-order methods wit

Haoyu Xie, Changqi Wang, Mingkai Zheng, Minjing Dong

Recent breakthroughs in semi-supervised semantic segmentation have been developed through contrastive learning. In prevalent pixel-wise contrastive learning solutions, the model maps pixels to deterministic representations and regularizes them in the latent space. However, there exist inaccurate pseudo-labels which map the ambiguous representations of pixels

Dan Filipescu

Quasi-monochromatic, high energy and highly polarized $\gamma$-ray beam sources based on Compton scattering of laser photons (LCS) on relativistic electrons have developed for the last few decades as established instruments for nuclear physics studies. Following an extensive photoneutron experimental campaign at the LCS $\gamma$-ray beam line of the NewSUBAR

Tao Gui

We formulate a series of conjectures on the stable tensor product of irreducible representations of symmetric groups, which are closely related to the reduced Kronecker coefficients. These conjectures are certain generalizations of Okounkov's conjecture on the log-concavity of the Littlewood--Richardson coefficients and the Schur log-concavity theorem of Lam

Marcel Matha, Karsten Kucharczyk

White paper: The aim of this work is to apply and analyze machine learning methods for uncertainty quantification of turbulence models. In this work we investigate the classical and data-driven variants of the eigenspace perturbation method. This methodology is designed to estimate the uncertainties related to the shape of the modeled Reynolds stress tensor

Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma, Dongdong Zhang

Machine translation (MT) has almost achieved human parity at sentence-level translation. In response, the MT community has, in part, shifted its focus to document-level translation. However, the development of document-level MT systems is hampered by the lack of parallel document corpora. This paper describes BWB, a large parallel corpus first introduced in

Chunhui Wang, Chang Zeng, Xing He

XiaoiceSing is a singing voice synthesis (SVS) system that aims at generating 48kHz singing voices. However, the mel-spectrogram generated by it is over-smoothing in middle- and high-frequency areas due to no special design for modeling the details of these parts. In this paper, we propose XiaoiceSing2, which can generate the details of middle- and high-freq

Sherif Akoush, Andrei Paleyes, Arnaud Van Looveren, Clive Cox

Inference is a significant part of ML software infrastructure. Despite the variety of inference frameworks available, the field as a whole can be considered in its early days. This position paper puts forth a range of important qualities that next generation of inference platforms should be aiming for. We present our rationale for the importance of each qual

Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao

Vertical federated learning (VFL), where data features are stored in multiple parties distributively, is an important area in machine learning. However, the communication complexity for VFL is typically very high. In this paper, we propose a unified framework by constructing coresets in a distributed fashion for communication-efficient VFL. We study two impo

Gastón González, Rubén A. Fritz, Yamil J. Colón, Felipe Herrera

Porous materials are widely used for applications in gas storage and separation. The diffusive properties of a variety of gases in porous media can be modeled using molecular dynamics simulations that can be computationally demanding depending on the pore geometry, complexity and amount of gas adsorbed. We explore a dimensionality reduction approach for esti

Rong-Yang Sun, Tomonori Shirakawa, Seiji Yunoki

Motivated by the recent success of realizing the topologically ordered ground state of the exactly solvable toric code model by a quantum circuit on the real quantum device [K. J. Satzinger {\it et al}., Science \textbf{374}, 1237 (2021)], here we propose a parametrized quantum circuit (PQC) with the same real-device-performable optimal structure to represen

Santiago Pascual, Gautam Bhattacharya, Chunghsin Yeh, Jordi Pons

Recent works have shown the capability of deep generative models to tackle general audio synthesis from a single label, producing a variety of impulsive, tonal, and environmental sounds. Such models operate on band-limited signals and, as a result of an autoregressive approach, they are typically conformed by pre-trained latent encoders and/or several cascad

Wen Zhang, Yu-Lin Zheng

We study the performance of the simulated bifurcation (SB) algorithm for signal detection in multiple-input multiple-output (MIMO) system, a problem of key interest in modern wireless communication systems. Our results show that SB algorithm can achieve significant performance improvement over the widely used linear minimum-mean square error decoder in terms

Min Wang, Hua Zhu

In this article, we investigate the maximal bilinear Riesz means $S^{\alpha }_{*}$ associated to the sublaplacian on the Heisenberg group. We prove that the operator $S^{\alpha }_{*}$ is bounded from $L^{p_{1}}\times L^{p_{2}}$ into $% L^{p}$ for $2\leq p_{1}, p_{2}\leq \infty $ and $1/p=1/p_{1}+1/p_{2}$ when $% \alpha $ is large than a suitable smoothness i

Emmanuel V. C. Lopes, E. Vernek, Tome M. Schmidt

We have investigated magnetic interactions between transition metal ions in bismuthene topological insulator with protected edge states. We find that these topological states have a crucial role on the magnetic interactions in 2D topological insulators. Using first-principles and model Hamiltonian we make a comparative study of transition metal doped bulk an

Abhijit Das, Enrico Russo, Maurizio Palesi

The need to efficiently execute different Deep Neural Networks (DNNs) on the same computing platform, coupled with the requirement for easy scalability, makes Multi-Chip Module (MCM)-based accelerators a preferred design choice. Such an accelerator brings together heterogeneous sub-accelerators in the form of chiplets, interconnected by a Network-on-Package

S. Huemmerich, E. Paunzen, K. Bernhard

Shell stars, in particular the cooler ones, often do not show conspicuous Balmer-line emission and may consequently be missed in surveys that specifically search for emission signatures in the Halpha line. The present work is aimed at identifying stars with shell-signatures via a search for strong FeII multiplet 42 lines at 4924, 5018, 5169A in archival LAMO

Joanna Nieżurawska, Radosław A. Kycia, Iveta Ludviga, Agnieszka Niemczynowicz

This study aims to enrich the current literature by providing a new approach to motivating Generation Z employees in Poland. Employees need to be motivated in order to be efficient at doing a particular task at the workplace. As young people born between 1995 and 2004 called Generation Z, enter the labour market it, is essential to consider how employees' mo

Marek Fila, Kazuhiro Ishige, Tatsuki Kawakami

We study the linear heat equation on a halfspace with a linear dynamical boundary condition. We are interested in an appropriate choice of the function space of initial functions such that the problem possesses a solution. It was known before that bounded initial data guarantee solvability. Here we extend that result by showing that data from a weighted Lebe

Bowen Pang, Huan Zhao, Gaosheng Zhang, Xiaoyue Yang

This paper describes the TSUP team's submission to the ISCSLP 2022 conversational short-phrase speaker diarization (CSSD) challenge which particularly focuses on short-phrase conversations with a new evaluation metric called conversational diarization error rate (CDER). In this challenge, we explore three kinds of typical speaker diarization systems, which a

Uzy Smilansky, Gilad Sofer

The purpose of the present paper is to discuss the time dependent Schr\"odinger equation on a metric graph with time-dependent edge lengths, and the proper way to pose the problem so that the corresponding time evolution is unitary. We show that the well posedness of the Schr\"odinger equation can be guaranteed by replacing the standard Kirchhoff Laplacian w

Emily Zhang, Chi-Huan Tung, Luyi Feng, Yu Ren Zhou

Skin is the largest organ of many animals. Its protective function against hostile environments and predatorial attack makes high mechanical strength a vital characteristic. Here, we measured the mechanical properties of bass fish skins and found that fish skins are highly ductile with a rupture strain of up to 30-40% and a rupture strength of 10-15 MPa. The

Zhe Hu, Hou Pong Chan, Lifu Huang

Teaching neural models to generate narrative coherent texts is a critical problem. Recent pre-trained language models have achieved promising results, but there is still a gap between human written texts and machine-generated outputs. In this work, we propose a novel multi-task training strategy for coherent text generation grounded on the cognitive theory o

Jerome Jochems, Eddie Jones, Steven Ramsay

The monadic shallow linear (MSL) class is a decidable fragment of first-order Horn clauses that was discovered and rediscovered around the turn of the century, with applications in static analysis and verification. We propose a new class of higher-order Horn constraints which extend MSL to higher-order logic and develop a resolution-based decision procedure.

Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi, Noboru Harada

Masked Autoencoders is a simple yet powerful self-supervised learning method. However, it learns representations indirectly by reconstructing masked input patches. Several methods learn representations directly by predicting representations of masked patches; however, we think using all patches to encode training signal representations is suboptimal. We prop

Bart Cleuren, Ralf Eichhorn

A general formalism is derived describing both dynamical and energetic properties of a microscopic Feynman ratchet. Work and heat flows are given as a series expansion in the thermodynamic forces, obtaining analytical expressions for the (non)linear response coefficients. Our results extend previously obtained expressions in the context of a chiral heat pump

Josef Matouš, Kristin Y. Pettersen, Damiano Varagnolo, Claudio Paliotta

This paper proposes a method for formation path following control of a fleet of underactuated autonomous underwater vehicles. The proposed method combines several hierarchic tasks in a null space-based behavioral algorithm to safely guide the vehicles. Compared to the existing literature, the algorithm includes both inter-vehicle and obstacle collision avoid

Hongyi Wang, Lanfen Lin, Hongjie Hu, Qingqing Chen

High resolution (HR) 3D images are widely used nowadays, such as medical images like Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). However, segmentation of these 3D images remains a challenge due to their high spatial resolution and dimensionality in contrast to currently limited GPU memory. Therefore, most existing 3D image segmentation met

Yuxuan Du, Ruohua Zhou

In the task of speaker diarization, the number of small-scale meetings accounts for a large proportion. When microphone arrays are employed as a recording device, its spatial information is usually ignored by most researchers. In this paper, inspired by the clustering method combining d-vector and microphone array spatial vector, we proposed a diarization me

Alberto Bressan, Khai T. Nguyen

We consider a class of deterministic mean field games, where the state associated with each player evolves according to an ODE which is linear w.r.t. the control. Existence, uniqueness, and stability of solutions are studied from the point of view of generic theory. Within a suitable topological space of dynamics and cost functionals, we prove that, for near

Asu Büşra Temizer, Gökçe Uludoğan, Rıza Özçelik, Taha Koulani

Machine learning models have found numerous successful applications in computational drug discovery. A large body of these models represents molecules as sequences since molecular sequences are easily available, simple, and informative. The sequence-based models often segment molecular sequences into pieces called chemical words (analogous to the words that

Simon Anniés, Christoph Scheurer, Chiara Panosetti

Lithium-graphite intercalation compounds (Li-GICs) are the most common anode material for modern Li-ion batteries. However, the dielectric response of this material in the electrostatic limit (and its variation with the state of charge (SOC)) has not been investigated to a satisfactory degree, especially not for the higher SOC range. Nevertheless, said diele

Aurélien Delage, Olivier Buffet, Jilles S. Dibangoye, Abdallah Saffidine

State-of-the-art methods for solving 2-player zero-sum imperfect information games rely on linear programming or regret minimization, though not on dynamic programming (DP) or heuristic search (HS), while the latter are often at the core of state-of-the-art solvers for other sequential decision-making problems. In partially observable or collaborative settin

M. T. Núñez Pardo de Vera, M. Berggren, J. List

One of the most interesting channels to search for SUSY is the direct pair-production of the $\tau$-lepton superpartner, $\widetilde{\tau}$. The $\widetilde{\tau}$ is with high probability the lightest of the scalar leptons, so one of the first SUSY particles that can be observerd, and the signature of $\widetilde{\tau}$ pair production signal events is one

Daniel Lokshtanov, Marcin Pilipczuk, Michał Pilipczuk, Saket Saurabh

We prove that Graph Isomorphism and Canonization in graphs excluding a fixed graph $H$ as a minor can be solved by an algorithm working in time $f(H)\cdot n^{O(1)}$, where $f$ is some function. In other words, we show that these problems are fixed-parameter tractable when parameterized by the size of the excluded minor, with the caveat that the bound on the

Kristen C. Dage, Yifan Sun, Arunav Kundu, Stephen E. Zepf

We investigate archival Hubble Space Telescope ACS/SBC F140LP observations of NGC~1399 to search for evidence of multiple stellar populations in extragalactic globular clusters. Enhanced FUV populations are thought to be indicators of He-enhanced second generation populations in globular clusters, specifically extreme/blue horizontal branch stars. Out of 149

Zhao Ren, Thanh Tam Nguyen, Yi Chang, Björn W. Schuller

Speech emotion recognition (SER) is the task of recognising human's emotional states from speech. SER is extremely prevalent in helping dialogue systems to truly understand our emotions and become a trustworthy human conversational partner. Due to the lengthy nature of speech, SER also suffers from the lack of abundant labelled data for powerful models like

Zijian Lin, Cuixiang Wang, A. Balassis, J. P. Echeverry

1T-TiSe2 is one of the most studied charge density wave (CDW) systems, not only because of its peculiar properties related to the CDW transition, but also due to its status as a promising candidate of exciton insulator signaled by the proposed plasmon softening at the CDW wave vector. Using high-resolution electron energy loss spectroscopy, we report a syste

Selma Benseguane, Aurélie Guilbert-Lepoutre, Jérémie Lasue, Sébastien Besse

The observation of pits at the surface of comets offers the opportunity to take a glimpse into the properties and the mechanisms that shape a nucleus through cometary activity. If the origin of these pits is still a matter of debate, multiple studies have recently suggested that known phase transitions alone could not have carved these morphological features

Koki Yamada

The problem of recovering graph signals is one of the main topics in graph signal processing. A representative approach to this problem is the graph Wiener filter, which utilizes the statistical information of the target signal computed from historical data to construct an effective estimator. However, we often encounter situations where the current graph di