October 2022 arXiv papers — page 5

Daniel Kelshaw, Georgios Rigas, Luca Magri

In the absence of high-resolution samples, super-resolution of sparse observations on dynamical systems is a challenging problem with wide-reaching applications in experimental settings. We showcase the application of physics-informed convolutional neural networks for super-resolution of sparse observations on grids. Results are shown for the chaotic-turbule

Jingyu Li, Yusheng Tian, Tan Lee

Deep convolutional neural networks (CNNs) have been applied to extracting speaker embeddings with significant success in speaker verification. Incorporating the attention mechanism has shown to be effective in improving the model performance. This paper presents an efficient two-dimensional convolution-based attention module, namely C2D-Att. The interaction

Soroush Shakeri, Davood Rafiei Karkevandi

We explore the presence of self-interacting bosonic dark matter (DM) within neutron stars (NSs) in light of the latest multi-messenger observations of the Neutron Star Interior Composition Explorer (NICER) and LIGO/Virgo detectors. The bosonic DM is distributed as a core inside the NS or as a halo around it leading to formation of a DM admixed NS. We focus o

Shoya Motonaga

We study properties of action-minimizing invariant sets for Tonelli Lagrangian and Hamiltonian systems and weak KAM solutions to the Hamilton-Jacobi equation in terms of Mather's averaging functions. Our principal discovery is that exposed points and extreme points of Mather's alpha function are closely related to disjoint properties and graph properties of

Hadi Nahari, Thomas Strobl

We recall the notion of a singular foliation (SF) on a manifold $M$, viewed as an appropriate submodule of $\mathfrak{X}(M)$, and adapt it to the presence of a Riemannian metric $g$, yielding a module version of a singular Riemannian foliation (SRF). Following Garmendia-Zambon on Hausdorff Morita equivalence of SFs, we define the Morita equivalence of SRFs (

Yongmao Zhang, Zhichao Wang, Peiji Yang, Hongshen Sun

Learning accent from crowd-sourced data is a feasible way to achieve a target speaker TTS system that can synthesize accent speech. To this end, there are two challenging problems to be solved. First, direct use of the poor acoustic quality crowd-sourced data and the target speaker data in accent transfer will apparently lead to synthetic speech with degrade

Philipp Karg, Simon Stoll, Simon Rothfuß, Sören Hohmann

Stochastic Optimal Control models represent the state-of-the-art in modeling goal-directed human movements. The linear-quadratic sensorimotor (LQS) model based on signal-dependent noise processes in state and output equation is the current main representative. With our newly introduced Inverse Stochastic Optimal Control algorithm building upon two bi-level o

Daegyu Lee, Hyunki Seong, Seungil Han, Gyuree Kang

Recently, numerous studies have investigated cooperative traffic systems using the communication among vehicle-to-everything (V2X). Unfortunately, when multiple autonomous vehicles are deployed while exposed to communication failure, there might be a conflict of ideal conditions between various autonomous vehicles leading to adversarial situation on the road

Irina Bigoulaeva, Rachneet Sachdeva, Harish Tayyar Madabushi, Aline Villavicencio

We compare sequential fine-tuning with a model for multi-task learning in the context where we are interested in boosting performance on two tasks, one of which depends on the other. We test these models on the FigLang2022 shared task which requires participants to predict language inference labels on figurative language along with corresponding textual expl

Rainer Sinn, Günter M. Ziegler

In his first mathematical paper, published in 1895 when he was 18, Edmund Landau suggested a new way to determine the winner of a chess tournament by not simply adding for each player the fixed number of points they would get for each win or draw, but rather by considering the performance of all players in the tournament relative to each other: each player w

Zhuoling Jiang, Tong Su, Cherq Chua, L. K. Ang

Two-dimensional (2D) layered dielectrics offers a compelling route towards the design of next-generation ultimately compact nanoelectronics. Motivated by recent high-throughput computational prediction of LaO$X$ ($X$ = Br, Cl) as an exceptional 2D dielectrics that significantly outperforms HfO$_2$ even in the monolyaer limit, we investigate the interface pro

Yiying Wang, Xin Kang, Tieyan Li, Haiguang Wang

Recent years have witnessed a digital explosion with the deployment of 5G and proliferation of 5G-enabled innovations. Compared with 5G, 6G is envisioned to achieve much higher performance in terms of latency, data rate, connectivity, energy efficiency, coverage and mobility. To fulfil these expectations, 6G will experience a number of paradigm shifts, such

He Zhang, Santosh Kumar, Yong Meng Sua, Shenyu Zhu

We demonstrate a photon-sensitive, three-dimensional camera by active near-infrared illumination and fast time-of-flight gating. It uses pico-second pump pulses to selectively up-convert the backscattered photons according to their spatiotemporal modes via sum-frequency generation in a \c{hi}2 nonlinear crystal, which are then detected by electron-multiplyin

Zhou Li, Chinmay Khandekar

Achieving strong repulsive Casimir forces through engineered coatings can pave the way for micro- and nano-electromechanical applications where adhesive forces currently cause reliability issues. Here, we exploit Lifshitz theory to identify the requirements for repulsive Casimir forces in gyrotropic media for two limiting cases (ultra-strong gyroelectric and

Pragya Srivastava, Tanuja Ganu, Saikat Guha

We present very early results on using GPT-3 to perform question answering on tabular data. We find that stock pre-trained GPT-3 is able to zero-shot learn the table structure from a serialized JSON array-of-arrays representation, and able to answer lookup queries and simple comparison questions in natural language without any fine-tuning. We further find th

Erik Christensen

For an $m \times n$ complex matrix $X$ of rank $r$ with Schur multiplier $S_X$ we show that there exist an $ r \times m $ complex matrix $L$ and an $ r\times n $ complex matrix $R$ such that $X = L^*R$ and $\|S_X\|\, =\, \|\mathrm{diag} (L^*L) \|^{\frac{1}{2}} \| \mathrm{diag} (R^*R) \| ^{\frac{1}{2}},$ and the norm condition is optimal. Let the completely b

Mathieu Chevalley, Yusuf Roohani, Arash Mehrjou, Jure Leskovec

Causal inference is a vital aspect of multiple scientific disciplines and is routinely applied to high-impact applications such as medicine. However, evaluating the performance of causal inference methods in real-world environments is challenging due to the need for observations under both interventional and control conditions. Traditional evaluations conduc

José Ignacio Cogolludo-Agustín, Eva Elduque

In this work we study smooth complex quasi-projective surfaces whose fundamental group is a free product of cyclic groups. In particular, we prove the existence of an admissible map from the quasi-projective surface to a smooth complex quasi-projective curve. Associated with this result, we prove addition-deletion Lemmas for fibers of the admissible map whic

Liekang Zeng, Chongyu Yang, Peng Huang, Zhi Zhou

Edge intelligence has arisen as a promising computing paradigm for supporting miscellaneous smart applications that rely on machine learning techniques. While the community has extensively investigated multi-tier edge deployment for traditional deep learning models (e.g. CNNs, RNNs), the emerging Graph Neural Networks (GNNs) are still under exploration, pres

J. de la Nuez González

We show that the homeomorphism group of a surface without boundary does not admit a Hausdorff group topology strictly coarser than the compact-open topology. In combination with known automatic continuity results, this implies that the compact-open topology is the unique Hausdorff separable group topology on the group if the surface is closed or the compleme

Regina S. Burachik, Bethany I. Caldwell, C. Yalçın Kaya

Splitting and projection-type algorithms have been applied to many optimization problems due to their simplicity and efficiency, but the application of these algorithms to optimal control is less common. In this paper we utilize the Douglas--Rachford (DR) algorithm to solve control-constrained minimum-energy optimal control problems. Instead of the tradition

N. Hlaing, Pablo G. Morato, F. d. N. Santos, W. Weijtjens

Offshore wind structures are subject to deterioration mechanisms throughout their operational lifetime. Even if the deterioration evolution of structural elements can be estimated through physics-based deterioration models, the uncertainties involved in the process hurdle the selection of lifecycle management decisions. In this scenario, the collection of re

Bernt Øksendal

In the first part of this paper I give the historical background to my initial interest in stochastic analysis and to the writing of my book Stochastic Differential Equations. The first edition of this book was published by Springer in 1985, with the highly appreciated support of Catriona Byrne. In the second part I present a motivation for modelling the dyn

Md. Sajidul Islam, Razu Ahmed, Md. Mahamudujjaman, R. S. Islam

We present a detailed density functional theory based calculations of the structural, elastic, lattice dynamical, thermophysical, and optoelectronic properties of ternary semiconductors CaZn$_2$X$_2$ (X = N, P, As) in this paper. The obtained lattice parameters are in excellent agreement with the experimental values and other theoretical findings. These elas

Thomas Waters, Matthew Cherrie

In this paper we study the conjugate locus in convex manifolds. Our main tool is Jacobi fields, which we use to define a special coordinate system on the unit sphere of the tangent space; this provides a natural coordinate system to study and classify the singularities of the conjugate locus. We pay particular attention to 3-dimensional manifolds, and descri

Roman Prosanov

Let $M$ be a compact orientable 3-manifold with hyperbolizable interior and non-empty boundary such that all boundary components have genii at least 2. We study an Alexandrov-Weyl-type problem for convex hyperbolic cone-metrics on $\partial M$. We consider a class of hyperbolic metrics on M with convex boundary, which we call bent metrics, and which naturall

Egor I. Kiselev, Florian G. Pflug, Arndt von Haeseler

We develop a Fokker-Planck theory of tissue growth with three types of cells (symmetrically dividing, asymmetrically dividing and non-dividing) as main agents to study the growth dynamics of human cerebral organoids. Fitting the theory to lineage tracing data obtained in next generation sequencing experiments, we show that the growth of cerebral organoids is

Bingyang Wen, K. P. Subbalakshmi, Fan Yang

Attention mechanisms have recently demonstrated impressive performance on a range of NLP tasks, and attention scores are often used as a proxy for model explainability. However, there is a debate on whether attention weights can, in fact, be used to identify the most important inputs to a model. We approach this question from an information theoretic perspec

Yen Hoang Nguyen

Scoliosis is a sideways curvature of the spine that most often is diagnosed among young teenagers. It dramatically affects the quality of life, which can cause complications from heart and lung injuries in severe cases. The current gold standard to detect and estimate scoliosis is to manually examine the spinal anterior-posterior X-ray images. This process i

Anthony Mallama, Jay Respler

A large dataset of visual magnitudes for all three designs of Starlink satellites is analyzed. Brightness phase functions are derived for the Original, VisorSat and Post-VisorSat models. Similarities and differences between the functions for these spacecraft are noted. A metric called the characteristic magnitude is defined as the average brightness of a sat

Rahul Dandekar, R. Rajesh, V. Subashri, Oleg Zaboronski

We develop a biased Monte Carlo algorithm to measure probabilities of rare events in cluster-cluster aggregation for arbitrary collision kernels. Given a trajectory with a fixed number of collisions, the algorithm modifies both the waiting times between collisions, as well as the sequence of collisions, using local moves. We show that the algorithm is ergodi

Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab, Hadi Otrok

Federated Learning (FL) is a novel distributed privacy-preserving learning paradigm, which enables the collaboration among several participants (e.g., Internet of Things devices) for the training of machine learning models. However, selecting the participants that would contribute to this collaborative training is highly challenging. Adopting a random select

Sergey Buterin

We suggest a new concept of functional-differential operators with constant delay on geometrical graphs that involves {\it global} delay parameter. Differential operators on graphs model various processes in many areas of science and technology. Although a vast majority of studies in this direction concern purely differential operators on graphs (often refer

Philipp Karg, Simon Stoll, Simon Rothfuß, Sören Hohmann

In this paper, we define and solve the Inverse Stochastic Optimal Control (ISOC) problem of the linear-quadratic Gaussian (LQG) and the linear-quadratic sensorimotor (LQS) control model. These Stochastic Optimal Control (SOC) models are state-of-the-art approaches describing human movements. The LQG ISOC problem consists of finding the unknown weighting matr

Nikolaos Ellinas, Georgios Vamvoukakis, Konstantinos Markopoulos, Georgia Maniati

This paper presents a method for end-to-end cross-lingual text-to-speech (TTS) which aims to preserve the target language's pronunciation regardless of the original speaker's language. The model used is based on a non-attentive Tacotron architecture, where the decoder has been replaced with a normalizing flow network conditioned on the speaker identity, allo

Lars Becker

We prove $L^2 \to L^p$ estimates on the torus for maximal polynomial modulations of Calder\'on-Zygmund operators with anisotropic scaling. We obtain improved constants in these estimates. As a corollary, maximal polynomial modulations of a mollified version of the Hilbert transform along the parabola are bounded with only logarithmic dependence of the estima

Wei Day, Hao-Sheng Chen, Min-Te Sun

This work proposes QNet, a novel sequence encoder model that entirely inferences on the quantum computer using a minimum number of qubits. Let $n$ and $d$ represent the length of the sequence and the embedding size, respectively. The dot-product attention mechanism requires a time complexity of $O(n^2 \cdot d)$, while QNet has merely $O(n+d)$ quantum circuit

Carlos Celemin, Rodrigo Pérez-Dattari, Eugenio Chisari, Giovanni Franzese

Interactive Imitation Learning (IIL) is a branch of Imitation Learning (IL) where human feedback is provided intermittently during robot execution allowing an online improvement of the robot's behavior. In recent years, IIL has increasingly started to carve out its own space as a promising data-driven alternative for solving complex robotic tasks. The advant

Thomas Hahn, Andrii Verbytskyi

The installation and maintenance of scientific software for research in experimental, phenomenological, and theoretical High Energy Physics (HEP) requires a considerable amount of time and expertise. While many tools are available to make the task of installation and maintenance much easier, many of these tools require maintenance on their own, have little d

Sifan Liu, Rang Liu, Ming Li, Yang Liu

Reconfigurable intelligent surface (RIS) is a revolutionary technology for sixth-generation (6G) networks owing to its ability to manipulate wireless environments. As a frequency-selective device, RIS can only effectively shape the propagation of signals within a certain frequency band. Due to this frequency-selective property, the deployment of RIS in cellu

Pan Li, Yi Ling, Zhangping Yu

We investigate the generation rate of quantum gravity induced entanglement of masses(QGEM) in setup with multiple quantum massive particles, among of which only the gravity interaction due to the Newton potential is taken into account. When the distance between any two adjacent Stern-Gerlach (SG) devices is fixed, we consider all the possible configurations

Jianjian Qin, Chunzhi Gu, Jun Yu, Chao Zhang

Anomaly detection, which is a critical and popular topic in computer vision, aims to detect anomalous samples that are different from the normal (i.e., non-anomalous) ones. The current mainstream methods focus on anomaly detection for images, whereas little attention has been paid to 3D point cloud. In this paper, drawing inspiration from the knowledge trans

Maxime Chambonneau, Qingfeng Li, Markus Blothe, Stefan Nolte

While ultrafast laser welding is an appealing technique for bonding transparent workpieces, it is not applicable for joining silicon samples due to nonlinear propagation effects which dramatically diminishes the possible energy deposition at the interface. We demonstrate that these limitations can be circumvented by local absorption enhancement at the interf

Vladimir R. Chechetkin, Vasily V. Lobzin

The multifunctional nucleoproteins play important role in the life cycle of coronaviruses. The assessment of their quantities is of general interest for the assembly of virions and medical applications. The proliferating nucleoproteins induce the related (auto)immune response and via binding to host RNA affect various regulation mechanisms. In this report we

Anne Matthies, Mark Rudner, Achim Rosch, Erez Berg

We propose a simple, robust protocol to prepare a low-energy state of an arbitrary Hamiltonian on a quantum computer or programmable quantum simulator. The protocol is inspired by the adiabatic demagnetization technique, used to cool solid-state systems to extremely low temperatures. A fraction of the qubits (or spins) is used to model a spin bath that is co

Zhi-Hong Sun

Let $p>3$ be a prime. In this paper, we obtain the congruences for $$\sum_{k=0}^{p-1}\frac{w(k)\binom{2k}k^3}{(-8)^k},\ \sum_{k=0}^{p-1}\frac{w(k)\binom{2k}k^2\binom{3k}k}{(-192)^k},\ \sum_{k=0}^{p-1}\frac{w(k)\binom{2k}k^2\binom{4k}{2k}}{(-144)^k}\ \text{and} \ \sum_{k=0}^{p-1}\frac{w(k)\binom{2k}k^2\binom{4k}{2k}}{648^k}$$ modulo $p^2$, and partial results

Mark Hillery, Himanshu Gupta, Caitao Zhan

We model a quantum sensor network using techniques from quantum state discrimination. The interaction between a qubit detector and the environment is described by a unitary operator, and we will assume that at most one detector does interact. The task is to determine which one does or if none do. This involves choosing an initial state of the detectors and a

Kris Coolsaet, Sven D'hondt, Jan Goedgebeur

In 2012 we announced the House of Graphs (https://houseofgraphs.org) [Discrete Appl. Math. 161 (2013), 311-314], which was a new database of graphs. The House of Graphs hosts complete lists of graphs of various graph classes, but its main feature is a searchable database of so called "interesting" graphs, which includes graphs that already occurred as extrem

Hongxiang Jiang, Wenming Meng, Hongmei Zhu, Qian Zhang

In advanced paradigms of autonomous driving, learning Bird's Eye View (BEV) representation from surrounding views is crucial for multi-task framework. However, existing methods based on depth estimation or camera-driven attention are not stable to obtain transformation under noisy camera parameters, mainly with two challenges, accurate depth prediction and c

Songbai Guo, Min He, Jing-An Cui

A four-dimensional delay differential equations (DDEs) model of malaria with standard incidence rate is proposed. By utilizing the limiting system of the model and Lyapunov direct method, the global stability of equilibria of the model is obtained with respect to the basic reproduction number ${R}_{0}$. Specifically, it shows that the disease-free equilibriu

Martin Tømterud, Simen K. Hellner, Sabrina D. Eder, Stiven Forti

The mechanical properties of two-dimensional materials are important for a wide range of applications including composite and van der Waals-materials, flexible electronics and superconductivity. Several aspects are highly debated in the literature: For example, the theoretically predicted bending rigidity $\kappa$ at 0 K for quasi free-standing graphene vari

Kei Yuen Chan

The main goal of this article is to formulate a notion, called a generalized GGP relevant pair, governing the quotient branching law for $p$-adic general linear groups. Such notion relies on a commutation relation between derivatives (from Jacquet functors) and integrals (from parabolic inductions), for which we provide both representation-theoretic and comb

Zakaria Dahbi, Mansoura Oumennana, Mostafa Mansour

Spin qubits are at the heart of technological advances in quantum processors and offer an excellent framework for quantum information processing. This work characterizes the time evolution of coherence and nonclassical correlations in a two-spin XXZ Heisenberg model, from which a two-qubit system is realized. We study the effects of intrinsic decoherence on

Hiroaki Tanaka, Kenta Kuroda, Tomohiro Matsushita

We develop a software package SPADExp (simulator of photoemission angular distribution for experiments) to calculate the photoemission angular distribution (PAD), which is the momentum dependence of spectrum intensity in angle-resolved photoemission spectroscopy (ARPES). The software can directly load the output of the first-principles software package OpenM

Pratik Kayal, Mrinal Anand, Harsh Desai, Mayank Singh

Scientific documents contain tables that list important information in a concise fashion. Structure and content extraction from tables embedded within PDF research documents is a very challenging task due to the existence of visual features like spanning cells and content features like mathematical symbols and equations. Most existing table structure identif

M. Schmassmann, M. Rempel, N. Bello González, R. Schlichenmaier

We analyse a sunspot simulation in an effort to understand the origin of the convective instabilities giving rise to the penumbral and umbral distinct regimes. We applied the criterion from Gough \& Tayler (1966), accounting for the stabilising effect of the vertical magnetic field to investigate the convective instabilities in a MURaM sunspot simulation. We

Pierre-Étienne Druet, Katharina Hopf, Ansgar Jüngel

We investigate degenerate cross-diffusion equations with a rank-deficient diffusion matrix that are considered to model populations which move as to avoid spatial crowding and have recently been found to arise in a mean-field limit of interacting stochastic particle systems. To date, their analysis in multiple space dimensions has been confined to the purely

Yajun Zhou

The hyper-Mahler measures $m_k( 1+x_1+x_2),k\in\mathbb Z_{>1}$ and $m_k( 1+x_1+x_2+x_3),k\in\mathbb Z_{>1}$ are evaluated in closed form via Goncharov-Deligne periods, namely $\mathbb Q$-linear combinations of multiple polylogarithms at cyclotomic points (complex-valued coordinates that are roots of unity). Some infinite series related to these hyper-Mahler

Robert Lasarzik, Maximilian E. V. Reiter

We define the concept of energy-variational solutions for the Ericksen--Leslie equations in three spatial dimensions. This solution concept is finer than dissipative solutions and satisfies the weak-strong uniqueness property. For a certain choice of the regularity weight, the existence of energy-variational solutions implies the existence of measure-valued

Dingran Yi, Nikolaos M. Freris

We consider the problem of minimizing the sum of cost functions pertaining to agents over a network whose topology is captured by a directed graph (i.e., asymmetric communication). We cast the problem into the ADMM setting, via a consensus constraint, for which both primal subproblems are solved inexactly. In specific, the computationally demanding local min

Volker Branding, Anna Siffert

We prove that for given $k\in\mathbb{N}$, $k\geq 3$, $d\in\mathbb{N}$ and each $a\in\mathbb{R}^{*}$ with \begin{align*} a^2<4d (d+k-2)(k-2)^{-2} \end{align*} the ellipsoid $E_a:=\{x\in\mathbb{R}^k\,\lvert\,a^{-2}x_1^2+x_2^2+\ldots+x_k^2=1\}$ admits infinitely many harmonic self-maps.

Krishan K. Tiwari, Giuseppe Caire

We present a novel, power and hardware efficient, antenna system leveraging the eigenmodes of the over-the-air propagation matrix from an active multi-antenna feeder (AMAF) to a large reflective intelligent surface (RIS), both configured as standard linear arrays and placed in the near field of each other. We demonstrate the flexibility of the proposed archi

Nyoungwoo Lee, ChaeHun Park, Ho-Jin Choi, Jaegul Choo

In retrieval-based dialogue systems, a response selection model acts as a ranker to select the most appropriate response among several candidates. However, such selection models tend to rely on context-response content similarity, which makes models vulnerable to adversarial responses that are semantically similar but not relevant to the dialogue context. Re

Katherine Tsai, Boxin Zhao, Sanmi Koyejo, Mladen Kolar

Joint multimodal functional data acquisition, where functional data from multiple modes are measured simultaneously from the same subject, has emerged as an exciting modern approach enabled by recent engineering breakthroughs in the neurological and biological sciences. One prominent motivation to acquire such data is to enable new discoveries of the underly

Daoguang Zan, Bei Chen, Zeqi Lin, Bei Guan

With the rapid development of pre-training techniques, a number of language models have been pre-trained on large-scale code corpora and perform well in code generation. In this paper, we investigate how to equip pre-trained language models with the ability of code generation for private libraries. In practice, it is common for programmers to write code usin

Moran Mizrahi, Dafna Shahaf

The web is full of guidance on a wide variety of tasks, from changing the oil in your car to baking an apple pie. However, as content is created independently, a single task could have thousands of corresponding procedural texts. This makes it difficult for users to view the bigger picture and understand the multiple ways the task could be accomplished. In t

Corrado Monti, Luca Maria Aiello, Gianmarco De Francisci Morales, Francesco Bonchi

Which messages are more effective at inducing a change of opinion in the listener? We approach this question within the frame of Habermas' theory of communicative action, which posits that the illocutionary intent of the message (its pragmatic meaning) is the key. Thanks to recent advances in natural language processing, we are able to operationalize this th

Ines Rieger, Jaspar Pahl, Bettina Finzel, Ute Schmid

Neural networks are widely adopted, yet the integration of domain knowledge is still underutilized. We propose to integrate domain knowledge about co-occurring facial movements as a constraint in the loss function to enhance the training of neural networks for affect recognition. As the co-ccurrence patterns tend to be similar across datasets, applying our m

Joseph M. Hamill, Ali Ismael, Alaa Al-Jobory, Troy L. R. Bennett

We report on the single-molecule electronic and thermoelectric properties of strategically chosen anthracene-based molecules with anchor groups capable of binding to noble metal substrates, such as gold and platinum. Specifically, we study the effect of different anchor groups, as well as quantum interference, on the electric conductance and the thermopower

Xiu-Hua Luo, Shijie Zhu

Given a finite dimensional algebra $A$ over a field $k$, and a finite acyclic quiver $Q$, let $\Lambda = A\otimes_k kQ/I$, where $kQ$ is the path algebra of $Q$ over $k$ and $I$ is a monomial ideal. We show that $(\mathcal X,\mathcal Y)$ is a (complete) hereditary cotorsion pair in $A$-mod if and only if $({\rm smon}(Q,I,\mathcal X), {\rm rep}(Q,I,\mathcal Y

Hyemin Gu, Panagiota Birmpa, Yannis Pantazis, Luc Rey-Bellet

We build a new class of generative algorithms capable of efficiently learning an arbitrary target distribution from possibly scarce, high-dimensional data and subsequently generate new samples. These generative algorithms are particle-based and are constructed as gradient flows of Lipschitz-regularized Kullback-Leibler or other $f$-divergences, where data fr

Matthew G. Hennessy, Richard V. Craster, Omar K. Matar

Understanding the generation of mechanical stress in drying, particle-laden films is important for a wide range of industrial processes. The cantilever experiment allows the stress in a drying film that has been deposited onto a thin plate to be quantified. Mechanical stresses in the film are transmitted to the plate and drive bending. Mathematical modelling

Florian van Daalen, Lianne Ippel, Andre Dekker, Inigo Bermejo

Federated learning makes it possible to train a machine learning model on decentralized data. Bayesian networks are probabilistic graphical models that have been widely used in artificial intelligence applications. Their popularity stems from the fact they can be built by combining existing expert knowledge with data and are highly interpretable, which makes

Geraint I. Palmer, Jorge Martín-Pérez

The future Internet promises to support time-sensitive services that require ultra low latencies and reliabilities of 99.99%. Recent advances in cellular and WiFi connections enhance the network to meet high reliability and ultra low latencies. However, the aforementioned services require that the server processing time ensures low latencies with high reliab

Yan B. Bandeira, Victor P. Goncalves

In this paper we investigate the impact of the higher - twist effects, resummed by the non - linear approaches for the QCD dynamics, on the inclusive observables that will be measured in future electron - ion colliders. We assume a phenomenological model for the dipole - nucleus scattering amplitude which takes into account the non - linear corrections and e

Antoine Henrot, Antoine Lemenant, Ilaria Lucardesi

In this paper we prove that among all convex domains of the plane with two axis of symmetry, the maximizer of the first non trivial Neumann eigenvalue $\mu_1$ with perimeter constraint is achieved by the square and the equilateral triangle. Part of the result follows from a new general bound on $\mu_1$ involving the minimal width over the area. Our main resu

Moshe Eliasof, Lars Ruthotto, Eran Treister

Graph Neural Networks (GNNs) are limited in their propagation operators. In many cases, these operators often contain non-negative elements only and are shared across channels, limiting the expressiveness of GNNs. Moreover, some GNNs suffer from over-smoothing, limiting their depth. On the other hand, Convolutional Neural Networks (CNNs) can learn diverse pr

Jiamin Li, Yimin Jiang, Yibo Zhu, Cong Wang

Scaling model parameters improves model quality at the price of high computation overhead. Sparsely activated models, usually in the form of Mixture of Experts (MoE) architecture, have sub-linear scaling of computation cost with model size, thus providing opportunities to train and serve a larger model at lower cost than their dense counterparts. However, di

Shangsheng Wen, Manxi Liu, Yanyi Chen, Yirong Chen

We demonstrate an internet access application based on optical camera communication and bluetooth. The app will access the website while the camera in the phone receives the optical signal. \c{opyright} 2022 The Author(s)

Luigi Attorresi, Davide Salvi, Clara Borrelli, Paolo Bestagini

The rapid spread of media content synthesis technology and the potentially damaging impact of audio and video deepfakes on people's lives have raised the need to implement systems able to detect these forgeries automatically. In this work we present a novel approach for synthetic speech detection, exploiting the combination of two high-level semantic propert

Aleksandra Nabilkova, Azat Ismagilov, Maksim Melnik, Anton Tcypkin

To create self-controlled radiation photonics systems, it is necessary to have complete information about the nonlinear properties of the materials used. In this paper, the vibrational mechanism of the giant low-inertia cubic nonlinearity of water in the terahertz frequency range is experimentally proven. Its dominance which manifests itself when the tempera

André Oliva, Rolf Kuiper

Like their lower mass siblings, massive protostars can be expected to: a) be surrounded by circumstellar disks and b) launch magnetically-driven jets and outflows. The disk formation and global evolution is thereby controlled by advection of angular momentum from large scales, the efficiency of magnetic braking and the resistivity of the medium, and the inte

Yoshiaki Sofue

The mechanism to produce the numerous Galactic-Centre filaments (GCF) that vertically penetrate the Galactic plane without clear evidence of connection to the disc remains a mystery . Here we show that the GCFs are explained by relics of supernova remnants (rSNR) driven by hundreds of supernovae (SNe) exploded in the star-forming ring of the central molecula

Vincent J. Straub, Deborah Morgan, Jonathan Bright, Helen Margetts

Recent advances in artificial intelligence (AI), especially in generative language modelling, hold the promise of transforming government. Given the advanced capabilities of new AI systems, it is critical that these are embedded using standard operational procedures, clear epistemic criteria, and behave in alignment with the normative expectations of society

Lawrence Yunliang Chen, Baiyu Shi, Daniel Seita, Richard Cheng

Thin plastic bags are ubiquitous in retail stores, healthcare, food handling, recycling, homes, and school lunchrooms. They are challenging both for perception (due to specularities and occlusions) and for manipulation (due to the dynamics of their 3D deformable structure). We formulate the task of "bagging:" manipulating common plastic shopping bags with tw

Bo Zhao, Iordan Ganev, Robin Walters, Rose Yu

Empirical studies of the loss landscape of deep networks have revealed that many local minima are connected through low-loss valleys. Yet, little is known about the theoretical origin of such valleys. We present a general framework for finding continuous symmetries in the parameter space, which carve out low-loss valleys. Our framework uses equivariances of

Sten Vercammen, Serge Demeyer, Markus Borg, Niklas Pettersson

Mutation testing is the state-of-the-art technique for assessing the fault detection capacity of a test suite. Unfortunately, a full mutation analysis is often prohibitively expensive. The CppCheck project for instance, demands a build time of 5.8 minutes and a test execution time of 17 seconds on our desktop computer. An unoptimised mutation analysis, for 5

T. Cap, M. Kowal, K. Siwek-Wilczyńska

This article summarizes recent progress in our understanding of the reaction mechanisms leading to the formation of superheavy nuclei in cold and hot fusion reactions. Calculations are done within the Fusion-by-Diffusion (FBD) model using the new nuclear data tables by Jachimowicz et al. [At. Data Nucl. Data Tables 138, 101393 (2021)]. The synthesis reaction

Tom Savage, Nausheen Basha, Omar Matar, Ehecatl Antonio Del-Rio Chanona

New manufacturing techniques such as 3D printing have recently enabled the creation of previously infeasible chemical reactor designs. Optimizing the geometry of the next generation of chemical reactors is important to understand the underlying physics and to ensure reactor feasibility in the real world. This optimization problem is computationally expensive

An Chen, Wenbo Xu, Liyang Lu, Yue Wang

In frequency division duplex (FDD) massive MIMO systems, reliable downlink channel estimation is essential for the subsequent data transmission but is realized at the cost of massive pilot overhead due to hundreds of antennas at base station (BS). In order to reduce the pilot overhead without compromising the estimation, compressive sensing (CS) based method

Bernd Riederer, Axel Maas

Vector boson scattering (VBS) plays a central role in the search for new physics at collider experiments such as ATLAS and CMS at the LHC. Usually predictions for this kind of process are obtained using mainly perturbative approaches in fixed gauges. Here we present a fully gauge-invariant study of VBS in the scalar-channel involving three different types of

Mohsen Asgharzadeh, Mohammad Golshani, Saharon Shelah

For a given cardinal $\lambda$ and a torsion abelian group $K$ of cardinality less than $\lambda$, we present, under some mild conditions (for example $\lambda=\lambda^{\aleph_0}$), boundedly endo-rigid abelian group $G$ of cardinality $\lambda$ with $Tor(G)=K$. Essentially, we give a complete characterization of such pairs $(K, \lambda)$. Among other things

Eason Chen

In this research, by responding to users' utterances with multiple replies to create a group chat atmosphere, we alleviate the problem that Natural Language Generation chatbots might reply with inappropriate content, thus causing a bad user experience. Because according to our findings, users tend to pay attention to appropriate replies and ignore inappropri

Ryan Donnelly, Zi Li

Agents attempt to maximize expected profits earned by selling multiple units of a perishable product where their revenue streams are affected by the prices they quote as well as the distribution of other prices quoted in the market by other agents. We propose a model which captures this competitive effect and directly analyze the model in the mean-field limi

Shuai Sun, Christopher Gilliam, Kamran Ghorbani, Glenn Matthews

Simultaneous localization and mapping (SLAM) using automotive radar sensors can provide enhanced sensing capabilities for autonomous systems. In SLAM applications, with a greater requirement for the environment map, information on the extent of landmarks is vital for precise navigation and path planning. Although object extent estimation has been successfull

Pierluca Carenza, Pedro De la Torre Luque

The elusive nature of Dark Matter (DM) remains a mystery far from being solved. A vast effort is dedicated to search for signatures of feeble DM interactions with Standard Model particles. In this work, we explore the signatures of axion DM boosted by interactions with Supernova neutrinos: Neutrino-Boosted Axion DM ($\nu$BADM). We focus on $\nu$BADM converti

A. J. Cooper, O. Gupta, Z. Wadiasingh, R. A. M. J. Wijers

We investigate pre-merger coherent radio emission from neutron star mergers arising due to the magnetospheric interaction between compact objects. We consider two plausible radiation mechanisms, and show that if one neutron star has a surface magnetic field $B_{\rm s} \ge 10^{12}$G, coherent millisecond radio bursts with characteristic temporal morphology an

Johannes Buchner

For building the super-massive black hole population within a Hubble time, only sub-populations with more than 10^52 erg/s / L objects on the sky are relevant, where L is the sample-averaged bolometric luminosity.

Vaibhav Chimalgi, Bihalan Bhattacharya, Suchetana Goswami, Samyadeb Bhattacharya

The problem of entanglement detection is a long standing problem in quantum information theory. One of the primary procedures of detecting entanglement is to find the suitable positive but non-completely positive maps. Here we try to give a generic prescription to construct a positive map that can be useful for such scenarios. We study a class of positive ma

Guann-Yng Jiang, Cheng-Shang Chang

The multichannel rendezvous problem is a fundamental problem for neighbor discovery in many IoT applications. The existing works in the literature focus mostly on improving the worst-case performance, and the average-case performance is often not as good as that of the random algorithm. As IoT devices (users) are close to each other, their available channel