February 2024 arXiv papers — page 149

David Bachmann, Mathieu Isoard, Vyacheslav Shatokhin, Giacomo Sorelli

Wave propagation through random continuous media remains an important fundamental problem with applications ranging from remote sensing to quantum communication. Typically, such media are characterized by smooth refractive index fluctuations whose impact on the wave can be captured by the stochastic parabolic equation. The latter can be solved numerically by

Zach Evans, CJ Carr, Josiah Taylor, Scott H. Hawley

Generating long-form 44.1kHz stereo audio from text prompts can be computationally demanding. Further, most previous works do not tackle that music and sound effects naturally vary in their duration. Our research focuses on the efficient generation of long-form, variable-length stereo music and sounds at 44.1kHz using text prompts with a generative model. St

Philipp Sadler, Sherzod Hakimov, David Schlangen

Albrecht and Stone (2018) state that modeling of changing behaviors remains an open problem "due to the essentially unconstrained nature of what other agents may do". In this work we evaluate the adaptability of neural artificial agents towards assumed partner behaviors in a collaborative reference game. In this game success is achieved when a knowledgeable

Mihaela Cătălina Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz

Deep Generative Models (DGMs) have been shown to be powerful tools for generating tabular data, as they have been increasingly able to capture the complex distributions that characterize them. However, to generate realistic synthetic data, it is often not enough to have a good approximation of their distribution, as it also requires compliance with constrain

Jinge Zhang, Hamish A. S. Reid, Eoin Carley, Laurent Lamy

Solar radio U-bursts are generated by electron beams traveling along closed magnetic loops in the solar corona. Low-frequency ($<$ 100 MHz) U-bursts serve as powerful diagnostic tools for studying large-sized coronal loops that extend into the middle corona. However, the positive frequency drift component (descending leg) of U-bursts has received less attent

Thuan Trang, Nhat Khang Ngo, Daniel Levy, Thieu N. Vo

Triangular meshes are widely used to represent three-dimensional objects. As a result, many recent works have address the need for geometric deep learning on 3D mesh. However, we observe that the complexities in many of these architectures does not translate to practical performance, and simple deep models for geometric graphs are competitive in practice. Mo

Arjun S. Lakshmipathy, Jessica K. Hodgins, Nancy S. Pollard

Hand motion capture data is now relatively easy to obtain, even for complicated grasps; however this data is of limited use without the ability to retarget it onto the hands of a specific character or robot. The target hand may differ dramatically in geometry, number of degrees of freedom (DOFs), or number of fingers. We present a simple, but effective frame

Philippe Brax, Clare Burrage, Jose A. R. Cembranos, Patrick Valageas

We consider the phase shift in the gravitational wave signal induced by fast oscillations of scalar dark matter surrounding binary systems, which could be probed by the future experiments LISA and DECIGO. This effect depends on the local matter density and the mass of the dark matter particle. We compare it to the phase shift due to a standard dynamical fric

Abderrahmane Boudi, Malik Loudini

Active Queue Management (AQM) is a key congestion control scheme that aims to find a balance between keeping high link utilization, minimizing queuing delays, and ensuring a fair share of the bandwidth between the competing flows. Traditional AQM mechanisms use only information that is present at the intermediate nodes (routers). They do not take into accoun

Tafat Weiss-Attia, Martin Schäfer, Betzalel Bazak

Lattice quantum chromodynamics (LQCD) calculations with physical pion mass would revolutionize nuclear physics by enabling predictions based on the fundamental theory of the strong force. To bridge the gap between finite-volume LQCD results and free-space physical observables, two primary extrapolation methods have been employed so far. The traditional appro

Amin Karimi Monsefi, Pouya Shiri, Ahmad Mohammadshirazi, Nastaran Karimi Monsefi

Reducing traffic accidents is a crucial global public safety concern. Accident prediction is key to improving traffic safety, enabling proactive measures to be taken before a crash occurs, and informing safety policies, regulations, and targeted interventions. Despite numerous studies on accident prediction over the past decades, many have limitations in ter

Victor Porée, Dariusz J. Gawryluk, Tian Shang, J. Alberto Rodríguez-Velamazań

Layered perovskites of general formula AA'CuFeO$_5$ are one of the few examples of cycloidal spiral magnets where the ordering temperatures $T_{spiral}$ can be tuned far beyond room temperature by introducing modest amounts of Cu/Fe chemical disorder in the crystal structure. This rare property makes these materials prominent candidates to host multiferroici

Giuliano Basso

This is an erratum to the article: "Computation of maximal projection constants" (J. Funct. Anal., 277). The statement of Lemma 3.1(2) of that paper is incorrect. As a consequence of this the proof of Theorem 1.4 is incomplete. In this erratum we prove a corrected version of Lemma 3.1 and explain why, with this weaker result, our original strategy for provin

Zong-Kai Liu, Kong-Hao Sun, Albert Cabot, Federico Carollo

Quantum many-body systems near phase transitions respond collectively to externally applied perturbations. We explore this phenomenon in a laser-driven dissipative Rydberg gas that is tuned to a bistable regime. Here two metastable phases coexist, which feature a low and high density of Rydberg atoms, respectively. The ensuing collective dynamics, which we m

Roshni . R. Kamath, Rupert Mitchell, Subarnaduti Paul, Kristian Kersting

Traditional machine learning excels on static benchmarks, but the real world is dynamic and seldom as carefully curated as test sets. Practical applications may generally encounter undesired inputs, are required to deal with novel information, and need to ensure operation through their full lifetime - aspects where standard deep models struggle. These three

Gaurav N. Gadbail, Simran Arora, P. K. Sahoo, Kazuharu Bamba

We study the bounce cosmology to construct a singularity-free $f(\mathcal{R})$ model using the reconstruction technique. The formulation of the $f(\mathcal{R})$ model is based on the Raychaudhari equation, a key element employed in reconstructed models to eliminate singularities. We explore the feasibility of obtaining stable gravitational Lagrangians, adher

Lois Rink, Job Meijdam, David Graus

Understanding preferences, opinions, and sentiment of the workforce is paramount for effective employee lifecycle management. Open-ended survey responses serve as a valuable source of information. This paper proposes a machine learning approach for aspect-based sentiment analysis (ABSA) of Dutch open-ended responses in employee satisfaction surveys. Our appr

J. Ryan Stinnett, Stephen Kell

Many debugging tools rely on compiler-produced metadata to present a source-language view of program states, such as variable values and source line numbers. While this tends to work for unoptimised programs, current compilers often generate only partial debugging information in optimised programs. Current approaches for measuring the extent of coverage of l

Zhangnan Hu, Bing Li

Let $T\colon\mathbb{T}^d\to \mathbb{T}^d$, defined by $T x=Ax(\bmod 1)$, where $A$ is a $d\times d$ integer matrix with eigenvalues $1<|\lambda_1|\le|\lambda_2|\le\dots\le|\lambda_d|$. We investigate the Hausdorff dimension of the recurrence set \[R(\psi):=\{x\in\mathbb{T}^d\colon T^nx\in B(x,\psi(n)) {\rm ~for~infinitely~ many~}n\}\] for $\alpha\ge\log|\lam

Lars Diening, Kyeongbae Kim, Ho-Sik Lee, Simon Nowak

The aim of this work is to establish numerous interrelated gradient estimates in the nonlinear nonlocal setting. First of all, we prove that weak solutions to a class of homogeneous nonlinear nonlocal equations of possibly arbitrarily low order have H\"{o}lder continuous gradients. Using these estimates in the homogeneous case, we then prove sharp higher dif

Christian Acal, Ana M. Aguilera

The methodological contribution in this paper is motivated by biomechanical studies where data characterizing human movement are waveform curves representing joint measures such as flexion angles, velocity, acceleration, and so on. In many cases the aim consists of detecting differences in gait patterns when several independent samples of subjects walk or ru

Koen Vellenga, H. Joe Steinhauer, Alexander Karlsson, Göran Falkman

Driver intention recognition studies increasingly rely on deep neural networks. Deep neural networks have achieved top performance for many different tasks, but it is not a common practice to explicitly analyse the complexity and performance of the network's architecture. Therefore, this paper applies neural architecture search to investigate the effects of

Krzysztof Langner, Francesco Marzari, Alessandro Rossi, Giovanni Zanotti

In 2022 the DART mission spacecraft impacted the asteroid Dimorphos, the secondary body of the binary Didymos system, ejecting a large number of dust particles, rocks and boulders. The ESA Hera mission will reach the system in 2026 for post--impact studies and possible detection of orbiting fragments. We investigate the long term dynamics of the large boulde

Sven Nordebo, Martin Stumpf

This paper presents a systematic approach to derive physical bounds for Positive Real (PR) functions directly in the Time-Domain (TD). The theory is based on Cauer's representation of an arbitrary PR function together with associated sum rules (moments of the measure) and exploits the unilateral Laplace transform to derive rigorous bounds on the TD response

Rehan Ahmad, Muhammad Umar Farooq, Thomas Hain

In Automatic Speech Recognition (ASR), teacher-student (T/S) training has shown to perform well for domain adaptation with small amount of training data. However, adaption without ground-truth labels is still challenging. A previous study has shown the effectiveness of using ensemble teacher models in T/S training for unsupervised domain adaptation (UDA) but

A. Rodriguez-Prieto, D. R. Bowler

In this paper we use density-functional theory calculations to analyze both the stability and diffusion of Cu adatoms near and on the H-passivated Si(001) surface. Two different Cu sources are considered: depositing Cu from vacuum, and contaminating Cu outdiffusing from bulk Si. Deposited Cu from vacuum quickly moves subsurface to an interstitial site in the

Jesús A. Álvarez López, Yuri A. Kordyukov, Eric Leichtnam

Let $F$ be a transversely oriented foliation of codimension 1 on a closed manifold $M$, and let $\phi=\{\phi^t\}$ be a foliated flow on $(M,F)$. Assume the closed orbits of $\phi$ are simple and its preserved leaves are transversely simple. In this case, there are finitely many preserved leaves, which are compact. Let $M^0$ denote their union, $M^1=M\setminu

Luis Sanz, Rafael Bravo de la Parra, Marcos Marvá, Eva Sánchez

In this work we present a reduction result for discrete time systems with two time scales. In order to be valid, previous results in the field require some strong hypotheses that are difficult to check in practical applications. Roughly speaking, the iterates of a map as well as their differentials must converge uniformly on compact sets. Here, we eliminate

Yannick Weiser, Tommaso Faorlin, Lorenz Panzl, Thomas Lafenthaler

Levitated dipolar scatterers exhibit exceptional performance as optomechanical systems for observing quantum mechanics at the mesoscopic scale. However, their tendency to scatter light in almost any direction poses experimental challenges, in particular limiting light collection efficiencies and, consequently, the information extractable from the system. In

Ali Rajabpour, Julien El Hajj, Mauricio Gómez Viloria, Riccardo Messina

Despite recent experiments exhibiting an impressive enhancement in radiative heat flux between parallel planar silica surfaces with gap sizes of about 10 nm, the exploration of sub-nanometric gap distances remains unexplored. In this work, by employing non-equilibrium molecular dynamics (NEMD) simulations, we study the heat transfer between two SiO2 plates i

T. Signor, G. Rodighiero, L. Bisigello, M. Bolzonella

Dusty, distant, massive ($M_*\gtrsim 10^{11}\,\rm M_\odot$) galaxies are usually found to show a remarkable star-formation activity, contributing on the order of $25\%$ of the cosmic star-formation rate density at $z\approx3$--$5$, and up to $30\%$ at $z\sim7$ from ALMA observations. Nonetheless, they are elusive in classical optical surveys, and current nea

Sana Hafeez, Habib Ullah Manzoor, Lina Mohjazi, Ahmed Zoha

Exploiting unmanned aerial vehicles (UAVs) for delivery services is expected to reduce delivery time and human resource costs. However, the proximity of these UAVs to the ground can make them an ideal target for opportunistic criminals. Consequently, UAVs may be hacked, diverted from their destinations, or used for malicious purposes. Furthermore, as a decen

Daniel Dadush, Akshay Ramachandran

The frame scaling problem is: given vectors $U := \{u_{1}, ..., u_{n} \} \subseteq \mathbb{R}^{d}$, marginals $c \in \mathbb{R}^{n}_{++}$, and precision $\varepsilon > 0$, find left and right scalings $L \in \mathbb{R}^{d \times d}, r \in \mathbb{R}^n$ such that $(v_1,\dots,v_n) := (Lu_1 r_1,\dots,Lu_nr_n)$ simultaneously satisfies $\sum_{i=1}^n v_i v_i^{\ma

Mingxuan Liu, Jiankai Tang, Yongli Chen, Haoxiang Li

Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, most existing ANN-based methods require substantial computing resources, which poses challenges for effective

Taha Bouzid, Youssef Alj

In this paper, we propose a new visual navigation method based on a single RGB perspective camera. Using the Visual Teach & Repeat (VT&R) methodology, the robot acquires a visual trajectory consisting of multiple subgoal images in the teaching step. In the repeat step, we propose two network architectures, namely ViewNet and VelocityNet. The combination of t

Lin Gao, Jie Yang, Bo-Tao Zhang, Jia-Mu Sun

Neural implicit representations, including Neural Distance Fields and Neural Radiance Fields, have demonstrated significant capabilities for reconstructing surfaces with complicated geometry and topology, and generating novel views of a scene. Nevertheless, it is challenging for users to directly deform or manipulate these implicit representations with large

Thomas Mejstrik, Vladimir Yu. Protasov

We decide the stability and compute the Lyapunov exponent of continuous-time linear switching systems with a guaranteed dwell time. The main result asserts that the discretization method with step size~$h$ approximates the Lyapunov exponent with the precision~$C\,h^2$, where~$C$ is a constant. Let us stress that without the dwell time assumption, the approxi

Chakib Fettal, Lazhar Labiod, Mohamed Nadif

The proliferation of high-dimensional data from sources such as social media, sensor networks, and online platforms has created new challenges for clustering algorithms. Multi-view clustering, which integrates complementary information from multiple data perspectives, has emerged as a powerful solution. However, existing methods often struggle with scalabili

Joanna Rencławowicz, Wojciech M. Zajączkowski

The nonhomogeneous Navier-Stokes equations are considered in a cylindrical domain in ${\mathbb R}^3$, parallel to the $x_3$-axis with large inflow and outflow on the top and the bottom. Moreover, on the lateral part of the cylinder the slip boundary conditions are assumed. The global existence of regular solutions is proved under assumptions that inflow and

Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu

Direct alignment from preferences (DAP) methods, such as DPO, have recently emerged as efficient alternatives to reinforcement learning from human feedback (RLHF), that do not require a separate reward model. However, the preference datasets used in DAP methods are usually collected ahead of training and never updated, thus the feedback is purely offline. Mo

Maria Axenovich, Dingyuan Liu

A subset $M$ of vertices in a graph $G$ is a mutual-visibility set if any two vertices $u$ and $v$ in $M$ ``see'' each other in $G$, that is, there exists a shortest $u,v$-path in $G$ that contains no elements of $M$ as internal vertices. The mutual-visibility number $\mu(G)$ of a graph $G$ is the largest size of a mutual-visibility set in $G$. Let $n\in\mat

Eduardo Latorre Iglesias, David Thompson, Jorge Muñoz Paniagua, Javier García García

At speeds above 300 km/h, aerodynamic noise becomes a significant source of railway noise. In a high-speed train, the bogie area is one of the most important aerodynamic noise sources. To predict aerodynamic noise, semi-empirical component-based models are attractive as they allow fast and cheap calculations compared with numerical methods. Such component-ba

Loïc Dubois

On an orientable surface $S$, consider a collection $\Gamma$ of closed curves. The (geometric) intersection number $i_S(\Gamma)$ is the minimum number of self-intersections that a collection $\Gamma'$ can have, where $\Gamma'$ results from a continuous deformation (homotopy) of $\Gamma$. We provide algorithms that compute $i_S(\Gamma)$ and such a $\Gamma'$,

Muhammad Firdaus, Kyung-Hyune Rhee

The popularity of federated learning (FL) is on the rise, along with growing concerns about data privacy in artificial intelligence applications. FL facilitates collaborative multi-party model learning while simultaneously ensuring the preservation of data confidentiality. Nevertheless, the problem of statistical heterogeneity caused by the presence of diver

Dongping Chen, Ruoxi Chen, Shilin Zhang, Yinuo Liu

Multimodal Large Language Models (MLLMs) have gained significant attention recently, showing remarkable potential in artificial general intelligence. However, assessing the utility of MLLMs presents considerable challenges, primarily due to the absence of multimodal benchmarks that align with human preferences. Drawing inspiration from the concept of LLM-as-

Sana Hafeez, Lina Mohjazi, Muhammad Ali Imran, Yao Sun

Privacy, scalability, and reliability are significant challenges in unmanned aerial vehicle (UAV) networks as distributed systems, especially when employing machine learning (ML) technologies with substantial data exchange. Recently, the application of federated learning (FL) to UAV networks has improved collaboration, privacy, resilience, and adaptability,

Marc Braun, Jenny Kunz

The self-rationalising capabilities of LLMs are appealing because the generated explanations can give insights into the plausibility of the predictions. However, how faithful the explanations are to the predictions is questionable, raising the need to explore the patterns behind them further. To this end, we propose a hypothesis-driven statistical framework.

Yan-Jie Min, De-Quan Zhu, Jin-Hua Zhao

Buffon-Laplace Needle Problem considers a needle of a length $l$ randomly dropped on a large plane distributed with vertically parallel lines with distances $a$ and $b$ ($a \geqslant b$), respectively. As a classical problem in stochastic probability, it serves as a mathematical basis of various physical literature, such as the efficiency of a filter and the

Larisa V. Arapkina, Kirill V. Chizh, Oleg V. Uvarov, Valery V. Voronov

We present Raman spectroscopy of the polycrystalline Si and Ge films deposited by molecular beam deposition on a dielectric substrate. The Raman study has been made using lasers with different wavelengths. Structural properties of the poly-films have been studied by XRD and TEM. The Raman spectra are characterized by appearance of the additional wide peaks a

Inmaculada Gutiérrez, Daniel Gómez, Javier Castro, Rosa Espínola

In this paper we introduce the concept of multiple bipolar fuzzy measures as a generalization of a bipolar fuzzy measure. We also propose a new definition of a group, which is based on the multidimensional bipolar fuzzy relations of its elements. Taking into account this information, we provide a novel procedure (based on the well-known Louvain algorithm) to

Alexander Tyurin, Marta Pozzi, Ivan Ilin, Peter Richtárik

We consider nonconvex stochastic optimization problems in the asynchronous centralized distributed setup where the communication times from workers to a server can not be ignored, and the computation and communication times are potentially different for all workers. Using an unbiassed compression technique, we develop a new method-Shadowheart SGD-that provab

Laura Breitkopf, Marc Kesseböhmer, Anke Pohl

In the framework of infinite ergodic theory, we derive equidistribution results for suitable weighted sequences of cusp points of Hecke triangle groups encoded by group elements of constant word length with respect to a set of natural generators. This is a generalization of the corresponding results for the modular group, for which we rely on advanced result

Hemanth Saratchandran, Shin-Fang Chng, Simon Lucey

Recently, neural networks utilizing periodic activation functions have been proven to demonstrate superior performance in vision tasks compared to traditional ReLU-activated networks. However, there is still a limited understanding of the underlying reasons for this improved performance. In this paper, we aim to address this gap by providing a theoretical un

Inmaculada Gutiérrez, Daniel Gómez, Javier Castro, Rosa Espínola

On the basis of network analysis, and within the context of modeling imprecision or vague information with fuzzy sets, we propose an innovative way to analyze, aggregate and apply this uncertain knowledge into community detection of real-life problems. This work is set on the existence of one (or multiple) soft information sources, independent of the network

Alain Mazzolo

The probability density is a fundamental quantity for characterizing diffusion processes. However, it is seldom known except in a few renowned cases, including Brownian motion and the Ornstein-Uhlenbeck process and their bridges, geometric Brownian motion, Brownian excursion, or Bessel processes. In this paper, we utilize Girsanov's theorem, along with a var

O. Contreras-Vergara, G. Valencia-Ortega, N. Sánchez-Salas, J. I. Jiménez-Aquino

This paper focuses on the coefficient of performance (COP) at maximum figure of merit $\chi$ for a Brownian Carnot-like refrigerator, within the context of symmetric Low-Dissipation approach. Our proposal is based on the Langevin equation for a Brownian particle bounded to a harmonic potential trap, which can perform Carnot-like cycles at finite time. We sho

Qingyu Yin, Xuzheng He, Xiang Zhuang, Yu Zhao

The decoder-only Transformer architecture with causal masking and relative position encoding (RPE) has become the de facto choice in language modeling. Despite its exceptional performance across various tasks, we have identified two limitations: First, it requires all attention scores to be non-zero and sum up to 1, even if the current embedding has sufficie

Yao Yao, Taiki Inoue, Makoto Takamura, Yoshitaka Taniyasu

We investigated the growth of twisted graphene on graphene/silicon carbide (SiC-G) templates by metal-free chemical vapor deposition (CVD) through a sequential thermal (ST) process, which exploits the ultraclean surface of SiC-G without exposing the surface to air before CVD. By conducting control experiments with SiC-G templates exposed to air (AirE process

Zhongyi Hu, Robin Evans

\emph{Maximal ancestral graph} (MAGs) is a class of graphical model that extend the famous \emph{directed acyclic graph} in the presence of latent confounders. Most score-based approaches to learn the unknown MAG from empirical data rely on BIC score which suffers from instability and heavy computations. We propose to use the framework of imsets \citep{stude

Daniel Celeny, Loïc Maréchal

We extract firms' cyber risk with a machine learning algorithm measuring the proximity between their disclosures and a dedicated cyber corpus. Our approach outperforms dictionary methods, uses full disclosure and not devoted-only sections, and generates a cyber risk measure uncorrelated with other firms' characteristics. We find that a portfolio of US-listed

Inmaculada Gutiérrez, Javier Castro, Daniel Gómez, Rosa Espínola

In this paper we address the problem of fuzzy measures index calculation. On the basis of fuzzy sets, Murofushi and Soneda proposed an interaction index to deal with the relations between two individuals. This index was later extended in a common frame-work by Grabisch. Both indices are fundamental in the literature of fuzzy measures. Nevertheless, the corre

Daniel Celeny, Loïc Maréchal, Evgueni Rousselot, Alain Mermoud

Along with the increasing frequency and severity of cyber incidents, understanding their economic implications is paramount. In this context, listed firms' reactions to cyber incidents are compelling to study since they (i) are a good proxy to estimate the costs borne by other organizations, (ii) have a critical position in the economy, and (iii) have their

Harshit Bajpai, Gaurav Mittal, Ankik Kumar Giri

In this study, we present and analyze a novel variant of the stochastic gradient descent method, referred as Stochastic data-driven Bouligand Landweber iteration tailored for addressing the system of non-smooth ill-posed inverse problems. Our method incorporates the utilization of training data, using a bounded linear operator, which guides the iterative pro

Javier Castro, Rosa Espínola, Inmaculada Gutiérrez, Daniel Gómez

In this paper we define a new auction, called the Draw auction. It is based on the implementation of a draw when a minimum price of sale is not reached. We find that a Bayesian Nash equilibrium is reached in the Draw auction when each player bids his true personal valuation of the object. Furthermore, we show that the expected profit for the seller in the Dr

Jose-Luis Perez-Diaz, Efren Diez-Jimenez, Ignacio Valiente-Blanco, Javier Herrero-de-Vicente

Forces and torques exerted by a superconducting torus on a permanent magnet have been mapped. It is demonstrated that stable orbits exist. Moreover, provided that the magnet remains in any of these orbits, the first critical field in the superconductor is never overpassed and the superconductor remains in the Meissner state. The consequent absence of hystere

Arpan Akash Ray, Boris Skoric

Continuous-Variable Quantum Key Distribution (CVQKD) at large distances has such high noise levels that the error-correcting code must have very low rate. In this regime it becomes feasible to implement random-codebook error correction, which is known to perform close to capacity. We propose a reverse reconciliation scheme for CVQKD in which the first step i

Hung Duy Nguyen, Minh Nhat Vu, Nguyen Ngoc Nam, Kyoungseok Han

Driving vehicles in complex scenarios under harsh conditions is the biggest challenge for autonomous vehicles (AVs). To address this issue, we propose hierarchical motion planning and robust control strategy using the front-active steering system in complex scenarios with various slippery road adhesion coefficients while considering vehicle uncertain paramet

Esteve Valls Mascaro, Yashuai Yan, Dongheui Lee

Integrating robots into populated environments is a complex challenge that requires an understanding of human social dynamics. In this work, we propose to model social motion forecasting in a shared human-robot representation space, which facilitates us to synthesize robot motions that interact with humans in social scenarios despite not observing any robot

Özgür Akarsu, Eoin Ó Colgáin, Anjan A. Sen, M. M. Sheikh-Jabbari

$\Lambda$CDM tensions are by definition model dependent; one sees anomalies through the prism of $\Lambda$CDM. Thus, progress towards tension resolution necessitates checking the consistency of the $\Lambda$CDM model to localise missing physics either in redshift or scale. Since the Universe is dynamical and redshift is a proxy for time, it is imperative to

Alena Jarolímová, Jaroslav Hron

One of the crucial aspects of patient-specific blood flow simulations is to specify material parameters and boundary conditions. The choice of boundary conditions can have a substantial impact on the character of the flow. While no-slip is the most popular wall boundary condition, some amount of slip, which determines how much fluid is allowed to flow along

Loïc Maréchal, Alain Mermoud, Dimitri Percia David, Mathias Humbert

Early-stage firms play a significant role in driving innovation and creating new products and services, especially for cybersecurity. Therefore, evaluating their performance is crucial for investors and policymakers. This work presents a financial evaluation of early-stage firms' performance in 19 cybersecurity sectors using a private-equity dataset from 201

David Venuto, Sami Nur Islam, Martin Klissarov, Doina Precup

Pre-trained Vision-Language Models (VLMs) are able to understand visual concepts, describe and decompose complex tasks into sub-tasks, and provide feedback on task completion. In this paper, we aim to leverage these capabilities to support the training of reinforcement learning (RL) agents. In principle, VLMs are well suited for this purpose, as they can nat

Fuda van Diggelen, Matteo De Carlo, Nicolas Cambier, Eliseo Ferrante

Natural groups of animals, such as swarms of social insects, exhibit astonishing degrees of task specialization, useful to address complex tasks and to survive. This is supported by phenotypic plasticity: individuals sharing the same genotype that is expressed differently for different classes of individuals, each specializing in one task. In this work, we e

Nizamuddin Maitlo, Nooruddin Noonari, Sajid Ahmed Ghanghro, Sathishkumar Duraisamy

Light plays a vital role in vision either human or machine vision, the perceived color is always based on the lighting conditions of the surroundings. Researchers are working to enhance the color detection techniques for the application of computer vision. They have implemented proposed several methods using different color detection approaches but still, th

J. M. Campillo Robles, E. Ogando, F. Plazaola

Theoretical positron lifetime values have been calculated systematically for most of the elements of the Periodic Table. Self-consistent and non-self-consistent schemes have been used for the calculation of the electronic structure in the solid, as well as different parameterizations for the positron enhancement factor and correlation energy. The results obt

Davi Lazzarotto, Michela Testolina, Touradj Ebrahimi

The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as MPEG and JPEG Pleno to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual artifacts that negatively impact the perceived quality of media, which can only be reliably measured t

Corinne Berat, Antonio Condorelli, Olivier Deligny, Francois Montanet

The search for neutrinos with energies greater than $10^{17}~$eV is being actively pursued. Although normalization of the dominant neutrino flux is highly uncertain, a floor level is guaranteed by the interactions of extragalactic cosmic rays with Milky Way gas. We estimate that this floor level gives an energy flux of $E^2\phi_\nu\simeq 10^{-13^{+0.5}_{-0.5

Niu Chence, Purvi Rastogi, Jaikishan Soman, Kausik Tamuli

In this paper, the multicommodity network flow (MCNF) problem is formulated as a mixed integer programing model which is known as NP-hard, aiming to optimize the vehicle routing and minimize the total travel cost. We explore the potential of quantum computing, specifically quantum annealing, by comparing its performance in terms of solution quality and effic

Ronaldo F. de Lima, Álvaro K. Ramos, João Paulo dos Santos

We establish the existence of one-parameter families of helicoidal surfaces of $\mathbb H^2\times\mathbb R$ which, under mean curvature flow, simultaneously rotate about a vertical axis and translate vertically.

Ye Zhang, Ziyue Wang, Yifeng Wang, Hao Bian

Semi-supervised segmentation methods have demonstrated promising results in natural scenarios, providing a solution to reduce dependency on manual annotation. However, these methods face significant challenges when directly applied to pathological images due to the subtle color differences between nuclei and tissues, as well as the significant morphological

MAGIC Collaboration, S. Abe, J. Abhir, V. A. Acciari

In recent years, a new generation of optical intensity interferometers has emerged, leveraging the existing infrastructure of Imaging Atmospheric Cherenkov Telescopes (IACTs). The MAGIC telescopes host the MAGIC-SII system (Stellar Intensity Interferometer), implemented to investigate the feasibility and potential of this technique on IACTs. After the first

Jian Chen, Ruiyi Zhang, Yufan Zhou, Rajiv Jain

Controllable layout generation refers to the process of creating a plausible visual arrangement of elements within a graphic design (e.g., document and web designs) with constraints representing design intentions. Although recent diffusion-based models have achieved state-of-the-art FID scores, they tend to exhibit more pronounced misalignment compared to ea

Zhenshan Xie, Simon Dahan, Logan Z. J. Williams, M. Jorge Cardoso

Cortical surface analysis has gained increased prominence, given its potential implications for neurological and developmental disorders. Traditional vision diffusion models, while effective in generating natural images, present limitations in capturing intricate development patterns in neuroimaging due to limited datasets. This is particularly true for gene

Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar

Action-constrained reinforcement learning (ACRL) is a popular approach for solving safety-critical and resource-allocation related decision making problems. A major challenge in ACRL is to ensure agent taking a valid action satisfying constraints in each RL step. Commonly used approach of using a projection layer on top of the policy network requires solving

Tomasz Klimsiak, Tomasz Komorowski, Lorenzo Marino

We show homogenization for a family of $\mathbb{R}^d$-valued stable-like processes $(X_t^{\epsilon;\theta})_{t\ge 0}$, $\epsilon\in(0,1]$, whose (random) Fourier symbols equal $q_\epsilon(x,\xi;\theta)=\frac{1}{\epsilon^{\alpha}}q(x/\epsilon,\epsilon\xi; \theta)$, where$$q(x,\xi; \theta)=\int_{\mathbb{R}^d}\big(1-e^{i y\cdot\xi}+iy\cdot\xi\mathds{1}_{\{|y|\l

Koki Okajima, Takashi Takahashi

This study investigates the dynamics of alternating minimization applied to a bilinear regression task with normally distributed covariates, under the asymptotic system size limit where the number of parameters and observations diverge at the same rate. This is achieved by employing the replica method to a multi-temperature glassy system which unfolds the al

Nizamuddin Maitlo, Nooruddin Noonari, Kaleem Arshid, Naveed Ahmed

Recently, researchers have been exploring various ways to improve the effectiveness and efficiency of autonomous vehicles by researching new methods, especially for indoor scenarios. Autonomous Vehicles in indoor navigation systems possess many challenges especially the limited accuracy of GPS in indoor scenarios. Several, robust methods have been explored f

Katsumasa Tanaka, Kushal Tibrewal, Philippe Ciais, Olivier Boucher

The Global Methane Pledge and other methane measures may potentially undermine CO2 mitigation in certain countries, unless they are considered as additional to the existing Nationally Determined Contributions to strengthen overall greenhouse gas emission targets. Maintaining the progress on CO2 mitigation in the revision of Nationally Determined Contribution

Junliang Wang, Hermann Edlbauer, Baptiste Jadot, Tristan Meunier

The displacement of a single electron enables exciting avenues for nanotechnology with vast application potential in quantum metrology, quantum communication and quantum computation. Surface acoustic waves (SAW) have proven itself as a surprisingly useful solution to perform this task over large distance with outstanding precision and reliability. Over the l

Rubén Medina, Andrés Quilis

We construct a Banach space satisfying that the nearest point map (also called proximity mapping or metric projection) onto any compact and convex subset is continuous but not uniformly continuous. The space we construct is locally uniformly convex, which ensures the continuity of all these nearest point maps. Moreover, we prove that every infinite-dimension

Adri Bhattacharya, Giuseppe F. Italiano, Partha Sarathi Mandal

We investigate the black hole search problem by a set of mobile agents in a dynamic torus. Black hole is defined to be a dangerous stationary node which has the capability to destroy any number of incoming agents without leaving any trace of its existence. A torus of size $n\times m$ ($3\leq n \leq m$) is a collection of $n$ row rings and $m$ column rings, a

Gang V. Chen

Motivated by the experiments on the triangular lattice bilayer colbaltate K$_2$Co$_2$(SeO$_3$)$_3$, we formulate a theory to explore the underlying physics from a couple observation. The model is composed of interacting Co$^{2+}$ dimers on the triangular lattice, where the Co$^{2+}$ ion provides an effective spin-1/2 local moment via the spin-orbit coupling

Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao

N:M Structured sparsity has garnered significant interest as a result of relatively modest overhead and improved efficiency. Additionally, this form of sparsity holds considerable appeal for reducing the memory footprint owing to their modest representation overhead. There have been efforts to develop training recipes for N:M structured sparsity, they primar

Catarina Cosme, Francesco Costa, Oleg Lebedev

Dark matter freeze-in at stronger coupling is operative when the Standard Model (SM) bath temperature never exceeds the dark matter mass. An attractive feature of this scenario is that it can be probed by direct detection experiments as well as at the LHC. In this work, we show how the mechanism can be realized in a simple UV complete framework, emphasizing

E. Mendieta-Otero, I. Pérez-Álvarez, B. Pérez-Díaz

In this paper, we use jointly a model of narrow band interference and a congestion model to model and implement an interference simulator for the whole HF band. The result is a model to generate interfering signals that could be found in a given frequency allocation, at a given time (past, present, or future) and for a given location. Our model does not requ

Milad Delfan Azari, Hirokazu Sasaki, Tomoya Takiwaki, Hirotada Okawa

We investigate the dynamics of fast neutrino flavor conversions (FFCs) in the one-dimensional (1D) and zero-dimensional (0D) models, in which spatial advection is considered and ignored, respectively. In this study, we employ snapshots obtained by our self-consistent, realistic Boltzmann-neutrino-radiation-hydrodynamics simulations. We show that the FFC grow

Sobin Joseph, Shashi Jain

An extension of the Hawkes process, the Marked Hawkes process distinguishes itself by featuring variable jump size across each event, in contrast to the constant jump size observed in a Hawkes process without marks. While extensive literature has been dedicated to the non-parametric estimation of both the linear and non-linear Hawkes process, there remains a

César Díaz, Julián Cabrera, Fernando Jaureguizar, Narciso García

An optimization technique based on an adapted combination of simulated annealing (SA) and tabu search (TS) is presented. This method aims at finding near-optimal unequal error protection (UEP) application-layer FEC code configurations. This approach is intended to smartly protect audio and video transmission over IP networks when hard time restrictions apply

Dongxin Liu, Oren Elishav, Jiarui Fu, Masaya Sakakibara

Upon melting, the molecules in the crystal explore numerous configurations, reflecting an increase in disorder. The molar entropy of disorder can be defined by Bolzmann's formula dSd = Rln(Wd) where Wd is the increase in the number of microscopic states, so far inaccessible experimentally. We found that the Arrhenius frequency factor A of the electron diffra

Michela Ascolese, Matthias Lienau, Matthias Schulte, Anusch Taraz

The question whether there exists a hypergraph whose degrees are equal to a given sequence of integers is a well-known reconstruction problem in graph theory, which is motivated by discrete tomography. In this paper we approach the problem by randomized algorithms which generate the required hypergraph with positive probability if the sequence satisfies cert