February 2024 arXiv papers — page 119

Alberto Pozanco, Ramon Fraga Pereira, Daniel Borrajo

In Environment Design, one interested party seeks to affect another agent's decisions by applying changes to the environment. Most research on planning environment (re)design assumes the interested party's objective is to facilitate the recognition of goals and plans, and search over the space of environment modifications to find the minimal set of changes t

Nikolas Patris, Stelios Stavroulakis, Fivos Kalogiannis, Rose Zhang

We consider the problem of computing Nash equilibria in potential games where each player's strategy set is subject to private uncoupled constraints. This scenario is frequently encountered in real-world applications like road network congestion games where individual drivers adhere to personal budget and fuel limitations. Despite the plethora of algorithms

Luis G. Varela, Laura E. Boucheron, Steven Sandoval, David Voelz

The non-uniform blur of atmospheric turbulence can be modeled as a superposition of linear motion blur kernels at a patch level. We propose a regression convolutional neural network (CNN) to predict angle and length of a linear motion blur kernel for varying sized patches. We analyze the robustness of the network for different patch sizes and the performance

Predrag M. Rajković, Sladjana D. Marinković, Miomir S. Stanković, Marko D. Petković

This paper deals with the Mittag-Leffler polynomials (MLP) by extracting their essence which consists of real polynomials with fine properties. They are orthogonal on the real line instead of the imaginary axes for MLP. Beside recurrence relations and zeros, we will point to the closed form of its Fourier transform. The most important contribution consists o

Wei Chen, Anzhuo Yu, Zhou Zhou, Lingling Ma

Space-time (ST) beams, ultrafast optical wavepackets with customized spatial and temporal characteristics, present a significant contrast to conventional spatial-structured light and hold the potential to revolutionize our understanding and manipulation of light. However, the progress in ST beam research has been constrained by the absence of a universal fra

Ahmed Khaled, Chi Jin

Large-scale machine learning problems make the cost of hyperparameter tuning ever more prohibitive. This creates a need for algorithms that can tune themselves on-the-fly. We formalize the notion of "tuning-free" algorithms that can match the performance of optimally-tuned optimization algorithms up to polylogarithmic factors given only loose hints on the re

Holger R. Roth, Ziyue Xu, Yuan-Ting Hsieh, Adithya Renduchintala

In the ever-evolving landscape of artificial intelligence (AI) and large language models (LLMs), handling and leveraging data effectively has become a critical challenge. Most state-of-the-art machine learning algorithms are data-centric. However, as the lifeblood of model performance, necessary data cannot always be centralized due to various factors such a

Matthew Litton, Doron Drusinsky, James Bret Michael

Developing and fielding complex systems requires proof that they are reliably correct with respect to their design and operating requirements. Especially for autonomous systems which exhibit unanticipated emergent behavior, fully enumerating the range of possible correct and incorrect behaviors is intractable. Therefore, we propose an optimization-based sear

Agathe Fernandes Machado, Arthur Charpentier, Emmanuel Flachaire, Ewen Gallic

The assessment of binary classifier performance traditionally centers on discriminative ability using metrics, such as accuracy. However, these metrics often disregard the model's inherent uncertainty, especially when dealing with sensitive decision-making domains, such as finance or healthcare. Given that model-predicted scores are commonly seen as event pr

Raffaele Folino, Anna Naumkina, Ramón G. Plaza

In this paper, it is proved that the KdV-Burgers equation with a monostable source term of Fisher-KPP type has small-amplitude periodic traveling wave solutions with finite fundamental period. These solutions emerge from a subcritical local Hopf bifurcation around a critical value of the wave speed. Moreover, it is shown that these periodic waves are spectra

Mingzhe Li, Xiuying Chen, Jing Xiang, Qishen Zhang

Text matching systems have become a fundamental service in most searching platforms. For instance, they are responsible for matching user queries to relevant candidate items, or rewriting the user-input query to a pre-selected high-performing one for a better search experience. In practice, both the queries and items often contain multiple attributes, such a

Xinran Li, Xiaowei Zhao, Yubo Zhu, Zhiheng Zhang

Aspect-based Sentiment Analysis (ABSA) aims to determine sentiment polarity toward specific aspects in text. Existing methods enrich semantic and syntactic representations through external knowledge or GNNs, but the growing diversity of linguistic features increases model complexity and lacks a unified, extensible framework. We propose an Extensible Multi-Gr

Matteo Becchi, Federico Fantolino, Giovanni M. Pavan

Complex systems are typically characterized by intricate internal dynamics that are often hard to elucidate. Ideally, this requires methods that allow to detect and classify in unsupervised way the microscopic dynamical events occurring in the system. However, decoupling statistically relevant fluctuations from the internal noise remains most often non-trivi

Haoyue Bai, Yifei Ming, Julian Katz-Samuels, Yixuan Li

Out-of-distribution (OOD) generalization is critical for machine learning models deployed in the real world. However, achieving this can be fundamentally challenging, as it requires the ability to learn invariant features across different domains or environments. In this paper, we propose a novel framework HYPO (HYPerspherical OOD generalization) that provab

Stefano Menchiari, Giovanni Morlino, Elena Amato, Niccolò Bucciantini

In this paper, we focus on the scientific case of Cygnus OB2, a northern sky young massive stellar cluster (YMSC) located towards the Cygnus X star-forming complex. We consider a model that assumes cosmic ray acceleration occurring only at the termination shock of the collective wind of the YMSC and address the question of whether, and under what hypotheses,

Bernard Dieny, Olivier Fruchart, Ernesto E. Marinero

This paper delves into the origins and specificity of the unique stable spin textures (360{\deg} closed loop domain walls and skyrmions) observed in exchange-biased systems, with either in-plane or out-of-plane magnetic anisotropy. In the case of skyrmions, which are nanometer-sized bubbles consisting of closed-loop 180{\deg} walls in perpendicularly-magneti

Louis Gaillard, Mohab Safey El Din

We consider systems of polynomial equations and inequalities in $\mathbb{Q}[\boldsymbol{y}][\boldsymbol{x}]$ where $\boldsymbol{x} = (x_1, \ldots, x_n)$ and $\boldsymbol{y} = (y_1, \ldots,y_t)$. The $\boldsymbol{y}$ indeterminates are considered as parameters and we assume that when specialising them generically, the set of common complex solutions, to the o

Wenjing Jiang, Vidya A. Chhabria, Sachin S. Sapatnekar

Engineering change orders (ECOs) in late stages make minimal design fixes to recover from timing shifts due to excessive IR drops. This paper integrates IR-drop-aware timing analysis and ECO timing optimization using reinforcement learning (RL). The method operates after physical design and power grid synthesis, and rectifies IR-drop-induced timing degradati

Giovanni P. Galdi, Paolo Maremonti

We give sufficient conditions on the initial data for the decay in time of the kinetic energy, $E$, of solutions to the system of equations describing the motion of a rigid body in a Navier-Stokes liquid. More precisely, assuming the initial data ``small" in appropriate norm, we show that if, in addition, the initial velocity field of the liquid, $v_0$, is i

Dimitrios Charamaras, Andreas Mountakis

In 2022, using methods from ergodic theory, Kra, Moreira, Richter, and Robertson resolved a longstanding conjecture of Erd\H{o}s about sumsets in large subsets of the natural numbers. In this paper, we extend this result to several important classes of amenable groups, including all finitely generated virtually nilpotent groups, and all abelian groups $(G,+)

Jamelle Watson-Daniels

Our focus lies at the intersection between two broader research perspectives: (1) the scientific study of algorithms and (2) the scholarship on race and racism. Many streams of research related to algorithmic fairness have been born out of interest at this intersection. We think about this intersection as the product of work derived from both sides. From (1)

Abhijit Kulkarni, Ahsan Nadeem, Roberta Di Fonso, Yusheng Zheng

Modeling of Li-ion cells is used in battery management systems (BMS) to determine key states such as state-of-charge (SoC), state-of-health (SoH), etc. Accurate models are also useful in developing a cell-level digital-twin that can be used for protection and diagnostics in the BMS. In this paper, a low-complexity model development is proposed based on the e

Hui Liu, Wenya Wang, Haoru Li, Haoliang Li

The proliferation of fake news has emerged as a severe societal problem, raising significant interest from industry and academia. While existing deep-learning based methods have made progress in detecting fake news accurately, their reliability may be compromised caused by the non-transparent reasoning processes, poor generalization abilities and inherent ri

Bhaswar B. Bhattacharya, Sandip Das, Sk Samim Islam, Saumya Sen

Given a set $P$ of $n$ points in the plane, in general position, denote by $N_\Delta(P)$ the number of empty triangles with vertices in $P$. In this paper we investigate by how much $N_\Delta(P)$ changes if a point $x$ is removed from $P$. By constructing a graph $G_P(x)$ based on the arrangement of the empty triangles incident on $x$, we transform this geom

Guy Boyde, Niall Taggart

We describe the Goodwillie calculus of polyhedral products in the case that the fat wedge filtration on the associated real moment-angle complex is trivial. We do this by analysing the behaviour on calculus of the Denham-Suciu fibre sequence, the Iriye-Kishimoto decomposition of the polyhedral product constructed from a collection of pairs of cones and their

Zhi-Guo He, Xiao-Bo Jin, Bernd A. Kniehl

We calculate the relativistic corrections to prompt $J/\psi$ pair and $J/\psi+\psi(2S)$ hadroproduction through the color-singlet channel within the framework of nonrelativistic QCD (NRQCD) factorization. The short-distance coefficients are obtained by matching full-QCD and NRQCD calculations at the partonic level, in which both squared amplitude and phase s

My H Dinh, James Kotary, Ferdinando Fioretto

Many decision processes in artificial intelligence and operations research are modeled by parametric optimization problems whose defining parameters are unknown and must be inferred from observable data. The Predict-Then-Optimize (PtO) paradigm in machine learning aims to maximize downstream decision quality by training the parametric inference model end-to-

Alexander Leonhardt, Ulrich Meyer, Manuel Penschuck

A graph is called a $(k,\rho)$-graph iff every node can reach $\rho$ of its nearest neighbors in at most k hops. This property proved useful in the analysis and design of parallel shortest-path algorithms. Any graph can be transformed into a $(k,\rho)$-graph by adding shortcuts. Formally, the $(k,\rho)$-Minimum-Shortcut problem asks to find an appropriate sh

David Selby, Kai Spriestersbach, Yuichiro Iwashita, Mohammad Saad

Large language models (LLMs) have been extensively studied for their abilities to generate convincing natural language sequences, however their utility for quantitative information retrieval is less well understood. Here we explore the feasibility of LLMs as a mechanism for quantitative knowledge retrieval to aid two data analysis tasks: elicitation of prior

D. Vida, J. M. Scott, A. Egal, J. Vaubaillon

A new meteor shower $\lambda$-Sculptorids produced by the comet 46P/Wirtanen was forecast for December 12, 2023. The predicted activity was highly uncertain, but generally considered to be low. Observations in Australia, New Zealand, and Oceania were solicited to help constrain the size distribution of meteoroids in the shower. This work aims to characterize

Charlie M. Rawlins, Gareth A. Tribello

We run molecular dynamics simulations of folded graphene sheets and present a procedure to measure the sliding friction in these systems based on the rate of decay of a damped-harmonic oscillator. This procedure allowed us to study the affect the size, geometry and the temperature of the graphene sheet had on the ability to propagate the initial fold and the

Sourabrata Mukherjee, Akanksha Bansal, Atul Kr. Ojha, John P. McCrae

This paper focuses on text detoxification, i.e., automatically converting toxic text into non-toxic text. This task contributes to safer and more respectful online communication and can be considered a Text Style Transfer (TST) task, where the text style changes while its content is preserved. We present three approaches: knowledge transfer from a similar ta

Jean-Louis Le Mouël, Dominique Gibert, Jean-Baptiste Boulé, Pierpaolo Zuddas

In this paper, we revisit old electrical measurements conducted on a poplar tree in 2003 (Gibert et al. 2006), which showed the presence of a diurnal electrical signal, attributed to an electrokinetic phenomenon correlated with sap flow, even in winter. We reanalyze these data using the singular spectrum analysis method and demonstrate that the electrical si

Pawel Kalczynski, Zvi Drezner, Morton O'Kelly

This paper continues to develop and explore the impact of multipurpose trips on retail location. We develop the model of locating multiple competing facilities of a chain where several competing facilities exist in the area. There may be some existing facilities of the same chain as well. The addition of multiple new outlets can cause cannibalization of exis

Shomik Verma, Colin Kelsall, Kyle Buznitsky, Alina LaPotin

Thermal energy storage using sensible heating of a solid storage medium is a potential low-cost technology for long-duration energy storage. To effectively get heat in and out of the solid material, channels of heat transfer fluid can be embedded within the storage material. Here we present design principles to improve performance of channel-embedded thermal

Dante Kalise, Estefanía Loayza-Romero, Kirsten A. Morris, Zhengang Zhong

Optimal actuator and control design is studied as a multi-level optimisation problem, where the actuator design is evaluated based on the performance of the associated optimal closed loop. The evaluation of the optimal closed loop for a given actuator realisation is a computationally demanding task, for which the use of a neural network surrogate is proposed

Felix Leopoldo Rios, Alex Markham, Liam Solus

Several approaches to graphically representing context-specific relations among jointly distributed categorical variables have been proposed, along with structure learning algorithms. While existing optimization-based methods have limited scalability due to the large number of context-specific models, the constraint-based methods are more prone to error than

Edit Fenyvesi, Gergely Gábor Barnaföldi, Gábor Gyula Kiss, Dénes Molnár

The question whether an annual modulation is observable during nuclear decay rate measurements has long been the subject of research. One of the possible explanations for the annual variations would be the effect of solar neutrinos, the flux of which changes in correlation with the Earth-Sun distance. A decay rate measurement with a $^{137}$Cs source and a H

Alex J Meyer, Daniel J Scheeres

While contact binary objects are common in the solar system, their formation mechanism is unclear. In this work we examine several contact binaries and calculate the necessary strength parameters that allow the two lobes to merge without the smaller of the two being gravitationally destroyed by the larger. We find a small but non-zero amount of cohesion or a

Giuseppe Orlando, Tommaso Benacchio, Luca Bonaventura

We systematically validate the static local mesh refinement capabilities of a recently proposed IMEX-DG scheme implemented in the framework of the deal.II library. Non-conforming meshes are employed in atmospheric flow simulations to increase the resolution around complex orography. A number of numerical experiments based on classical benchmarks with idealiz

Damien Mégy, Mihai Pavel, Matei Toma

We study a class of semistability conditions defined by a system of ample classes for coherent sheaves over a smooth projective variety. Under some necessary boundedness assumptions, we show the existence of a well-behaved chamber structure for the variation of moduli spaces of sheaves with respect to the change of semistability.

Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh

Stepwise inference protocols, such as scratchpads and chain-of-thought, help language models solve complex problems by decomposing them into a sequence of simpler subproblems. Despite the significant gain in performance achieved via these protocols, the underlying mechanisms of stepwise inference have remained elusive. To address this, we propose to study au

Ruda Guo, Yue-Xin Huang, Xiaoxin Yang, Yi Liu

Nonlinear spin polarization occurring in the second order of driving electric current is the dominant source of nonequilibrium magnetization in centrosymmetric or weakly noncentrosymmetric nonmagnetic materials, and induces nonlinear spin-orbit torque in magnets. Up to now, only the intrinsic mechanism based on anomalous spin polarizability dipole, which is

Manuel Schlierf

It is well-known that the Willmore flow of closed spherical immersions exists globally in time and converges if the initial datum has Willmore energy below $8\pi$ - exactly the Li-Yau energy threshold below which all closed immersions are embedded. Extending the Li-Yau inequality for closed surfaces via Simon's monotonicity formula also for surfaces with bou

Richard Lau, Anthony Tylan-Tyler, Lihan Yao, Rey de Castro Roberto

This paper describes a temporal-spatial model for video processing with special applications to processing event camera videos. We propose to study a conjecture motivated by our previous study of video processing with delay loop reservoir (DLR) neural network, which we call Temporal-Spatial Conjecture (TSC). The TSC postulates that there is significant infor

Jiacheng Ye, Shansan Gong, Liheng Chen, Lin Zheng

Recently, diffusion models have garnered significant interest in the field of text processing due to their many potential advantages compared to conventional autoregressive models. In this work, we propose Diffusion-of-Thought (DoT), a novel approach that integrates diffusion models with Chain-of-Thought, a well-established technique for improving the reason

Marcelo Fonseca Faraj, Ernestine Großmann, Felix Joos, Thomas Möller

Increasing the connectivity of a graph is a pivotal challenge in robust network design. The weighted connectivity augmentation problem is a common version of the problem that takes link costs into consideration. The problem is then to find a minimum cost subset of a given set of weighted links that increases the connectivity of a graph by one when the links

Yasin Findik, S. Reza Ahmadzadeh

Tackling multi-agent learning problems efficiently is a challenging task in continuous action domains. While value-based algorithms excel in sample efficiency when applied to discrete action domains, they are usually inefficient when dealing with continuous actions. Policy-based algorithms, on the other hand, attempt to address this challenge by leveraging c

Arman Farhang, Mohsen Bayat

This paper compares orthogonal time frequency space (OTFS) modulation and single-carrier frequency division multiple access (SC-FDMA). It shows that these are equivalent except for a set of linear phase shifts, applied to the transmit/receive data symbols, which can be absorbed into the channel. Through mathematical and numerical analysis, it is confirmed th

A. H. Sheikh, Biman J. Medhi

We present a statistical and multiwavelength photometric studies of young open cluster IC 1590. We identified 91 cluster members using $Gaia$ DR3 astrometry data using ensemble-based unsupervised machine learning techniques. From $Gaia$ EDR3 data, we estimate the best-fitted parameters for IC 1590 using the Automated Stellar Cluster Analysis package (ASteCA)

Qiang Du, James M. Scott, Xiaochuan Tian

We present a study on asymptotically compatible Galerkin discretizations for a class of parametrized nonlinear variational problems. The abstract analytical framework is based on variational convergence, or Gamma-convergence. We demonstrate the broad applicability of the theoretical framework by developing asymptotically compatible finite element discretizat

Kevin L. Beeson, Janez Kos, Richard de Grijs, Sarah L. Martell

The ability to measure precise and accurate stellar effective temperatures ($T_{\rm{eff}}$) and surface gravities ($\log(g)$) is essential in determining accurate and precise abundances of chemical elements in stars. Measuring $\log(g)$ from isochrones fitted to colour-magnitude diagrams of open clusters is significantly more accurate and precise compared to

Andre Wibisono, Yihong Wu, Kaylee Yingxi Yang

We study the problem of estimating the score function of an unknown probability distribution $\rho^*$ from $n$ independent and identically distributed observations in $d$ dimensions. Assuming that $\rho^*$ is subgaussian and has a Lipschitz-continuous score function $s^*$, we establish the optimal rate of $\tilde \Theta(n^{-\frac{2}{d+4}})$ for this estimati

Douwe J. Spaanderman, Martijn P. A. Starmans, Gonnie C. M. van Erp, David F. Hanff

Segmentations are crucial in medical imaging to obtain morphological, volumetric, and radiomics biomarkers. Manual segmentation is accurate but not feasible in the radiologist's clinical workflow, while automatic segmentation generally obtains sub-par performance. We therefore developed a minimally interactive deep learning-based segmentation method for soft

Jamelle Watson-Daniels, Flavio du Pin Calmon, Alexander D'Amour, Carol Long

Issues can arise when research focused on fairness, transparency, or safety is conducted separately from research driven by practical deployment concerns and vice versa. This separation creates a growing need for translational work that bridges the gap between independently studied concepts that may be fundamentally related. This paper explores connections b

Zonghan Yang, An Liu, Zijun Liu, Kaiming Liu

The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decision-making, and environmental interaction. However, the efficacy of agents remains limited when operating in intricate, realistic environments. In this work, we introduce the princip

Jooyoung Cha

This paper presents a comprehensive local projections (LP) framework for estimating future responses to current shocks, robust to high-dimensional controls without relying on sparsity assumptions. The approach is applicable to various settings, including impulse response analysis and difference-in-differences (DiD) estimation. While methods like LASSO exist,

Yifei Yuan, Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke

In mixed-initiative conversational search systems, clarifying questions are used to help users who struggle to express their intentions in a single query. These questions aim to uncover user's information needs and resolve query ambiguities. We hypothesize that in scenarios where multimodal information is pertinent, the clarification process can be improved

Francesco Tropeano

We present some effective approaches in studying the relative monodromy group of elliptic logarithms with respect to periods of elliptic schemes. We provide explicit ways of constructing explicit loops which leave periods unchanged but along which logarithms have non-trivial variations. We also get some topological methods and effective results which allow t

Pierre Marza, Laetitia Matignon, Olivier Simonin, Christian Wolf

Successfully addressing a wide variety of tasks is a core ability of autonomous agents, requiring flexibly adapting the underlying decision-making strategies and, as we argue in this work, also adapting the perception modules. An analogical argument would be the human visual system, which uses top-down signals to focus attention determined by the current tas

Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh V. Chawla

Link prediction is a crucial task in graph machine learning, where the goal is to infer missing or future links within a graph. Traditional approaches leverage heuristic methods based on widely observed connectivity patterns, offering broad applicability and generalizability without the need for model training. Despite their utility, these methods are limite

Oliver Clarke, Giacomo Masiero, Fatemeh Mohammadi

We study point-line configurations through the lens of projective geometry and matroid theory. Our focus is on their realisation spaces, where we introduce the concepts of liftable and quasi-liftable configurations, exploring cases in which an $n$-tuple of collinear points can be lifted to a non-degenerate realisation of a point-line configuration. We show t

Thong Nguyen, Mariya Hendriksen, Andrew Yates

Learned Sparse Retrieval (LSR) is a group of neural methods designed to encode queries and documents into sparse lexical vectors. These vectors can be efficiently indexed and retrieved using an inverted index. While LSR has shown promise in text retrieval, its potential in multi-modal retrieval remains largely unexplored. Motivated by this, in this work, we

Philipp Froehlich, Heinz Koeppl

In statistics and machine learning, detecting dependencies in datasets is a central challenge. We propose a novel neural network model for supervised graph structure learning, i.e., the process of learning a mapping between observational data and their underlying dependence structure. The model is trained with variably shaped and coupled simulated input data

Hailee Hettrick, David W. Miller, Begum Cannataro

The circular restricted three-body problem (CR3BP) with solar radiation pressure (SRP) has often been analyzed with assumptions made on a spacecraft's attitude, such that the problem remains Hamiltonian. These assumptions are unsatisfactorily limiting for a starshade mission since the starshade's attitude will inherently vary from the configuration that corr

Joshua Edzards, Holger-Dietrich Saßnick, Julia Santana Andreo, Caterina Cocchi

The chemical flexibility of metal-organic frameworks (MOFs) offers an ideal platform to tune structure and composition for specific applications, from gas sensing to catalysis and from photoelectric conversion to energy storage. This variability gives rise to a large configurational space that can be efficiently explored using high-throughput computational m

Gabriel Bathie, Panagiotis Charalampopoulos, Tatiana Starikovskaya

In this work, we address the problem of approximate pattern matching with wildcards. Given a pattern $P$ of length $m$ containing $D$ wildcards, a text $T$ of length $n$, and an integer $k$, our objective is to identify all fragments of $T$ within Hamming distance $k$ from $P$. Our primary contribution is an algorithm with runtime $O(n+(D+k)(G+k)\cdot n/m)$

Zhengguo Tang, Hongchao Shi, Heng Zhu, Bing Tang

The photoinduced topological phase transitions and thermal Hall conductivity of a kagome magnet with Heisenberg, Kitaev, and DM interactions under an external magnetic field aligned along the [111] directions is investigated in this study. In the presence of a strong magnetic field perpendicular to the lattice plane in the [111] direction, the system exhibit

Jieming Sheng, Le Wang, Wenrui Jiang, Han Ge

Continuum of spin excitations observed in inelastic neutron scattering experiments are often considered as a strong evidence of quantum spin liquid formation. When quantum spin liquid is indeed the ground state of a disorder-free magnetic compound, the elementary excitation is no longer the conventional spin waves (magnons). Instead, the magnons fractionaliz

Qian Yang, Jin Xu, Wenrui Liu, Yunfei Chu

Recently, instruction-following audio-language models have received broad attention for human-audio interaction. However, the absence of benchmarks capable of evaluating audio-centric interaction capabilities has impeded advancements in this field. Previous models primarily focus on assessing different fundamental tasks, such as Automatic Speech Recognition

Robin Willems, Lex Verberne, Clemens V. Verhoosel, Olaf van der Sluis

Monitoring the cardiac function often relies on non-invasive vital measurements, electrocardiograms, and low-resolution echocardiograms. The monitoring data can be augmented with numerical modeling results to support treatment-risk assessment. Often, medical images are not suitable for high-fidelity modeling due to their spatial sparsity and low resolution.

Haotian Xu, Shuai Liu, Bohui Wang, Jingcheng Wang

The distributed observer design problem holds significant importance in cases in which the output information of a system is decentralized across different subsystems. Each subsystem has a local observer and access to one part of the measurement outputs and information exchanged through communication networks. This paper focuses on the design of distributed

Zhengsheng Guo, Zhiwei He, Wenxiang Jiao, Xing Wang

Motivated by the success of unsupervised neural machine translation (UNMT), we introduce an unsupervised sign language translation and generation network (USLNet), which learns from abundant single-modality (text and video) data without parallel sign language data. USLNet comprises two main components: single-modality reconstruction modules (text and video)

George Rupp

Resonance pole positions of the $f_0(500)$ alias $\sigma(500)$ meson are computed and plotted as a continuous function of pion mass in the framework of a unitary and analytic coupled-channel model for scalar mesons as dynamical $q\bar{q}$ states. The $\sigma$ is described with a light and a strange $q\bar{q}$ seed, mixing with each other mainly through the c

Mariia Soloviova, Juan Carlos Beltran Vargas, Luis Fernandez de Castro, Juan Belmonte-Beitia

Fibrous dysplasia (FD) is a mosaic non-inheritable genetic disorder of the skeleton in which normal bone is replaced by structurally unsound fibro-osseous tissue. There is no curative treatment for FD, partly because its pathophysiology is not yet fully known. We present a simple mathematical model of the disease incorporating its basic known biology, to gai

Benjamin Dupuis, Umut Şimşekli

Understanding the generalization properties of heavy-tailed stochastic optimization algorithms has attracted increasing attention over the past years. While illuminating interesting aspects of stochastic optimizers by using heavy-tailed stochastic differential equations as proxies, prior works either provided expected generalization bounds, or introduced non

Ratheejit Ghosh, Matteo Ciardi, Rejish Nath, Fabio Cinti

By combining first-principles path integral Monte Carlo methods and mean-field techniques, we explore the properties of cylindrically trapped doubly-dipolar Bose gases. We first verify the emergence of a pancake quantum droplet at low temperatures, validating previously mean-field calculations. In a regime of small doubly-dipolar interactions, first-principl

Hongyun Zhou, Xiangyu Lu, Wang Xu, Conghui Zhu

Low-Rank Adaptation (LoRA) is currently the most commonly used Parameter-efficient fine-tuning (PEFT) method, it introduces auxiliary parameters for each layer to fine-tune the pre-trained model under limited computing resources. However, it still faces resource consumption challenges during training when scaling up to larger models. Most previous studies ha

Cheng Chang, Jiawei Zhang, Jingwei Ge, Zuo Zhang

Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and index scenarios, various vehicle interactions are worthy of much attention, and deserve refined descriptions and labels. However, existing methods cannot

F. Jaron, S. Kiehlmann, A. C. S. Readhead

The high-mass X-ray binary LS I +61{\deg}303 is composed of a Be-type star and a compact object. The emission is variable and periodic across the electromagnetic spectrum, from radio to very high-energy gamma rays. The orbital period is ~26.5 d, and the source also features a super-orbital period with a value of ~4.6 years. Long-term monitoring of the binary

Atsushi Miyauchi, Lorenzo Severini, Francesco Bonchi

Centrality measures, quantifying the importance of vertices or edges, play a fundamental role in network analysis. To date, triggered by some positive approximability results, a large body of work has been devoted to studying centrality maximization, where the goal is to maximize the centrality score of a target vertex by manipulating the structure of a give

Mengqi Lou, Guy Bresler, Ashwin Pananjady

We study the problem of approximately transforming a sample from a source statistical model to a sample from a target statistical model without knowing the parameters of the source model, and construct several computationally efficient such reductions between canonical statistical experiments. In particular, we provide computationally efficient procedures th

Özgür Akarsu, Antonio De Felice, Eleonora Di Valentino, Suresh Kumar

We integrate $\Lambda_{\rm s}$CDM, a promising scenario for alleviating cosmological tensions, into VCDM, a type-II minimally modified gravity. This promotes the scenario to a fully predictive model (dubbed $\Lambda_{\rm s}$VCDM) that specifies the cosmological evolution self-consistently, including through the late-time AdS-to-dS transition epoch. In this t

R. Paviot, A. Rocher, S. Codis, A. de Mattia

Analytical models of galaxy-halo connection such as the Halo Occupation Distribution (HOD) model have been widely used over the past decades as a means to intensively test perturbative models on quasi-linear scales. However, these models fail to reproduce the galaxy-galaxy lensing signal on non-linear scales, over-predicting the observed signal up to 40%. Wi

Jorge Maestre Vidal, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

Denial of service attacks pose a threat in constant growth. This is mainly due to their tendency to gain in sophistication, ease of implementation, obfuscation and the recent improvements in occultation of fingerprints. On the other hand, progress towards self-organizing networks, and the different techniques involved in their development, such as software-d

Cosmin Ilie

Any astrophysical object can, in principle, serve as a probe of the interaction between Dark Matter and regular, baryonic matter. This method is based on the potential observable consequences annihilations of captured Dark Matter has on the surface temperature of the object itself. In a series of previous papers we developed and validated simple analytic app

Elvis Dohmatob, Yunzhen Feng, Julia Kempe

In the era of proliferation of large language and image generation models, the phenomenon of "model collapse" refers to the situation whereby as a model is trained recursively on data generated from previous generations of itself over time, its performance degrades until the model eventually becomes completely useless, i.e the model collapses. In this work,

Miao Liu, Zengjiao Ma, Chong Shangguan

Frameproof codes are a class of secure codes that were originally introduced in the pioneering work of Boneh and Shaw in the context of digital fingerprinting. They can be used to enhance the security and credibility of digital content. Let $M_{c,l}(q)$ denote the largest cardinality of a $q$-ary $c$-frameproof code with length $l$. Based on an intriguing ob

Chester Luo, Kevin Lai

In recent years, there has been a significant increase in the utilization of deep learning methods, particularly convolutional neural networks (CNNs), which have emerged as the dominant approach in various domains that involve structured grid data, such as picture analysis and processing. Nevertheless, the exponential growth in the utilization of LiDAR and 3

Filip Broćić

In this short note, we construct an explicit embedding of the rescaling of the $p$-sum $K\oplus_p K^{\circ}$ of the centrally symmetric convex domain $K$ and its polar $K^{\circ}$ to the product $K \times K^{\circ}$. The rescaling constant is sharp in some cases. Additionally, we comment on the strong Viterbo conjecture for $K\oplus_p K^{\circ}$.

Kristine Aavild Juhl, Jakob Slipsager, Ole de Backer, Klaus Kofoed

Patients with atrial fibrillation have a 5-7 fold increased risk of having an ischemic stroke. In these cases, the most common site of thrombus localization is inside the left atrial appendage (LAA) and studies have shown a correlation between the LAA shape and the risk of ischemic stroke. These studies make use of manual measurement and qualitative assessme

Zhen Wang, Feiyang Sun, Xiaodong Xu, Xin Li

Multi-stable mechanical structures find cutting-edge applications across various domains due to their reconfigurability, which offers innovative possibilities for engineering and technology advancements. This study explores the emergence of topological states in a one-dimensional chain-like multi-stable mechanical metamaterial composed of bistable units thro

Arno B. J. Kuijlaars, Mateusz Piorkowski

We compare two methods for analysing periodic dimer models. These are the matrix-valued orthogonal polynomials approach due to Duits and one of the authors, and the Wiener-Hopf approach due to Berggren and Duits. We establish their equivalence in the special case of the Aztec diamond. Additionally, we provide explicit formulas for the matrix-valued orthogona

Alrik Durand, Yoann Baron, Félix Cache, Tobias Herzig

Among the wide variety of single fluorescent defects investigated in silicon, numerous studies have focused on color centers with a zero-phonon line around $1.28 \mu$m and identified to a common carbon-complex in silicon, namely the G center. However, inconsistent estimates regarding their quantum efficiency cast doubt on the correct identification of these

Ofir Schnabel

We classify crossed product gradings for arbitrary groups and fields up to several equivalence relations in terms of group actions and their orbits.

Ping Wu, Heyan Huang, Zhengyang Liu

In the field of online sequential decision-making, we address the problem with delays utilizing the framework of online convex optimization (OCO), where the feedback of a decision can arrive with an unknown delay. Unlike previous research that is limited to Euclidean norm and gradient information, we propose three families of delayed algorithms based on appr

Alena Schnickmanna, Danilo Alencar De Abreu, Olga Fabrichnaya, Thomas Schirmer

The expected shortage of Li due to the strong increase in electromobility is an important issue for the recovery of Li from spent Li-ion batteries. One approach is pyrometallurgical processing, during which ignoble elements such as Li, Al and Mn enter the slag system. The Engineered Artificial Minerals (EnAM) strategy aims to efficiently recover critical ele

Rupchand Sutradhar, D C Dalal

In this paper, we investigate the dynamics of hepatitis B virus infection taking into account the implementation of combination therapy through mathematical modeling. This model is established considering the interplay between uninfected cells, infected cells, capsids, and viruses. Three drugs are considered for specific roles (i) pegylated interferon (PEG I

Vahid Karimipour

Two important classes of quantum channels, namly the Werner-Holevo and the Landau-Streater channels are known to be related only in three dimensions, i.e. when acting on qutrits. In this work, definition of the Landau-Streater channel is extended in such a way which retains its equivalence to the Werner-Holevo channel in all dimensions. This channel is then

F. Javadi, M. J. Mehdipour

In this paper, we first prove a theorem by a little modification on the Lax-Milgram theorem. Then, using $K$-frames, we obtain lower and upper bounds for the results obtained from this theorem. Also, we present some methods for the characterization of scalable $K$-frames. Finally, we introduce piecewise scalable $K$-frames and give necessary and sufficient c