March 2024 arXiv papers — page 163

Chaehyeon Song, Jaeho Shin, Myung-Hwan Jeon, Jongwoo Lim

In the literature, points and conics have been major features for camera geometric calibration. Although conics are more informative features than points, the loss of the conic property under distortion has critically limited the utility of conic features in camera calibration. Many existing approaches addressed conic-based calibration by ignoring distortion

Lu Xing, Venkata Sai Pavan Kumar Vadrevu, Walid G. Aref

Skiplists have become prevalent in systems. The main advantages of skiplists are their simplicity and ease of implementation, and the ability to support operations in the same asymptotic complexities as their tree-based counterparts. In this survey, we explore skiplists and their many variants. We highlight many scenarios about how skiplists are useful, and

Deepak K Sharma, Adrian Agreda, Florian DellOva, Konstantin Malchow

Nonlinear photoluminescence (N-PL) is a broadband photon emission arising from non-equilibrium electron distribution generated at the surface of metallic nanostructures by an ultrafast pulsed laser illumination. N-PL is sensitive to surface morphology, local electromagnetic field strength, and electronic band structure making it relevant to probe optically e

Joonyoung F. Joung, Mun Hong Fong, Jihye Roh, Zhengkai Tu

Mechanistic understanding of organic reactions can facilitate reaction development, impurity prediction, and in principle, reaction discovery. While several machine learning models have sought to address the task of predicting reaction products, their extension to predicting reaction mechanisms has been impeded by the lack of a corresponding mechanistic data

L. S. Dolan, E. J. W de Mooij, C. A. Watson, D. G. Jackson

Stellar activity and planetary effects induce radial velocity (RV) offsets and cause temporal distortions in the shape of the stellar line profile. Hence, accurately probing the stellar line profile offers a wealth of information on both the star itself and any orbiting planets. Typically, Cross-Correlation Functions (CCFs) are used as a proxy for the stella

Edgar Mauricio Salazar Duque, Juan S. Giraldo, Pedro P. Vergara, Phuong H. Nguyen

In this paper, we present two multidimensional power flow formulations based on a fixed-point iteration (FPI) algorithm to efficiently solve hundreds of thousands of power flows in distribution systems. The presented algorithms are the base for a new TensorPowerFlow (TPF) tool and shine for their simplicity, benefiting from multicore \gls{cpu} and \gls{gpu}

Aneta Koleva, Martin Ringsquandl, Ahmed Hatem, Thomas Runkler

Interest in solving table interpretation tasks has grown over the years, yet it still relies on existing datasets that may be overly simplified. This is potentially reducing the effectiveness of the dataset for thorough evaluation and failing to accurately represent tables as they appear in the real-world. To enrich the existing benchmark datasets, we extrac

Veronika Trávníková, Daniel Wolff, Nico Dirkes, Stefanie Elgeti

This paper explores the potential of Physics-Informed Neural Networks (PINNs) to serve as Reduced Order Models (ROMs) for simulating the flow field within stirred tank reactors (STRs). We solve the two-dimensional stationary Navier-Stokes equations within a geometrically intricate domain and explore methodologies that allow us to integrate additional physica

Juan B. Gil, Emma G. Hoover, Jessica A. Shearer

In this paper, we give part-preserving bijections between three fundamental families of objects that serve as natural framework for many problems in enumerative combinatorics. Specifically, we consider compositions, Dyck paths, and partitions of a convex polygon, and identify suitable building blocks that are then appropriately decorated to achieve matching

Juan Carlos Ruiz-Garcia, Carlos Hojas, Ruben Tolosana, Ruben Vera-Rodriguez

This article proposes a novel Children-Computer Interaction (CCI) approach for the task of age group detection. This approach focuses on the automatic analysis of the time series generated from the interaction of the children with mobile devices. In particular, we extract a set of 25 time series related to spatial, pressure, and kinematic information of the

Johannes V. Roth, Yunxin Ye, Sören Schlichting, Lorenz von Smekal

In the chiral limit the complicated many-body dynamics around the second-order chiral phase transition of two-flavor QCD can be understood by appealing to universality. We present a novel formulation of the real-time functional renormalization group that describes the stochastic hydrodynamic equations of motion for systems in the same dynamic universality cl

Victor V. Albert, Eric Kubischta, Mikhail Lemeshko, Lee R. Liu

We formulate a quantum phase space for rotational and nuclear-spin states of rigid molecules. For each nuclear spin isomer, we re-derive the isomer's admissible angular momentum states from molecular geometry and nuclear-spin data, introduce its angular position states using quantization theory, and develop a generalized Fourier transform converting between

Yoshua Bengio, Nikolay Malkin

The current state-of-the-art in artificial intelligence is impressive, especially in terms of mastery of language, but not so much in terms of mathematical reasoning. What could be missing? Can we learn something useful about that gap from how the brains of mathematicians go about their craft? This essay builds on the idea that current deep learning mostly s

Sören Henning, Adriano Vogel, Michael Leichtfried, Otmar Ertl

Distributed stream processing frameworks help building scalable and reliable applications that perform transformations and aggregations on continuous data streams. This paper introduces ShuffleBench, a novel benchmark to evaluate the performance of modern stream processing frameworks. In contrast to other benchmarks, it focuses on use cases where stream proc

Daniel Førland Holmen, Jan Martin Nordbotten, Jon Eivind Vatne

Many coupled problems in engineering and science can be described by elliptic partial differential equations on adjacent domains, where the coupling can be considered either as a thin equidimensional overlap between the model domains, or as a lower-dimensional interface. Thereby we distinguish equidimensional and mixed-dimensional models of the same system,

Long-Fei Li, Peng Zhao, Zhi-Hua Zhou

We study reinforcement learning with linear function approximation, unknown transition, and adversarial losses in the bandit feedback setting. Specifically, we focus on linear mixture MDPs whose transition kernel is a linear mixture model. We propose a new algorithm that attains an $\widetilde{O}(d\sqrt{HS^3K} + \sqrt{HSAK})$ regret with high probability, wh

Antonio Tribuzio, Konstantinos Zemas

We study energy scaling laws for a simplified, singularly perturbed, double-well nucleation problem confined in a half-space, in the absence of gauge invariance and for an inclusion of fixed volume. Motivated by models for boundary nucleation of a single-phase martensite inside a parental phase of austenite, our main focus in this nonlocal isoperimetric prob

Qiao He, Yousheng Shi, Tonghai Yang

This paper is a complement of the modularity result of Bruinier, Howard, Kudla, Rapoport and Yang (BHKRY) for the special case $U(1,1)$ not considered there. The main idea to embed a $U(1, 1)$ Shimura curve to many $U(n-1, 1)$ Shimura varieties for big $n$, and prove a precise pullback formula of the generating series of arithmetic divisors. Afterwards, we u

Thiago Solovera e Nery

The goal of this paper is to show a (derived) $p$-adic Simpson correspondence for (locally) unipotent coefficients on smooth rigid-analytic varieties. Our results depend on a deformation to $\mathbf{B}_\mathtt{dr}^+/\xi^2$, and not on a choice of exponential (as required for more general coefficients). Our methods are inherently higher categorical, hinging o

Mamadou Yauck, Erica EM Moodie, Alain Fourmigue, Milada Dvorakova

This work is concerned with the estimation of hard-to-reach population sizes using a single respondent-driven sampling (RDS) survey, a variant of chain-referral sampling that leverages social relationships to reach members of a hidden population. The popularity of RDS as a standard approach for surveying hidden populations brings theoretical and methodologic

Panrui Ni, Maxime Zavidovique

In this paper, we introduce a discrete version of the nonlinear implicit Lax-Oleinik operator. We consider the associated vanishing discount problem with a non-degenerate condition and prove convergence of solutions as the discount factor goes to $0$. We also discuss the uniqueness of the discounted solution. The convergence result is a selection principle f

Stamatios Georgoulis, Weining Ren, Alfredo Bochicchio, Daniel Eckert

Rapid and reliable identification of dynamic scene parts, also known as motion segmentation, is a key challenge for mobile sensors. Contemporary RGB camera-based methods rely on modeling camera and scene properties however, are often under-constrained and fall short in unknown categories. Event cameras have the potential to overcome these limitations, but co

A. G. da Costa Moura, C. H. Monken

We present analytic expressions for the coincidence detection probability amplitudes of photon pairs generated by spontaneous parametric down-conversion in both momentum and position spaces, without making use of the Gaussian approximation, and taking into account the effects of birefringence in the nonlinear crystal. We also present experimental data suppor

Takafumi Kouno, Satoshi Naito

We construct an injective weight-preserving map (called the forgetful map) from the set of all admissible subsets in the quantum alcove model associated to an arbitrary weight. The image of this forgetful map can be explicitly described by introducing the notion of "interpolated quantum Lakshmibai-Seshadri (QLS for short) paths", which can be thought of as a

Florian Messerer, Katrin Baumgärtner, Sergio Lucia, Moritz Diehl

We investigate the suboptimality resulting from the application of nominal model predictive control (MPC) to a nonlinear discrete time stochastic system. The suboptimality is defined with respect to the corresponding stochastic optimal control problem (OCP) that minimizes the expected cost of the closed loop system. In this context, nominal MPC corresponds t

Tim Lenz, Omar S. M. El Nahhas, Marta Ligero, Jakob Nikolas Kather

Deep Learning models have been successfully utilized to extract clinically actionable insights from routinely available histology data. Generally, these models require annotations performed by clinicians, which are scarce and costly to generate. The emergence of self-supervised learning (SSL) methods remove this barrier, allowing for large-scale analyses on

Pankaj Gautam, Markus Grasmair

In this paper we consider the solution of monotone inverse problems using the particular example of a parameter identification problem for a semilinear parabolic PDE. For the regularized solution of this problem, we introduce a total variation based regularization method requiring the solution of a monotone inclusion problem. We show well-posedness in the se

Joel Diaz Maier, Joachim Wagner

We describe experimentally observed collective dynamics in colloidal suspensions of model hard-sphere particles using a modified mode coupling theory (MCT). This rescaled MCT is capable to describe quantitatively the wave-vector and time-dependent diffusion in these systems. Intermediate scattering functions of liquid-like structured dispersions are determin

R. Hassaine, F. Gauchet, F. Iacob, J. Zs Mezei

Cross sections and rate coefficients for the Dissociative Recombination (DR) of the NS+ ion induced by collisions with low-energy electrons are reported for temperatures between 10 and 1000 K, relevant to a large range of interstellar cloud temperatures. Uncertainties are discussed for these rates. Comparisons are made with DR rates for the isovalent NO+ mol

Varshitha Chennamsetti, Laiba Mehnaz, Dan Zhao, Banani Ghosh

In this paper, we report the performance benchmarking results of deep learning models on MLCommons' Science cloud-masking benchmark using a high-performance computing cluster at New York University (NYU): NYU Greene. MLCommons is a consortium that develops and maintains several scientific benchmarks that can benefit from developments in AI. We provide a desc

Yonghui Zhao

This paper investigates the dynamical properties of the Leslie-Gower model with Alle effects, cooperative hunting, and constant placement rates. The conditions for the existence of the triple equilibrium point of the model are first analyzed. Subsequently, the canonical type theory and the qualitative theory of planar systems are applied to obtain that the t

Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar

Characterizing samples that are difficult to learn from is crucial to developing highly performant ML models. This has led to numerous Hardness Characterization Methods (HCMs) that aim to identify "hard" samples. However, there is a lack of consensus regarding the definition and evaluation of "hardness". Unfortunately, current HCMs have only been evaluated o

Alexander G. Eaton, Nicholas J. M. Popiel, Ke-Jun Xu, Alexander J. Hickey

We present local and nonlocal electrical transport measurements of the correlated insulator FeSb$_2$. By employing wiring configurations that delineate between bulk- and surface-dominated conduction, we reveal the formation of a metallic surface state in FeSb$_2$ for temperatures $\lessapprox 5$~K. This result is corroborated by an angular rotation study of

Yuhang Lu, Zewei Xu, Touradj Ebrahimi

Recent years have witnessed significant advancement in face recognition (FR) techniques, with their applications widely spread in people's lives and security-sensitive areas. There is a growing need for reliable interpretations of decisions of such systems. Existing studies relying on various mechanisms have investigated the usage of saliency maps as an expl

Philipp J. di Dio

These are the lecture notes based on [dD23] for the (upcoming) lecture "T-systems with a special emphasis on sparse moment problems and sparse Positivstellens\"atze" in the summer semester 2024 at the University of Konstanz. The main purpose of this lecture is to prove the sparse Positiv- and Nichtnegativstellens\"atze of Samuel Karlin (1963) and to apply th

Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner, Priya Goyal

We study the effectiveness of data-balancing for mitigating biases in contrastive language-image pretraining (CLIP), identifying areas of strength and limitation. First, we reaffirm prior conclusions that CLIP models can inadvertently absorb societal stereotypes. To counter this, we present a novel algorithm, called Multi-Modal Moment Matching (M4), designed

Satwat Bashir, Tasos Dagiuklas, Kasra Kassai, Muddesar Iqbal

This paper proposes a novel three tier architecture for federated learning to optimize edge computing environments. The proposed architecture addresses the challenges associated with client data heterogeneity and computational constraints. It introduces a scalable, privacy preserving framework that enhances the efficiency of distributed machine learning. Thr

Thedoros S. Papazachariou

We study the K-moduli space of products of Fano varieties in relation to the product of K-moduli spaces of the product components. We show that there exists a well-defined morphism from the product of K-moduli stacks of Fano varieties to the K-moduli stack of their product. Furthermore, we show that this morphism is an isomorphism if any two varieties with d

Andrzej Rozkosz, Tomasz Klimsiak

We consider the Dirichlet problem for equation involving a general operator associated with a symmetric transient regular Dirichlet form and bounded Borel measure on the right-hand side of the equation. We introduce a new function space (depending on the form) which allows us to distinguish between solutions with diffuse measure and with general Borel measur

Aurelio L. Sulser, Maximilian Probst Gutenberg

In this work, we present the first algorithm to compute expander decompositions in an m-edge directed graph with near-optimal time \~O(m). Further, our algorithm can maintain such a decomposition in a dynamic graph and again obtains near-optimal update times. Our result improves over previous algorithms of Bernstein-Probst Gutenberg-Saranurak (FOCS 2020), Hu

Manuel Borroto, Irfan Kareem, Francesco Ricca

This paper moves the first step towards automating the composition of Answer Set Programming (ASP) specifications. In particular, the following contributions are provided: (i) A dataset focused on graph-related problem specifications, designed to develop and assess tools for ASP automatic coding; (ii) A two-step architecture, implemented in the NL2ASP tool,

Mohamed-Raouf Amara, Caixia Huo, Christophe Voisin, Qihua Xiong

Understanding the interplay between bright and dark exciton states is crucial for deciphering the luminescence properties of low-dimensional materials. The origin of the outstanding brightness of lead halide perovskites remains elusive. Here, we analyse temperature-dependent time-resolved photoluminescence to investigate the population mixing between bright

Geraldo F. Oliveira, Emanuele G. Esposito, Juan Gómez-Luna, Onur Mutlu

Processing-using-DRAM (PUD) architectures impose a restrictive data layout and alignment for their operands, where source and destination operands (i) must reside in the same DRAM subarray (i.e., a group of DRAM rows sharing the same row buffer and row decoder) and (ii) are aligned to the boundaries of a DRAM row. However, standard memory allocation routines

Maria Recasens, Valentin Kasper, Maciej Lewenstein, Allan S. Johnson

Strong field terahertz pulses are increasingly used to excite and control quantum materials at the ultrafast timescale. They have found widespread application by enabling direct addressing of the superconducting gap or Josephson resonances and are essential in Higgs spectroscopy. Large non-linear optical signals can be induced by the strong coupling of the T

Sourav Roy, Subhadeep Paul, Tapas Kumar Maiti

This paper aims to get a comprehensive review of current-day robotic computation technologies at VLSI architecture level. We studied several repots in the domain of robotic processor architecture. In this work, we focused on the forward kinematics architectures which consider CORDIC algorithms, VLSI circuits of WE DSP16 chip, parallel processing and pipeline

Charlesquin Kemajou Mbakam, Marcelo Pereyra, Jean-François Giovannelli

This paper presents a novel stochastic optimisation methodology to perform empirical Bayesian inference in semi-blind image deconvolution problems. Given a blurred image and a parametric class of possible operators, the proposed optimisation approach automatically calibrates the parameters of the blur model by maximum marginal likelihood estimation, followed

Arnaud Pierens, Richard P. Nelson

The process of forming a circumbinary planet is thought to be intimately related to the structure of the nascent circumbinary disc. It has been shown that the structure of a circumbinary disc depends strongly on 3-dimensional effects and on the detailed modelling of the thermodynamics. Here, we employ 3-dimensional hydrodynamical simulations, combined with a

Mohamed Elhamdadi, Brooke Jones, Minghui Liu

We completely characterize the coloring quivers of general torus links by dihedral quandles by first exhausting all possible numbers of colorings, followed by determining the interconnections between colorings in each case. The quiver is obtained as function of the number of colorings. The quiver always contains complete subgraphs, in particular a complete s

Juhi Singh, Karthik V. Raman, Narayan Mohanta

Proximity coupling of ferromagnetic insulator EuS to the topological insulator Bi$_2$Se$_3$ has been proposed to break time-reversal symmetry near the surface of Bi$_2$Se$_3$, introducing an energy gap or a tilt in the surface Dirac cone. As an inverse proximity effect, strong spin-orbit coupling available in the topological surface states can enhance the Cu

Kuldeep Belwal, D. Bisht, Mohit Singh Bisht, Geeta Rangwal

We conducted a photometric and kinematic analysis of the young open cluster NGC 2345 using CCD \emph{UBV} data from 2-m Himalayan Chandra Telescope (HCT), \emph{Gaia} Data Release 3 (DR3), 2MASS, and the APASS datasets. We found 1732 most probable cluster members with membership probability higher than 70$\%$. The fundamental and structural parameters of the

Jianwei Zhang, Yonggang Shi

Normative modeling has emerged as a pivotal approach for characterizing heterogeneity and individual variance in neurodegenerative diseases, notably Alzheimer's disease(AD). One of the challenges of cortical normative modeling is the anatomical structure mismatch due to folding pattern variability. Traditionally, registration is applied to address this issue

Yannai A. Gonczarowski, Michael Yin, Shirley Zhang

We extend the seminal model of Pathak and S\"onmez (2008) to a setting with multiple school districts, each running its own separate centralized match, and focus on the case of two districts. In our setting, in addition to each student being either sincere or sophisticated, she is also either constrained - able to apply only to schools within her own distric

Wanru Zhao, Yaxin Du, Nicholas Donald Lane, Siheng Chen

In the current landscape of foundation model training, there is a significant reliance on public domain data, which is nearing exhaustion according to recent research. To further scale up, it is crucial to incorporate collaboration among multiple specialized and high-quality private domain data sources. However, the challenge of training models locally witho

Jie Gu, Gengbei Guo

We study the resurgent structures of Wilson loops in refined topological string theory. We argue that the Borel singularities should be integral periods, and that the associated Stokes constants are refined Donaldson-Thomas invariants, just like the free energies, except that the Borel singularities cannot be local flat coordinates. We also solve the non-per

Pengxiang Wang, Yuntian Chen, Wei Liu

Conventional approaches for scattering manipulations rely on the technique of field expansions into spherical harmonics (electromagnetic multipoles), which nevertheless is non-generic (expansion coefficients depend on the position of the coordinate system's origin) and more descriptive than predictive. Here we explore this classical topic from a different pe

Dimitar Georgiev, Álvaro Fernández-Galiana, Simon Vilms Pedersen, Georgios Papadopoulos

Raman spectroscopy is widely used across scientific domains to characterize the chemical composition of samples in a non-destructive, label-free manner. Many applications entail the unmixing of signals from mixtures of molecular species to identify the individual components present and their proportions, yet conventional methods for chemometrics often strugg

Nils L. Johannsen, Lukas Grundmann

This document shall provide all knowledge gained in conjunction and preparation with the conducted measurements in the antenna measurement chamber of the Institute of Microwave and Wireless Systems (IMW) of the Leibniz University of Hannover (LUH). The measurements have been prepared and conducted by Lukas Grundmann, IMW, and Nils L. Johannsen, Chair of Info

Thomas Budzinski

We prove the local convergence of uniform bipartite maps with prescribed face degrees in the high genus regime. Unlike in the previous work arxiv:2012.05813 on the subject, we do not make any assumption on the tail of the face degrees, except that they remain finite in the limit.

Mariano V. Ntrougkas, Nikolaos Gkalelis, Vasileios Mezaris

The development and adoption of Vision Transformers and other deep-learning architectures for image classification tasks has been rapid. However, the "black box" nature of neural networks is a barrier to adoption in applications where explainability is essential. While some techniques for generating explanations have been proposed, primarily for Convolutiona

Naoto Shiraishi

We rigorously prove that the Heisenberg chain with next-nearest-neighbor interaction, which is anticipated to be non-integrable, is indeed non-integrable in the sense that this system has no nontrivial local conserved quantity. Our result covers two important models, the Majundhar-Ghosh model and the Shastry-Sutherland model, as special cases. These models a

Qian Li, Shu Guo, Yinjia Chen, Cheng Ji

Few-shot knowledge graph completion (FKGC) aims to query the unseen facts of a relation given its few-shot reference entity pairs. The side effect of noises due to the uncertainty of entities and triples may limit the few-shot learning, but existing FKGC works neglect such uncertainty, which leads them more susceptible to limited reference samples with noise

Mengqi Tan

The existence and local stability of some non-negative equilibrium points of a class of SIRS infectious disease models with non-linear infection and treatment rates are investigated under the condition that the total population is a constant. The qualitative theory of differential equations was used to demonstrate that the endemic equilibrium point of the sy

Chi-Zhuo Wang, Yun-Guo Jiang

The variation mechanism of blazars is a long-standing unresolved problem. In this work, we present a scenario to explain diverse variation phenomena for ON 231, where the jet emissions are composed of the flaring and the less variable components (most probably from the post-flaring blobs), and the variation is dominated by shock-in-jet instead of the Doppler

Ravi Shankar Jaiswal

We prove the nontangential asymptotic limits of the Bergman canonical invariant, Ricci and Scalar curvatures of the Bergman metric, as well as the Kobayashi--Fuks metric, at exponentially flat infinite type boundary points of smooth bounded pseudoconvex domains in $\mathbb{C}^{n + 1}, \, n \in \mathbb{N}$. Additionally, we establish the nontangential asympto

Walter Boscheri, Andrea Thomann

We present a divergence-free semi-implicit finite volume scheme for the simulation of the ideal magnetohydrodynamics (MHD) equations which is stable for large time steps controlled by the local transport speed at all Mach and Alfv\'en numbers. An operator splitting technique allows to treat the convective terms explicitly while the hydrodynamic pressure and

Shimi Chettiparambil Mohanan, Nishith Mohan, Christina Surulescu

We propose a PDE-ODE model for tissue regeneration, obtained by parabolic upscaling from kinetic transport equations written for the mesoscopic densities of mesenchymal stem cells and chondrocytes which evolve in an artificial scaffold impregnated with hyaluron. Due to the simple chosen turning kernels, the effective equations obtained on the macroscopic lev

Xu Zhang, Tongshuai Zhu, Shuai Zhang, Zhongqiang Chen

Nonlinear transport is a unique functionality of noncentrosymmetric systems, which reflects profound physics, such as spin-orbit interaction, superconductivity and band geometry. However, it remains highly challenging to enhance the nonreciprocal transport for promising rectification devices. Here, we observe a light-induced giant enhancement of nonreciproca

Yingxia Xi, Junshan Lin, Jiguang Sun

We consider the numerical computation of resonances for metallic grating structures with dispersive media and small slit holes. The underlying eigenvalue problem is nonlinear and the mathematical model is multiscale due to the existence of several length scales in problem geometry and material contrast. We discretize the partial differential equation model o

Mark de Berg, Leonidas Theocharous

Let $\mathcal{P}$ be a simple polygon with $m$ vertices and let $P$ be a set of $n$ points inside $\mathcal{P}$. We prove that there exists, for any $\varepsilon>0$, a set $\mathcal{C} \subset P$ of size $O(1/\varepsilon^2)$ such that the following holds: for any query point $q$ inside the polygon $\mathcal{P}$, the geodesic distance from $q$ to its furthest

Athanasios Andrikopoulos, Nikolaos Sampanis

The theory of optimal choice sets is a solution theory that has a long and well-established tradition in social choice and game theories. Some of important general solution concepts of choice problems when the set of best alternatives does not exist (this problem occurs when the preferences yielded by an economic process are cyclic) is the Stable Set (Von Ne

Nicholas Sukiennik, Chen Gao, Nian Li

Filter bubbles have been studied extensively within the context of online content platforms due to their potential to cause undesirable outcomes such as user dissatisfaction or polarization. With the rise of short-video platforms, the filter bubble has been given extra attention because these platforms rely on an unprecedented use of the recommender system t

Suzanna Sia, David Mueller, Kevin Duh

Self-supervised large language models have demonstrated the ability to perform Machine Translation (MT) via in-context learning, but little is known about where the model performs the task with respect to prompt instructions and demonstration examples. In this work, we attempt to characterize the region where large language models transition from in-context

Mia S. Lundkvist, Hans Kjeldsen, Timothy R. Bedding, Mark J. McCaughrean

We have detected solar-like oscillations in the mid K-dwarf $\varepsilon$ Indi A, making it the coolest dwarf to have measured oscillations. The star is noteworthy for harboring a pair of brown dwarf companions and a Jupiter-type planet. We observed $\varepsilon$ Indi A during two radial velocity campaigns, using the high-resolution spectrographs HARPS (2011

Evangelos Skartados, Mehmet Kerim Yucel, Bruno Manganelli, Anastasios Drosou

Neural Radiance Fields (NeRF) have quickly become the primary approach for 3D reconstruction and novel view synthesis in recent years due to their remarkable performance. Despite the huge interest in NeRF methods, a practical use case of NeRFs has largely been ignored; the exploration of the scene space modelled by a NeRF. In this paper, for the first time i

Martyna Wiącek, Piotr Rybak, Łukasz Pszenny, Alina Wróblewska

With the advancements of transformer-based architectures, we observe the rise of natural language preprocessing (NLPre) tools capable of solving preliminary NLP tasks (e.g. tokenisation, part-of-speech tagging, dependency parsing, or morphological analysis) without any external linguistic guidance. It is arduous to compare novel solutions to well-entrenched

Christian Hamster, Jorik Schaap, Peter van Heijster, Joshua Dijksman

We study the effect of speciation, i.e. the introduction of new species through evolution into communities, in the setting of predator-prey systems. Predator-prey dynamics is classically well modeled by Lotka-Volterra equations, also when multiple predator and prey species co-exist. The consequences of the emergence of new species in such systems are much le

Eric Rozan, Marcelo N Kuperman, Sebastian Bouzat

This study investigates the utilization of various mathematical models for comprehending and managing outbreaks of infectious diseases, with a specific focus on how different distributions of incubation times influence predictions regarding epidemics. Two methodologies are examined: a compartmental SEnIR ODE model, which represents an enhanced version of the

Jaehyun Lee, SeongKu Kang, Hwanjo Yu

Matrix completion is an important area of research in recommender systems. Recent methods view a rating matrix as a user-item bi-partite graph with labeled edges denoting observed ratings and predict the edges between the user and item nodes by using the graph neural network (GNN). Despite their effectiveness, they treat each rating type as an independent re

Matteo Attimonelli, Danilo Danese, Daniele Malitesta, Claudio Pomo

In this work, we introduce Ducho 2.0, the latest stable version of our framework. Differently from Ducho, Ducho 2.0 offers a more personalized user experience with the definition and import of custom extraction models fine-tuned on specific tasks and datasets. Moreover, the new version is capable of extracting and processing features through multimodal-by-de

Hui Zhao, Dirk Slock

We introduce an energy-efficient downlink rate splitting multiple access (RSMA) scheme, employing a simple matched filter (MF) for precoding. We consider a transmitter equipped with multiple antennas, serving several single-antenna users at the same frequency-time resource, each with distinct message requests. Within the conventional 1-layer RSMA framework,

Saurav Bharadwaj, Akshita Midha, Shikha Sharma, Gurupkar Singh Sidhu

Citrus diseases pose threats to citrus farming and result in economic losses worldwide. Nucleic acid and serology-based methods of detection and, immunochromatographic assays are commonly used but these laboratory tests are laborious, expensive and might be subjected to cross-reaction and contamination. Modern optical spectroscopic techniques offer a promisi

Felix Höfling, Arthur V. Straube

The translational motion of anisotropic or self-propelled colloidal particles is closely linked with the particle's orientation and its rotational Brownian motion. In the overdamped limit, the stochastic evolution of the orientation vector follows a diffusion process on the unit sphere and is characterized by an orientation-dependent (``multiplicative'') noi

Jonas Weidner, Ivan Ezhov, Michal Balcerak, Marie-Christin Metz

Biophysical modeling, particularly involving partial differential equations (PDEs), offers significant potential for tailoring disease treatment protocols to individual patients. However, the inverse problem-solving aspect of these models presents a substantial challenge, either due to the high computational requirements of model-based approaches or the limi

Nis-Erik Bohne, Benedikt Gräßle, Stefan A. Sauter

The Scott-Vogelius element is a popular finite element for the discretization of the Stokes equations which enjoys inf-sup stability and gives divergence-free velocity approximation. However, it is well known that the convergence rates for the discrete pressure deteriorate in the presence of certain $critical$ $vertices$ in a triangulation of the domain. Mod

Aaron J. Hendrickson, David P. Haefner, Stanley H. Chan, Nicholas R. Shade

Working from a Poisson-Gaussian noise model, a multi-sample extension of the Photon Counting Histogram Expectation Maximization (PCH-EM) algorithm is derived as a general-purpose alternative to the Photon Transfer (PT) method. This algorithm is derived from the same model, requires the same experimental data, and estimates the same sensor performance paramet

Quanyong Chen, Zhaobing Fan, Qi Wang

The Hecke algebras and quantum group of affine type A admit geometric realizations in terms of complete flags and partial flags over a local field, respectively. Subsequently, it is demonstrated that the quantum group associated to partial flag varieties of affine type C is a coideal subalgebra of quantum group of affine type A. In this paper, we establish a

Angelina Parfenova

This paper explores the development and application of an automated system designed to extract information from semi-structured interview transcripts. Given the labor-intensive nature of traditional qualitative analysis methods, such as coding, there exists a significant demand for tools that can facilitate the analysis process. Our research investigates var

Nick Salter

The space of monic squarefree polynomials has a stratification according to the multiplicities of the critical points, called the equicritical stratification. Tracking the positions of roots and critical points, there is a map from the fundamental group of a stratum into a braid group. We give a complete determination of this map. It turns out to be characte

Błażej Żmija

For a sequence $M=(m_{i})_{i=0}^{\infty}$ of integers such that $m_{0}=1$, $m_{i}\geq 2$ for $i\geq 1$, let $p_{M}(n)$ denote the number of partitions of $n$ into parts of the form $m_{0}m_{1}\cdots m_{r}$. In this paper we show that for every positive integer $n$ the following congruence is true: \begin{align*} p_{M}(m_{1}m_{2}\cdots m_{r}n-1)\equiv 0\ \ \l

Jason DeBlois

The first main results of this note establish forms of the hyperbolic laws of cosines and sines for certain classes of quadrilaterals and pentagons in the hyperbolic plane, having at least one ideal vertex and right angles at non-ideal vertices, in which the length of a horocyclic cross-section at an ideal vertex plays the role filled by the dihedral angle i

Lucas Theis

The last decade has seen tremendous progress in our ability to generate realistic-looking data, be it images, text, audio, or video. Here, we discuss the closely related problem of quantifying realism, that is, designing functions that can reliably tell realistic data from unrealistic data. This problem turns out to be significantly harder to solve and remai

Rashindrie Perera, Saman Halgamuge

In this paper, we look at cross-domain few-shot classification which presents the challenging task of learning new classes in previously unseen domains with few labelled examples. Existing methods, though somewhat effective, encounter several limitations, which we alleviate through two significant improvements. First, we introduce a lightweight parameter-eff

Pietro Benedusi, Ada J. Ellingsrud, Halvor Herlyng, Marie E. Rognes

The activity and dynamics of excitable cells are fundamentally regulated and moderated by extracellular and intracellular ion concentrations and their electric potentials. The increasing availability of dense reconstructions of excitable tissue at extreme geometric detail pose a new and clear scientific computing challenge for computational modelling of ion

Michael Blank

Appeals to randomness in various number-theoretic constructions appear regularly in modern scientific publications. Such famous names as V.I. Arnold, M. Katz, Ya.G. Sinai, and T. Tao are just a few examples. Unfortunately, all of these approaches rely on various, although often very non-trivial and elegant, heuristics. A new analytical approach is proposed t

Saad Kriouile, Mohamad Assaad, Deniz Gündüz, Touraj Soleymani

In this paper, we investigate denial-of-service attacks against status updating. The target system is modeled by a Markov chain and an unreliable wireless channel, and the performance of status updating in the target system is measured based on two metrics: age of information and age of incorrect information. Our objective is to devise optimal attack policie

Gerardo Suárez, Marcin Łobejko, Michał Horodecki

In recent years, there has been tremendous focus on identifying whether effective descriptions of open quantum systems such as master equations, can accurately describe the dynamics of open quantum systems. One particular question is whether they provide the correct steady state in the long time limit. Transient regime is also of interest. Description of evo

Swetha Nair, Giovanni Pireddu, Benjamin Rotenberg

We study the charge induced in a Thomas-Fermi metal by an ion in vacuum, using an atomistic description employed in constant-potential molecular dynamics simulations, and compare the results with the predictions from continuum electrostatics. Specifically, we investigate the effects of the Thomas-Fermi screening length $l_{TF}$ and the position $d$ of the io

Shion Yamashika, Filiberto Ares, Pasquale Calabrese

The quantum Mpemba effect is the counter-intuitive non-equilibrium phenomenon wherein the dynamic restoration of a broken symmetry occurs more rapidly when the initial state exhibits a higher degree of symmetry breaking. The effect has been recently discovered theoretically and observed experimentally in the framework of global quantum quenches, but so far i

Haleh Hayati, Nathan van de Wouw, Carlos Murguia

Cloud computing enables users to process and store data remotely on high-performance computers and servers by sharing data over the Internet. However, transferring data to clouds causes unavoidable privacy concerns. Here, we present a synthesis framework to design coding mechanisms that allow sharing and processing data in a privacy-preserving manner without

Dovile Juodelyte, Yucheng Lu, Amelia Jiménez-Sánchez, Sabrina Bottazzi

Transfer learning has become an essential part of medical imaging classification algorithms, often leveraging ImageNet weights. The domain shift from natural to medical images has prompted alternatives such as RadImageNet, often showing comparable classification performance. However, it remains unclear whether the performance gains from transfer learning ste