December 2023 arXiv papers — page 54

William Heyden, Habib Ullah, M. Salman Siddiqui, Fadi Al Machot

Zero-Shot Learning (ZSL) presents the challenge of identifying categories not seen during training. This task is crucial in domains where it is costly, prohibited, or simply not feasible to collect training data. ZSL depends on a mapping between the visual space and available semantic information. Prior works learn a mapping between spaces that can be exploi

Jan Turczynowicz, Radost Waszkiewicz, Łukasz Gładczuk

Although it is commonly expected that a metal disk placed on the surface of water will sink, our investigation has revealed a surprising phenomenon: a vertical jet directed onto the disk from above can allow it to remain afloat. This result defies intuition, as one would assume that the force of the jet's impact would cause the disk to sink. We have discover

Roberto De Prisco

We consider the generalized Fibonacci counting problem with rabbits that become fertile at age $f$ and die at age $d$, with $1<=f<=d$ and $d$ finite or infinite. We provide a simple proof, based exclusively on a counting argumentation, for a recursive formula that gives the $n$th generalized Fibonacci number as a function of at most 3 previous numbers. The f

Mary Ryan Baumann, Denise Esserman, Monica Taljaard, Fan Li

Stepped wedge cluster randomized trials (SW-CRTs) are a form of randomized trial whereby clusters are progressively transitioned from control to intervention, with the timing of transition randomized for each cluster. An important task at the design stage is to ensure that the planned trial has sufficient power. While methods for determining power have been

Elizaveta Kuznetsova, Mykola Makhortykh, Victoria Vziatysheva, Martha Stolze

This article presents a comparative analysis of the ability of two large language model (LLM)-based chatbots, ChatGPT and Bing Chat, recently rebranded to Microsoft Copilot, to detect veracity of political information. We use AI auditing methodology to investigate how chatbots evaluate true, false, and borderline statements on five topics: COVID-19, Russian

Oscar Bouverot-Dupuis, Saptarshi Majumdar, Alberto Rosso, Laura Foini

We study an XXZ spin chain at zero magnetization coupled to a collection of local harmonic baths at zero temperature. We map this system on a (1+1)D effective field theory using bosonization, where the effect of the bath is taken care of in an exact manner. We provide analytical and numerical evidence of the existence of two phases at zero temperature: a Lut

George Bisbas, Rhodri Nelson, Mathias Louboutin, Fabio Luporini

Partial differential equations (PDEs) are crucial in modeling diverse phenomena across scientific disciplines, including seismic and medical imaging, computational fluid dynamics, image processing, and neural networks. Solving these PDEs at scale is an intricate and time-intensive process that demands careful tuning. This paper introduces automated code-gene

Jingping Li

Using the in-in formalism, we generalize the recently constructed magnetoelastic EFT arXiv:2112.13873 [hep-th] to describe the damping dynamics of ferromagnetic systems at long wavelengths. We find that the standard Gilbert damping term naturally arises as the simplest leading-order symmetry-consistent non-conservative contribution within the in-in framework

Jens O. Andersen, Martin Kjøllesdal Johnsrud, Qing Yu, Hua Zhou

We present recent results in three-flavor chiral perturbation theory at finite isospin $\mu_I$ and strangeness $\mu_s$ chemical potentials at zero temperature. The phase diagram to ${\cal O}(p^2)$ in the $\mu_I$--$\mu_S$ plane is mapped out with and without electromagnetic effects. The phase diagram consists of a vacuum phase and three Bose-condensed phases

Abdallah Dib, Luiz Gustavo Hafemann, Emeline Got, Trevor Anderson

Reconstructing an avatar from a portrait image has many applications in multimedia, but remains a challenging research problem. Extracting reflectance maps and geometry from one image is ill-posed: recovering geometry is a one-to-many mapping problem and reflectance and light are difficult to disentangle. Accurate geometry and reflectance can be captured und

Joseph Heyward, João Carreira, Dima Damen, Andrew Zisserman

The First Perception Test challenge was held as a half-day workshop alongside the IEEE/CVF International Conference on Computer Vision (ICCV) 2023, with the goal of benchmarking state-of-the-art video models on the recently proposed Perception Test benchmark. The challenge had six tracks covering low-level and high-level tasks, with both a language and non-l

Tal Kadosh, Niranjan Hasabnis, Vy A. Vo, Nadav Schneider

With easier access to powerful compute resources, there is a growing trend in AI for software development to develop large language models (LLMs) to address a variety of programming tasks. Even LLMs applied to tasks from the high-performance computing (HPC) domain are huge in size and demand expensive compute resources for training. This is partly because LL

Marina Fernández Galán, Javier Serrano, Enrique Conejero Jarque, Rocío Borrego-Varillas

High-order harmonic generation (HHG) arising from the non-perturbative interaction of intense light fields with matter constitutes a well-established tabletop source of coherent extreme-ultraviolet and soft X-ray radiation, which is typically emitted as attosecond pulse trains. However, ultrafast applications increasingly demand isolated attosecond pulses (I

Penying Rochanakul, Hatairat Yingtaweesittikul, Sayan Panma

A weak homomorphism from a graph G to a graph H is a mapping f from V(G) to V(H), where either f(x) = f(y) or {f(x), f(y)} is an element of E(H), and this holds for all {x, y} in E(G). A rectangular grid graph is formed by taking the Cartesian product of two paths. In this paper, we present a formula for calculating the number of weak homomorphisms from path

Łucja Kipczak, Arka Karmakar, Magdalena Grzeszczyk, Róża Janiszewska

We investigate the vibrational and magnetic properties of thin layers of chromium tribromide (CrBr$_3$) with a thickness ranging from three to twenty layers (3~L to 20~L) revealed by the Raman scattering (RS) technique. Systematic dependence of the RS process efficiency on the energy of the laser excitation is explored for four different excitation energies:

Veronica Lora, Thomas Nony, Alejandro Esquivel, Roberto Galván-Madrid

Variable accretion has been well studied in evolved stages of low-mass stars formation. However, the accretion history in the initial phases of star formation is still a seldom studied topic. The outflows and jets emerging from protostellar objects could shed some light onto their accretion history. We consider the recently studied case of W43-MM1, a protocl

Mahyar Pourjabar, Manuele Rusci, Luca Bompani, Lorenzo Lamberti

This work presents a multi-sensory anti-collision system design to achieve robust autonomous exploration capabilities for a swarm of 10 cm-side nano-drones operating on object detection missions. We combine lightweight single-beam laser ranging to avoid proximity collisions with a long-range vision-based obstacle avoidance deep learning model (i.e., PULP-Dro

Giacomo Borghi, Michael Herty

Model predictive control strategies require to solve in an sequential manner, many, possibly non-convex, optimization problems. In this work, we propose an interacting stochastic agent system to solve those problems. The agents evolve in pseudo-time and in parallel to the time-discrete state evolution. The method is suitable for non-convex, non-differentiabl

Alexandra Zytek, Wei-En Wang, Dongyu Liu, Laure Berti-Equille

Users in many domains use machine learning (ML) predictions to help them make decisions. Effective ML-based decision-making often requires explanations of ML models and their predictions. While there are many algorithms that explain models, generating explanations in a format that is comprehensible and useful to decision-makers is a nontrivial task that can

Yaser Alizadeh, Nino Bašić, Ivan Damnjanović, Tomislav Došlić

A nonnegative integer $p$ is realizable by a graph-theoretical invariant $I$ if there exist a graph $G$ such that $I(G) = p$. The inverse problem for $I$ consists of finding all nonnegative integers $p$ realizable by $I$. In this paper, we consider and solve the inverse problem for the Mostar index, a recently introduced graph-theoretical invariant which att

Eugenia Celada, Tao Han, Wolfgang Kilian, Nils Kreher

We study the capabilities of a muon collider, at 3 and 10 TeV center-of-mass energy, of probing the interactions of the Higgs boson with the muon. We consider all the possible processes involving the direct production of EW bosons ($W,Z$ and $H$) with up to five particles in the final state. We study these processes both in the HEFT and SMEFT frameworks, ass

Sushil Sharma, Arindam Das, Ganesh Sistu, Mark Halton

Trajectory prediction is, naturally, a key task for vehicle autonomy. While the number of traffic rules is limited, the combinations and uncertainties associated with each agent's behaviour in real-world scenarios are nearly impossible to encode. Consequently, there is a growing interest in learning-based trajectory prediction. The proposed method in this pa

Xiang-Mao Ding, Ting Zhang

For non-simple laced Lie algebras, the $\text{B}_{N}$ and $\text{C}_{N}$ are Langlands dual to each other in mathematical. In this article, we give another Bethe/Gauge correspondence between 3d (or 2d) classical Lie group supersymmetry gauge theory with closed and open $\text{XXZ}$ (or $\text{XXX}$) spin chain. Here, the representations of the $\text{ADE}$ L

Sameer Ahmad Mir, Nasir Ahmad Rather, Iqbal Mohi Ud Din, Saeed Uddin

We investigate relative hadron yield production of various like and unlike mass particles in ultra-relativistic heavy ion collisions by employing a statistical thermal model with finite-sized baryons (antibaryons) to imitate the hard-core repulsive interactions leading to the excluded volume type effect. A strong evidence of strangeness suppression relative

Daniel Rosen, Illa Rochez, Caleb McIrvin, Joshua Lee

Radio Frequency Reinforcement Learning (RFRL) is anticipated to be a widely applicable technology in the next generation of wireless communication systems, particularly 6G and next-gen military communications. Given this, our research is focused on developing a tool to promote the development of RFRL techniques that leverage spectrum sensing. In particular,

Federico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga, Paolo Emilio Mazzon

SelfEEG is an open-source Python library developed to assist researchers in conducting Self-Supervised Learning (SSL) experiments on electroencephalography (EEG) data. Its primary objective is to offer a user-friendly but highly customizable environment, enabling users to efficiently design and execute self-supervised learning tasks on EEG data. SelfEEG cove

Paweł Goldstein, Zofia Grochulska, Piotr Hajłasz

We prove that for any measurable mapping $T$ into the space of matrices with positive determinant, there is a diffeomorphism whose derivative equals $T$ outside a set of measure less than $\varepsilon$. We use this fact to prove that for any measurable mapping $T$ into the space of matrices with non-zero determinant (with no sign restriction), there is an al

Jaume Llabres, Sara Oliver-Bonafoux, Celia Anteneodo, Raul Toral

Changes of mind can become less likely the longer an agent has adopted a given opinion state. This resilience or inertia to change has been called ``aging''. We perform a comparative study of the effects of aging on the critical behavior of two standard opinion models with pairwise interactions. One of them is the voter model, which is a two-state model with

Lin Xie, Hanyi Li

In the context of Industry 4.0, the physical and digital worlds are closely connected, and robots are widely used to achieve system automation. Digital twin solutions have contributed significantly to the growth of Industry 4.0. Combining various technologies is a trend that aims to improve system performance. For example, digital twinning can be combined wi

Junsu Park, Bogeun Gwak

We investigate the bound on the Lyapunov exponents by a charged particle in Kerr-Newman-de Sitter black holes using analytic and numerical methods. We determine whether the Lyapunov exponent can exceed the bound by an electrically charged particle with an angular momentum. Our tests are applied to the de Sitter spacetime by the positive cosmological constant

Sebastian Halbig, Tony Zorman

We extend Willerton's graphical calculus for bimonads to comodule monads, a monadic interpretation of module categories over a monoidal category. As an application, we prove a version of Tannaka--Krein duality for these structures.

Huajian Xue

In this article, we study the full theta lifting for two cases of type II reductive dual pairs over a nonarchimedean local field. Firstly, we determine the structure of the full theta lifts of all irreducible representations for dual pair $(\mathrm{GL}(2),\mathrm{GL}(2))$. Secondly, we prove that the full theta lift of an irreducible tempered representation

Jiong-Jiong Liu, Zhan-Wei Liu, Kan Chen, Dan Guo

We examine the internal structure of the $\Lambda(1670)$ through an analysis of lattice QCD simulations and experimental data within Hamiltonian effective field theory. Two scenarios are presented. The first describes the $\Lambda(1670)$ as a bare three-quark basis state, which mixes with the $\pi\Sigma$, $\bar{K}N$, $\eta\Lambda$ and $K\Xi$ meson-baryon cha

Xingyilang Yin, Xi Yang, Liangchen Liu, Nannan Wang

Recently MLP-based methods have shown strong performance in point cloud analysis. Simple MLP architectures are able to learn geometric features in local point groups yet fail to model long-range dependencies directly. In this paper, we propose Point Deformable Network (PDNet), a concise MLP-based network that can capture long-range relations with strong repr

Nguyen Hong Quang, Nguyen Thi Kim Thanh, Nguyen Que Huong

We theoretically study biexcitons and quadrons in quantum dots with parabolic confinement and give a complete comparison between the two excitations. The calculation of quadron and biexciton binding energies as functions of electron-to-hole confinement potentials and mass ratios, using unrestricted Hartree-Fock method, shows the essential differences between

Peter Smith, Michael Line, Jacob Bean, Matteo Brogi

Ground-based, high-resolution and space-based, low-resolution spectroscopy are the two main avenues through which transiting exoplanet atmospheres are studied. Both methods provide unique strengths and shortcomings, and combining the two can be a powerful probe into an exoplanet's atmosphere. Within a joint atmospheric retrieval framework, we combined JWST N

Abdulkadir Celikkanat, Nikolaos Nakis, Morten Mørup

Over the past two decades, there has been a tremendous increase in the growth of representation learning methods for graphs, with numerous applications across various fields, including bioinformatics, chemistry, and the social sciences. However, current dynamic network approaches focus on discrete-time networks or treat links in continuous-time networks as i

F. Sattin, D. F. Escande, M. Gobbin, I. Predebon

The ion temperature during magnetic reconnections measured along the direction of the magnetic field at the MST Reverse Field Pinch has not yet received a satisfactory theoretical explanation. In this work we argue that it is consistent with a picture of ion energization by the parallel electric fields generated by the plasma during reconnection, and thermal

Yue-Jiang Dong, Yuan-Chen Guo, Ying-Tian Liu, Fang-Lue Zhang

Self-supervised monocular depth estimation is of significant importance with applications spanning across autonomous driving and robotics. However, the reliance on self-supervision introduces a strong static-scene assumption, thereby posing challenges in achieving optimal performance in dynamic scenes, which are prevalent in most real-world situations. To ad

Andrea Cavagna, Javier Cristín, Irene Giardina, Mario Veca

Numerical analysis of conserved field dynamics has been generally performed with pseudo spectral methods. Finite differences integration, the common procedure for non-conserved field dynamics, indeed struggles to implement a conservative noise in the discrete spatial domain. In this work, we present a novel method to generate a conservative noise in the fini

Mengxiao Zhang, Yongqiang Tian, Zhenyang Xu, Yiwen Dong

Program reduction is a prevalent technique to facilitate compilers' debugging by automatically minimizing bug-triggering programs. Existing program reduction techniques are either generic across languages (e.g., Perses and Vulcan) or specifically customized for one certain language by employing language-specific features, like C-Reduce. However, striking the

Kuldeep S. Meel, Sourav Chakraborty, Umang Mathur

Given a non-deterministic finite automaton (NFA) A with m states, and a natural number n (presented in unary), the #NFA problem asks to determine the size of the set L(A_n) of words of length n accepted by A. While the corresponding decision problem of checking the emptiness of L(A_n) is solvable in polynomial time, the #NFA problem is known to be #P-hard. R

Jason Aebischer

One-loop Fierz identities are discussed, together with general basis transformations in Effective Field theories at the tree- and one-loop level. To this end, the notion of one-loop shifts is introduced, together with several examples that illustrate the virtues of this method.

Zdeněk Dvořák, Benjamin Moore, Michaela Seifrtová, Robert Šámal

We consider the 4-precoloring extension problem in \emph{planar near-Eulerian-triangulations}, i.e., plane graphs where all faces except possibly for the outer one have length three, all vertices not incident with the outer face have even degree, and exactly the vertices incident with the outer face are precolored. We give a necessary topological condition f

Jingxuan Chen, Qian Wu, Xurong Chen, Qian Wang

The potential existence of a fifth fundamental force, mediated by the X17 boson, has generated significant interest. This force can manifest itself as either a vector or pseudoscalar particle. In order to gain insight into the effective potentials produced by the X17 boson for hyperfine interactions in muonic systems, we conduct calculations for both the pse

Alessio Zaccone, Vladimir M. Fomin

The supercurrent field effect is experimentally realized in various nano-scale devices, based on the superconductivity suppression by external electric fields being effective for confined systems. In spite of intense research, a microscopic theory and explanation of this effect is missing. Here, a microscopic theory of phonon-mediated superconductivity in th

Martijn Kluitenberg

We generalize the Cheeger inequality, a lower bound on the first nontrivial eigenvalue of a Laplacian, to the case of geometric sub-Laplacians on rank-varying Carnot-Carath\'eodory spaces and we describe a concrete method to lower bound the Cheeger constant. The proof is geometric, and works for Dirichlet, Neumann and mixed boundary conditions. One of the ma

Alessandro Gnoatto, Silvia Lavagnini

We provide a general HJM framework for forward contracts written on abstract market indices with arbitrary fixing and payment adjustments, and featuring collateralization in any currency denominations. In view of this, we first provide a thorough study of cross-currency markets in the presence of collateral and incompleteness. Then we give a general treatmen

Giulia Aleixo, Herondy Mota

In this work we consider lightcone fluctuation effects in a five-dimensional spacetime arising as a consequence of the compactification of the extra dimension via a quasiperiodic condition, characterized by a phase angle $2\pi\alpha$. By considering light propagating in a non-compactified direction we are able to compute both the renormalized graviton two-po

Mohamed H. Abdullah, Anatoly Klypin, Francisco Prada, Gillian Wilson

We measure the two point correlation function (CF) of 1357 galaxy clusters with a mass of $\log_{10}{M_{200}}\geq 13.6$~\hm~and at a redshift of $z \leq 0.125$. This work differs from previous analyses in that it utilizes a spectroscopic cluster catalogue, $\mathtt{SDSS-GalWCat}$, to measure the CF and detect the baryon acoustic oscillation (BAO) signal. Unl

Jordan Vice, Naveed Akhtar, Richard Hartley, Ajmal Mian

Bias in text-to-image (T2I) models can propagate unfair social representations and may be used to aggressively market ideas or push controversial agendas. Existing T2I model bias evaluation methods only focus on social biases. We look beyond that and instead propose an evaluation methodology to quantify general biases in T2I generative models, without any pr

Piotr Pokora

The main purpose of the present paper is to provide a partial classification, performed with respect the weak-combinatorics, of free arrangements consisting of lines and one smooth conic with quasi-homogeneous ordinary singularities.

Alexander C. Tyner

Multiple software packages currently exist for the computation of bulk topological invariants in both idealized tight-binding models and realistic Wannier tight-binding models derived from density functional theory. Currently, only one package, PythTB(https://www.physics.rutgers.edu/pythtb/) is capable of computing nested Wilson loops and spin-resolved Wilso

Rafael Boto, Dipankar Das, Jorge C. Romao, Ipsita Saha

Current measurement of the $h\to Z\gamma$ signal strength invite us to speculate about possible new physics interactions that exclusively affect $\mu_{Z\gamma}$ without altering the other signal strengths. Additional consideration of tree-unitarity enables us to correlate the nonstandard values of $\mu_{Z\gamma}$ with an upper limit on the scale of new physi

Eric Lindström, Larisa Beilina

The aim of this article is to investigate the well-posedness, stability and convergence of solutions to the time-dependent Maxwell's equations for electric field in conductive media in continuous and discrete settings. The situation we consider would represent a physical problem where a subdomain is emerged in a homogeneous medium, characterized by constant

Chan Xu, Shuowen Zhang

In this paper, we study a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system where one multi-antenna base station (BS) sends information to a user with multiple antennas in the downlink and simultaneously senses the location parameter of a target based on its reflected echo signals received back at the BS receive antenna

Wojciech Bielas, Mateusz Kula, Szymon Plewik

Motivated by results of J. R. Kline and R. L. Moore (1919) that a compact subset of the plane, homeomorphic to a subset of the reals, lies on the arc, we give a purely topological characterisation of compact sets of the reals. This allows us to reduce investigations of Cantorvals to properties of countable linear orders and to show, applying the Mazurkiewicz

Alexey Chernyshev, Vladimir Saleev

In the article, we study associated production of prompt $J/\psi(\Upsilon)$ and $D-$mesons in the improved color evaporation model using the high-energy factorization approach as it is realized in the Monte-Carlo event generator KaTie. The modified Kimber-Martin-Ryskin-Watt model for unintegrated parton distribution functions is used. We predict cross sectio

Shuai Ma, Haihong Sheng, Junchang Sun, Hang Li

Light fidelity (LiFi) is a potential key technology for future 6G networks. However, its feasibility of supporting mobile communications has not been fundamentally discussed. In this paper, we investigate the time-varying channel characteristics of mobile LiFi based on measured mobile phone rotation and movement data. Specifically, we define LiFi channel coh

Zhaoran Hou, Samuel W. K. Wong

State space models (SSMs) are widely used to describe dynamic systems. However, when the likelihood of the observations is intractable, parameter inference for SSMs cannot be easily carried out using standard Markov chain Monte Carlo or sequential Monte Carlo methods. In this paper, we propose a particle Gibbs sampler as a general strategy to handle SSMs wit

Belle II Collaboration, I. Adachi, L. Aggarwal, H. Ahmed

We search for the $e^+e^-\to\eta_b(1S)\omega$ and $e^+e^-\to\chi_{b0}(1P)\omega$ processes at a center-of-mass energy of 10.745 GeV, which is close to the peak of the $\Upsilon(10753)$ state. We use data collected by the Belle II experiment during a special run, corresponding to an integrated luminosity of $9.8\,\mathrm{fb}^{-1}$. We reconstruct $\omega\to\p

C. Itoi, Y. Sakamoto

Nishimori's gauge theory is extended to the quantum XYZ $p$-spin glass model in finite dimensions. This enables us to obtain useful correlation equalities, which show also that Duhamel correlation functions at an arbitrary temperature are bounded by those in the corresponding classical model on the Nishimori line. These bounds give that the spontaneous magne

Kasim Tasdemir, Rafiullah Khan, Fahad Siddiqui, Sakir Sezer

Detecting SQL Injection (SQLi) attacks is crucial for web-based data center security, but it is challenging to balance accuracy and computational efficiency, especially in high-speed networks. Traditional methods struggle with this balance, while NLP-based approaches, although accurate, are computationally intensive. We introduce a novel cascade SQLi detecti

Weixuan Wang, Barry Haddow, Alexandra Birch

Knowledge represented in Large Language Models (LLMs) is quite often incorrect and can also become obsolete over time. Updating knowledge via fine-tuning is computationally resource-hungry and not reliable, and so knowledge editing (KE) has developed as an effective and economical alternative to inject new knowledge or to fix factual errors in LLMs. Although

Charlie Hoy, Laura K. Nuttall

The Laser Interferometer Space Antenna (LISA) is scheduled to launch in the mid 2030s, and is expected to observe gravitational-wave candidates from massive black-hole binary mergers, extreme mass-ratio inspirals, and more. Accurately inferring the source properties from the observed gravitational-wave signals is crucial to maximise the scientific return of

Raphael Fischer, Amal Saadallah

Automated machine learning (AutoML) streamlines the creation of ML models. While most methods select the "best" model based on predictive quality, it's crucial to acknowledge other aspects, such as interpretability and resource consumption. This holds particular importance in the context of deep neural networks (DNNs), as these models are often perceived as

Hisham Sati, Urs Schreiber

While it has become widely appreciated that defining (higher) gauge theories requires, in addition to ordinary phase space data, also "flux quantization" laws in generalized differential cohomology, there has been little discussion of the general rules, if any, for lifting Poisson-brackets of (flux-)observables and their quantization from traditional phase s

Chen Ding, Xiao-Yue Xu, Shuo Zhang, Wan-Su Bao

Quantum state readout serves as the cornerstone of quantum information processing, exerting profound influence on quantum communication, computation, and metrology. In this study, we introduce an innovative readout architecture called Compression Shadow (CompShadow), which transforms the conventional readout paradigm by compressing multi-qubit states into si

Md Zobaer Islam, Sabit Ekin, John F. O'Hara, Gary Yen

In this study, we present a deep learning-based approach for time-series respiration data classification. The dataset contains regular breathing patterns as well as various forms of abnormal breathing, obtained through non-contact incoherent light-wave sensing (LWS) technology. Given the one-dimensional (1D) nature of the data, we employed a 1D convolutional

Alexander Yu. Vlasov

The cellular automaton is a widely known model of both reversible and irreversible computations. The family of reversible second-order cellular automata considered in this work is appropriate both for construction of logic gates and analysis of damage distribution. The quantities such as formal dimension of damage patterns can be used only for rough estimati

Param Rajpura, Hubert Cecotti, Yogesh Kumar Meena

This review paper provides an integrated perspective of Explainable Artificial Intelligence techniques applied to Brain-Computer Interfaces. BCIs use predictive models to interpret brain signals for various high-stake applications. However, achieving explainability in these complex models is challenging as it compromises accuracy. The field of XAI has emerge

Weigang Lu, Ziyu Guan, Wei Zhao, Yaming Yang

Graph Neural Networks (GNNs) have become mainstream methods for solving the semi-supervised node classification problem. However, due to the uneven location distribution of labeled nodes in the graph, labeled nodes are only accessible to a small portion of unlabeled nodes, leading to the \emph{under-reaching} issue. In this study, we firstly reveal under-rea

Zijian Li, Zhihui Wang

Generative Adversarial Networks (GANs) have become a ubiquitous technology for data generation, with their prowess in image generation being well-established. However, their application in generating tabular data has been less than ideal. Furthermore, attempting to incorporate differential privacy technology into these frameworks has often resulted in a degr

Xin Wang, Lizhi Wang, Xiangtian Ma, Maoqing Zhang

Dual-Camera Compressed Hyperspectral Imaging (DCCHI) offers the capability to reconstruct 3D Hyperspectral Image (HSI) by fusing compressive and Panchromatic (PAN) image, which has shown great potential for snapshot hyperspectral imaging in practice. In this paper, we introduce a novel DCCHI reconstruction network, the Intra-Inter Similarity Exploiting Trans

Enrico Marchetto, Alessio Miscioscia, Elli Pomoni

We study CFTs at finite temperature and derive explicit sum rules for one-point functions of operators by imposing the KMS condition. In the case of a large gap between light and heavy operators, we explicitly compute one-point functions for light operators. Turning to heavy operators we employ Tauberian theorems and compute the asymptotic OPE density for he

Julia Kharlan, Krzysztof Sobucki, Krzysztof Szulc, Sara Memarzadeh

Eddy currents in a superconductor shield the magnetic field in its interior and are responsible for the formation of a magnetic stray field outside of the superconducting structure. The stray field can be controlled by the external magnetic field and affect the magnetization dynamics in the magnetic system placed in its range. In the case of a hybrid system

Shubham Kejriwal, Lorenzo Speri, Alvin J. K. Chua

In gravitational-wave astronomy, extreme-mass-ratio-inspiral (EMRI) sources for the upcoming LISA observatory have the potential to serve as high-precision probes of astrophysical environments in galactic nuclei, and of potential deviations from general relativity (GR). Such ``beyond vacuum-GR'' effects are often modeled as perturbations to the evolution of

Byung Hyun Lee, Min-hwan Oh, Se Young Chun

Task Free online continual learning (TF-CL) is a challenging problem where the model incrementally learns tasks without explicit task information. Although training with entire data from the past, present as well as future is considered as the gold standard, naive approaches in TF-CL with the current samples may be conflicted with learning with samples in th

Ashish Seth, Sreyan Ghosh, S. Umesh, Dinesh Manocha

Continued pre-training (CP) offers multiple advantages, like target domain adaptation and the potential to exploit the continuous stream of unlabeled data available online. However, continued pre-training on out-of-domain distributions often leads to catastrophic forgetting of previously acquired knowledge, leading to sub-optimal ASR performance. This paper

Edward Black, Juliana Morbec

Heterostructures composed of pentacene (PEN) molecules and transition metal dichalchogenides (TMDs) are promising materials for small, flexible and lightweight photovoltaic devices and various other optoelectronic applications. The effects of changing concentration and orientation of adsorbed pentacene molecules on two-dimensional monolayer substrates of TMD

Håkon Robbestad Gylterud, Elisabeth Stenholm

Homotopy type theory (HoTT) can be seen as a generalisation of structural set theory, in the sense that 0-types represent structural sets within the more general notion of types. For material set theory, we also have concrete models as 0-types in HoTT, but this does not currently have any generalisation to higher types. The aim of this paper is to give such

Chao Han, Yudong Yan

Visual defect detection plays an important role in intelligent industry. Patch based methods consider visual images as a collection of image patches according to positions, which have stronger discriminative ability for small defects in products, e.g. scratches on pills. However, the nearest neighbor search for the query image and the stored patches will occ

Ziwei Zhang, Mengtao Zhu, Jiabin Liu, Yunjie Li

Automatic Modulation Recognition (AMR) is a crucial technology in the domains of radar and communications. Traditional AMR approaches assume a closed-set scenario, where unknown samples are forcibly misclassified into known classes, leading to serious consequences for situation awareness and threat assessment. To address this issue, Automatic Modulation Open

Alexey V. Nenashev, Florian Gebhard, Klaus Meerholz, Sergei D. Baranovskii

The space- and temperature-dependent electron distribution $n(r,T)$ determines optoelectronic properties of disordered semiconductors. It is a challenging task to get access to $n(r,T)$ in random potentials, avoiding the time-consuming numerical solution of the Schr\"{o}dinger equation. We present several numerical techniques targeted to fulfill this task. F

Simon Pfahler, Peter Georg, Rudolf Schill, Maren Klever

The Kullback-Leibler (KL) divergence is frequently used in data science. For discrete distributions on large state spaces, approximations of probability vectors may result in a few small negative entries, rendering the KL divergence undefined. We address this problem by introducing a parameterized family of substitute divergence measures, the shifted KL (sKL

Santiago Llorens, Gael Sentís, Ramon Muñoz-Tapia

A source assumed to prepare a specified reference state sometimes prepares an anomalous one. We address the task of identifying these anomalous states in a series of $n$ preparations with $k$ anomalies. We analyze the minimum-error protocol and the zero-error (unambiguous) protocol and obtain closed expressions for the success probability when both reference

Xin Guan, Jean-Marc Vanden-Broeck

We devise a new time-stepping algorithm for two-dimensional nonlinear unsteady surface and interfacial waves. The algorithm uses Cauchy's integral formula, which only requires information on the interface, to solve Laplace equation by using iterative techniques. We derive Eulerian and mixed Eulerian-Lagrangian descriptions by using arclength to parameterize

José Raimundo Carvalho, Diego de Maria André

Addressing unit nonresponse between waves of longitudinal studies using sampling design in weighting has recently incorporated a new strategy based on the availability of supplemental samples, collecting either refreshment or replacement samples on an ongoing larger sample. We implement an approach for calculating individual cross-sectional weights and apply

Mauricio Gómez Viloria, Riccardo Messina, Philippe Ben-Abdallah

We introduce a direct (Seebeck) and inverse (Peltier) thermoelectric effect induced by electron tunneling between closely separated conducting films. When a transverse temperature gradient is applied along one of two films, a bias voltage is induced in the second thanks to the heat transfer mediated by electrons tunneling through the separation gap. We highl

Yuming Gu, You Xie, Hongyi Xu, Guoxian Song

We present DiffPortrait3D, a conditional diffusion model that is capable of synthesizing 3D-consistent photo-realistic novel views from as few as a single in-the-wild portrait. Specifically, given a single RGB input, we aim to synthesize plausible but consistent facial details rendered from novel camera views with retained both identity and facial expression

Alessia Silvia Ivani, Federica Barontini, Manuel G. Catalano, Giorgio Grioli

The use of vibrotactile feedback is of growing interest in the field of prosthetics, but few devices fully integrate this technology in the prosthesis to transmit high-frequency contact information (such as surface roughness and first contact) arising from the interaction of the prosthetic device with external items. This study describes a wearable vibrotact

Kenneth Chan, Jason Gaddis, Robert Won, James J. Zhang

We study the ozone group of noetherian Artin--Schelter regular algebras satisfying a polynomial identity (or PI for short). The ozone group was shown in previous work by the authors to be an important invariant in the study of PI skew polynomial rings and their centers. In this paper, we show that skew polynomial rings are in fact characterized as those alge

Xianzhen Guo, Qin Shi, Shuowen Zhang, Chengwen Xing

This paper investigates user equipment (UE) assisted device-free networked sensing in the sixth-generation (6G) integrated sensing and communication (ISAC) system, where one base station (BS) and multiple UEs, such as unmanned aerial vehicles (UAVs), serve as anchors to cooperatively localize multiple passive targets based on the range information. Three cha

Cosmina-Cristina Ratiu, Christoph Mayr-Dorn, Alexander Egyed

Engineering processes for safety-critical systems describe the steps and sequence that guide engineers from refining user requirements into executable code, as well as producing the artifacts, traces, and evidence that the resulting system is of high quality. Process compliance focuses on ensuring that the actual engineering work is followed as closely as po

Klaus Kroencke, Louis Yudowitz

We prove dynamical stability and instability theorems for Poincar\'{e}-Einstein metrics under the Ricci flow. Our key tool is a variant of the expander entropy for asymptotically hyperbolic manifolds, which Dahl, McCormick and the first author established in a recent article. It allows us to characterize stability and instability in terms of a local positive

Dong Huang, Jie M. Zhang, Michael Luck, Qingwen Bu

The advancement of natural language processing (NLP) has been significantly boosted by the development of transformer-based large language models (LLMs). These models have revolutionized NLP tasks, particularly in code generation, aiding developers in creating software with enhanced efficiency. Despite their advancements, challenges in balancing code snippet

Marina Gnocco, Manuel G. Catalano, Giorgio Grioli, Carlo Trompetto

One of the most frequent and severe aftermaths of a stroke is the loss of upper limb functionality. Therapy started in the sub-acute phase proved more effective, mainly when the patient participates actively. Recently, a novel set of rehabilitation and support robotic devices, known as supernumerary robotic limbs, have been introduced. This work investigates

Ishan Rajendrakumar Dave, Simon Jenni, Mubarak Shah

Self-supervised approaches for video have shown impressive results in video understanding tasks. However, unlike early works that leverage temporal self-supervision, current state-of-the-art methods primarily rely on tasks from the image domain (e.g., contrastive learning) that do not explicitly promote the learning of temporal features. We identify two fact

Antonino Ficarra

We introduce the Macaulay2 package MatchingPowers. It allows to compute and manipulate the matching powers of a monomial ideal. The basic theory of matching powers is explained and the main features of the package are presented.

Antonino Ficarra

In the present paper, motivated by a conjecture of Jahan and Zheng, we prove that componentwise polymatroidal ideals have linear quotients. This solves positively a conjecture of Bandari and Herzog.