April 2024 arXiv papers — page 101

Zhaoxing Chen, Wei Liu, Ziqing Xie, Wenfan Yi

A Nehari manifold optimization method (NMOM) is introduced for finding 1-saddles, i.e., saddle points with the Morse index equal to one, of a generic nonlinear functional in Hilbert spaces. Actually, it is based on the variational characterization that 1-saddles of this functional are local minimizers of the same functional restricted on the associated Nehar

Nadia Na Li, Wenchang Chu

By means of the generating function method, a linear recurrence relation is explicitly resolved. The solution is expressed in terms of the Stirling numbers of both the first and the second kind. Two remarkable pairs of combinatorial identities are established as applications, that contain some well-known convolution formulae on Stirling numbers as special ca

H. W. Braden, Linden Disney-Hogg

The theta characteristics on a Riemann surface are permuted by the induced action of the automorphism group, with the orbit structure being important for the geometry of the curve and associated manifolds. We describe two new methods for advancing the understanding of these orbits, generalising existing results of Kallel & Sjerve, allowing us to establish th

Dengyu Wu, Yi Qi, Kaiwen Cai, Gaojie Jin

Spiking Neural Network (SNN) is acknowledged as the next generation of Artificial Neural Network (ANN) and hold great promise in effectively processing spatial-temporal information. However, the choice of timestep becomes crucial as it significantly impacts the accuracy of the neural network training. Specifically, a smaller timestep indicates better perform

Peter Baile Chen, Yi Zhang, Dan Roth

Retrieving relevant tables containing the necessary information to accurately answer a given question over tables is critical to open-domain question-answering (QA) systems. Previous methods assume the answer to such a question can be found either in a single table or multiple tables identified through question decomposition or rewriting. However, neither of

Josefine B. Graebener, Apurva S. Badithela, Denizalp Goktas, Wyatt Ubellacker

Designing tests to evaluate if a given autonomous system satisfies complex specifications is challenging due to the complexity of these systems. This work proposes a flow-based approach for reactive test synthesis from temporal logic specifications, enabling the synthesis of test environments consisting of static and reactive obstacles and dynamic test agent

David Kofroň

We revise the work of Scholtz, Flandera and G\"urlebeck [Kerr-Newman black hole in the formalism of isolated horizons, Phys. Rev. D 96, 064024 (2017)]. We cast the Kerr metric explicitly in the form suitable for the framework of isolated horizons. We proceed in a geometrical fashion and are capable to provide the results in a compact closed manner, without a

Divyang Doshi, Jung-Eun Kim

In this research, we propose an innovative method to boost Knowledge Distillation efficiency without the need for resource-heavy teacher models. Knowledge Distillation trains a smaller ``student'' model with guidance from a larger ``teacher'' model, which is computationally costly. However, the main benefit comes from the soft labels provided by the teacher,

Thibault Vieu, Lucia Härer, Brian Reville

We consider scenarios for non-thermal particle acceleration and re-acceleration in the central cores of compact massive star clusters, aided by insights from high resolution hydrodynamic simulations. We show that i) particles are unlikely to interact with many shocks during their lifetimes in the core; ii) colliding flows do not produce hard spectra; iii) tu

Shuai Chen, Tommaso Cavallari, Victor Adrian Prisacariu, Eric Brachmann

Pose regression networks predict the camera pose of a query image relative to a known environment. Within this family of methods, absolute pose regression (APR) has recently shown promising accuracy in the range of a few centimeters in position error. APR networks encode the scene geometry implicitly in their weights. To achieve high accuracy, they require v

David Frost, Keisha Cook, Hugo Sanabria

F\"orster resonance energy transfer (FRET) is a quantum mechanical phenomenon involving the non-radiative transfer of energy between coupled electric dipoles. Due to the strong dependence of FRET on the distance between the dipoles, it is frequently used as a ``molecular ruler" in biology, chemistry, and physics. This is done by placing dipolar molecules cal

Victoire Michal, Alexandra M. Schmidt

Spatio-temporal disease mapping models are commonly used to estimate the relative risk of a disease over time and across areas. For each area and time point, the disease count is modelled with a Poisson distribution whose mean is the product of an offset and the disease relative risk. This relative risk is commonly decomposed in the log scale as the sum of f

Biaogang Wu, Ralf Rapp

We provide an update on our semi-classical transport approach for quarkonium production in high-energy heavy-ion collisions, focusing on $J/\psi$ and $\psi(2S)$ mesons in 5.02 TeV Pb-Pb collisions at the Large Hadron Collider (LHC) at both forward and mid-rapidity. In particular, we employ the most recent charm-production cross sections reported in pp collis

Lilia Lazli

Alzheimers disease (AD) is a severe neurological brain disorder. It is not curable, but earlier detection can help improve symptoms in a great deal. The machine learning based approaches are popular and well motivated models for medical image processing tasks such as computer-aided diagnosis. These techniques can improve the process for accurate diagnosis of

Tomasz Radozycki

The present paper discusses certain special Gaussian beams that, thanks to some polynomial prefactors, have uniquely designed holes in the irradiance. Such holes, or rather tubes, can constitute potential valleys for negatively polarizable particles, providing the possibility of guiding several objects of that kind, each along its own trajectory. The mechani

Masoud Taleb, Paul Bittorf, Mximilian Black, Mario Hentschel

Defect centers in hexagonal boron nitride have been extensively studied as room temperature single photon sources. The electronic structure of these defects exhibits strong coupling to phonons, as evidenced by the observation of phonon sidebands in both photoluminescence and cathodoluminescence spectra. However, the dynamics of the electron phonon coupling a

Elyasheev Leibtag

We show that for algebraic groups over local fields of characteristic zero, the following are equivalent: Every homomorphism has a closed image, every unitary representation decomposes into a direct sum of finite-dimensional and mixing representations, and that the matrix coefficients are dense within the algebra of weakly almost periodic functions over the

Savvas Papaioannou, Panayiotis Kolios, Christos G. Panayiotou, Marios M. Polycarpou

In the rapidly changing environments of disaster response, planning and decision-making for autonomous agents involve complex and interdependent choices. Although recent advancements have improved traditional artificial intelligence (AI) approaches, they often struggle in such settings, particularly when applied to agents operating outside their well-defined

Paprapee Buason, Sidhant Misra, Daniel K. Molzahn

Accurate modeling of power flow behavior is essential for a wide range of power system applications, yet the nonlinear and nonconvex structure of the underlying equations often limits their direct use in large-scale optimization problems. As a result, linear models are frequently adopted to improve computational tractability, though these simplifications can

E. E. Kolomeitsev, D. N. Voskresensky

Analyses for the NICER data indicate that there is no significant variation of the compact star radii within the mass range of 1.4 to 2.0 solar masses. Yamamoto et al. [Phys. Rev. C 108, 035811 (2023)] concluded recently that ``this feature cannot be reproduced by the hadronic matter due to the softening of the equation of state (EoS) by hyperon mixing, sugg

Elyes Boughattas, Danny Neftin

We give an affirmative answer to the Grunwald problem for new families of non-solvable finite groups G, away from the set of primes dividing |G|. Furthermore, we show that such G verify the condition (BM), that is, the Brauer-Manin obstruction to weak approximation is the only one for quotients of SL_n by G. These new families include extensions of groups sa

Noah Abou El Wafa, André Platzer

Game Logic with sabotage ($\mathsf{GL_s}$) is introduced as a simple and natural extension of Parikh's game logic with a single additional primitive, which allows players to lay traps for the opponent. $\mathsf{GL_s}$ can be used to model infinite sabotage games, in which players can change the rules during game play. In contrast to game logic, which is stri

Haoxing Chen, Yaohui Li, Zizheng Huang, Yan Hong

Pre-trained large-scale vision-language models (VLMs) have acquired profound understanding of general visual concepts. Recent advancements in efficient transfer learning (ETL) have shown remarkable success in fine-tuning VLMs within the scenario of limited data, introducing only a few parameters to harness task-specific insights from VLMs. Despite significan

Daniele Meli

Online unsupervised detection of anomalies is crucial to guarantee the correct operation of cyber-physical systems and the safety of humans interacting with them. State-of-the-art approaches based on deep learning via neural networks achieve outstanding performance at anomaly recognition, evaluating the discrepancy between a normal model of the system (with

Thomas Gossard, Julian Krismer, Andreas Ziegler, Jonas Tebbe

Spin plays a pivotal role in ball-based sports. Estimating spin becomes a key skill due to its impact on the ball's trajectory and bouncing behavior. Spin cannot be observed directly, making it inherently challenging to estimate. In table tennis, the combination of high velocity and spin renders traditional low frame rate cameras inadequate for quickly and a

Yaguang Yang, William Bentz, Lia Lewis

This paper derives a symbolic multi-body rigid nonlinear model for a space telescope using Stoneking's implementation of Kane's method. This symbolic nonlinear model is linearized using Matlab symbolic functions {\tt diff} and {\tt inv} because the analytic linearization is intractable for manual derivation. The linearized system model is then used to design

Rohan Padhye

The recent proliferation of generative artificial intelligence (AI) technologies such as pre-trained large language models (LLMs) has opened up new frontiers in computational law. An exciting area of development is the use of AI to automate the deductive rule-based reasoning inherent in statutory and contract law. This paper argues that such automated deduct

Giovanni Placini, Jonas Stelzig, Leopold Zoller

We show that the bigraded quasi-isomorphism type of the bigraded, bidifferential algebra of forms on a compact K\"ahler manifold generally contains more information than the de Rham cohomology algebra with its real Hodge structure. More precisely, on any closed Riemann surface of genus at least two, there is a nontrivial ABC-Massey product. Furthermore, star

Nilotpal Sinha, Peyman Rostami, Abd El Rahman Shabayek, Anis Kacem

Hardware-aware Neural Architecture Search approaches (HW-NAS) automate the design of deep learning architectures, tailored specifically to a given target hardware platform. Yet, these techniques demand substantial computational resources, primarily due to the expensive process of assessing the performance of identified architectures. To alleviate this proble

Raghav Donakanti, Prakhar Jain, Shubham Kulkarni, Karthik Vaidhyanathan

Modern software systems are subjected to various types of uncertainties arising from context, environment, etc. To this end, self-adaptation techniques have been sought out as potential solutions. Although recent advances in self-adaptation through the use of ML techniques have demonstrated promising results, the capabilities are limited by constraints impos

E. Mediavilla, J. Jiménez-Vicente, V. Motta

Precise lens modeling is a critical step in time delay studies of multiply imaged quasars, which are key for measuring some important cosmological parameters (specially $H_0$). However, lens models (in particular those semi-automatically generated) often show discrepancies with the observed flux-ratios between the different quasar images. These flux-ratio an

Merim Dzaferagic, Marco Ruffini, Nina Slamnik-Krijestorac, Joao F. Santos

Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will necessarily have to encompass both the radio and the fiber-optical domain. This paper introduces the Decentralized Multi-Party, Multi-Network AI (DMMAI) framework for integrating A

Lorenzo Iorio

To the first post--Newtonian order, the orbital angular momentum of the fast--revolving inner binary of the triple system PSR J0337+1715, made of a millisecond pulsar and a white dwarf, induces an annular gravitomagnetic field which displaces the line of apsides of the slower orbit of the other, distant white dwarf by $-1.2$ milliarcseconds per year. The cur

Kevin Horan, Katarina Domijan, Chris Brunsdon

Fitting areal models which use a spatial weights matrix to represent relationships between geographical units can be a cumbersome task, particularly when these units are not well-behaved. The two chief aims of sfislands are to simplify the process of creating an appropriate neighbourhood matrix, and to quickly visualise the predictions of subsequent models.

Kyveli Doveri, Pierre Ganty, Chana Weil-Kennedy

We present a uniform approach for solving language inclusion problems. Our approach relies on a least fixpoint characterization and a quasiorder to compare words of the "smaller" language, reducing the inclusion check to a finite number of membership queries in the "larger" language. We present our approach in detail on the case of inclusion of a context-fre

Satyavrat Wagle, Seyyedali Hosseinalipour, Naji Khosravan, Christopher G. Brinton

Federated learning (FL) is a popular solution for distributed machine learning (ML). While FL has traditionally been studied for supervised ML tasks, in many applications, it is impractical to assume availability of labeled data across devices. To this end, we develop Cooperative Federated unsupervised Contrastive Learning ({\tt CF-CL)} to facilitate FL acro

Qi Gao, Hyun-Myung Chun, Jordan M. Horowitz

We analyze the static response to kinetic perturbations of nonequilibrium steady states that can be modeled as diffusions. We demonstrate that kinetic response is purely a nonequilibirum effect, measuring the degree to which the Fluctuation-Dissipation Theorem is violated out of equilibrium. For driven diffusions in a flat landscape, we further demonstrate t

Hugo C. Botós, Carlos H. Grossi

The non-trivial complete totally geodesic submanifolds of the complex hyperbolic plane $\mathbb H_{\mathbb C}^2$ are the complex geodesics and the real planes. We present two new proofs for this fact. One is a short proof based on an algebraic formula for the Riemann curvature tensor due to S. Anan'in and C. Grossi and resembles the traditional proof using L

Sjors Heefer

This PhD dissertation covers a range of topics in Finsler geometry and Finsler gravity, most notably: (i) the characterization of Berwald spaces, (ii) pseudo-Riemann (non-)metrizability of Berwald spaces, (iii) $(\alpha,\beta)$-metrics, (iv) exact solutions to Pfeifer and Wohlfarth's vacuum field equation in Finsler gravity, and (v) Finsler gravitational wav

Fangwei Zhong, Kui Wu, Hai Ci, Churan Wang

Embodied visual tracking is to follow a target object in dynamic 3D environments using an agent's egocentric vision. This is a vital and challenging skill for embodied agents. However, existing methods suffer from inefficient training and poor generalization. In this paper, we propose a novel framework that combines visual foundation models(VFM) and offline

André H. Hoang, Oliver L. Jin, Simon Plätzer, Daniel Samitz

In the context of Monte Carlo (MC) generators with parton showers that have next-to-leading-logarithmic (NLL) precision, the cutoff $Q_0$ terminating the shower evolution should be viewed as an infrared factorization scale so that parameters or non-perturbative effects of the MC generator may have a field theoretic interpretation with a controllable scheme d

Thibault Charpentier, David Perconte, Sébastien Léger, Kazi Rafsanjani Amin

Continuous quantum phase transitions are widely assumed and frequently observed in various systems of quantum particles or spins. Their characteristic trait involves scaling laws governing a second-order, gradual suppression of the order parameter as the quantum critical point is approached. The localization of Cooper pairs in disordered superconductors and

Dimitris Nikolaidis

We propose a novel and efficient, custom frame synchronization architecture aimed at rapid deployment on any hardware platform. Frame synchronization is the process of discerning valid data frames from an incoming transmission and in this article it is accomplished by attaching distinctive binary overhead sequences on the frame. These sequences act as marker

Sanath K. Devalapurkar

In this note, we study the local relative geometric Langlands conjecture of Ben-Zvi--Sakellaridis--Venkatesh for the spherical subgroup $\mathrm{PGL}_2^\mathrm{diag}$ of the triple product $\mathrm{PGL}_2^{\times 3}$ (and also for the spherical subgroup $\mathrm{G}_2$ of $\mathrm{SO}_8/\mu_2$), whose corresponding Langlands dual $\mathrm{SL}_2^{\times 3}$-va

Ningyi Lyu, Pouya Khazaei, Eitan Geva, Victor S. Batista

We present a quantum algorithm based on the Tensor-Train Thermo-Field Dynamics (TT-TFD) method to simulate the open quantum system dynamics of intramolecular charge transfer modulated by an optical cavity on noisy intermediate-scale quantum (NISQ) computers. We apply our methodology to a model that describes the $\pi\pi^*$ to CT1 intermolecular charge transf

Dustin Holley, Jovin Dsa, Hossein Nourkhiz Mahjoub, Gibran Ali

Enhancing simulation environments to replicate real-world driver behavior is essential for developing Autonomous Vehicle technology. While some previous works have studied the yielding reaction of lag vehicles in response to a merging car at highway on-ramps, the possible lane-change reaction of the lag car has not been widely studied. In this work we aim to

Taha Shafa, Melkior Ornik

Determining the reachable set for a given nonlinear system is critically important for autonomous trajectory planning for reach-avoid applications and safety critical scenarios. Providing the reachable set is generally impossible when the dynamics are unknown, so we calculate underapproximations of such sets using local dynamics at a single point and bounds

Andrew Nugent, Susana N. Gomes, Marie-Therese Wolfram

In this paper we propose a novel control approach for opinion dynamics on evolving networks. The controls modify the strength of connections in the network, rather than influencing opinions directly, with the overall goal of steering the population towards a target opinion. This requires that the social network remains sufficiently connected, the population

Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li

In a hyper-relational knowledge graph (HKG), each fact is composed of a main triple associated with attribute-value qualifiers, which express additional factual knowledge. The hyper-relational knowledge graph completion (HKGC) task aims at inferring plausible missing links in a HKG. Most existing approaches to HKGC focus on enhancing the communication betwee

Razieh Nabi, Nima S. Hejazi, Mark J. van der Laan, David Benkeser

We develop a general framework for estimating function-valued parameters under equality or inequality constraints in infinite-dimensional statistical models. Such constrained learning problems are common across many areas of statistics and machine learning, where estimated parameters must satisfy structural requirements such as moment restrictions, policy be

Eran Bamani, Eden Nissinman, Lisa Koenigsberg, Inbar Meir

Object recognition, commonly performed by a camera, is a fundamental requirement for robots to complete complex tasks. Some tasks require recognizing objects far from the robot's camera. A challenging example is Ultra-Range Gesture Recognition (URGR) in human-robot interaction where the user exhibits directive gestures at a distance of up to 25~m from the ro

Isaac A. Spiegel, Nard Strijbosch, Robin de Rozario, Tom Oomen

Model inversion is a fundamental technique in feedforward control. Unstable inverse models present a challenge in that useful feedforward control trajectories cannot be generated by directly propagating them. Stable inversion is a process for generating useful trajectories from unstable inverses by handling their stable and unstable modes separately. Piecewi

Delgermaa Gankhuyag, Stephanie Groiß, Lena Schwamberger, Özge Talay

Delivery services have undergone technological advancements, with robots now directly delivering packages to recipients. While these robots are designed for efficient functionality, they have not been specifically designed for interactions with humans. Building on the premise that incorporating human-like characteristics into a robot has the potential to pos

Ricardo Chacón, Pedro J. Martínez

Characterizing the emergence of chaotic dynamics of complex networks is an essential task in nonlinear science with potential important applications in many fields such as neural control engineering, microgrid technologies, and ecological networks. Here, we solve a critical outstanding problem in this multidisciplinary research field: The emergence and persi

V. K. Dobrev

We construct representations of the quantum algebras ~$U_{q{\bf q}}(gl(n))$ and ~$U_{q{\bf q}}(sl(n))$~ which are in duality with the multiparameter quantum groups ~$GL_{q{\bf q}}(n)$, ~$SL_{q{\bf q}}(n)$,~ respectively. These objects depend on ~$n(n-1)/2+1$~ deformation parameters ~$q,q_{ij}$ ($1\leq i <j\leq n$) which is the maximal possible number in the

Tao Wu, Mengqi Cao, Ziteng Gao, Gangshan Wu

Traditional video action detectors typically adopt the two-stage pipeline, where a person detector is first employed to generate actor boxes and then 3D RoIAlign is used to extract actor-specific features for classification. This detection paradigm requires multi-stage training and inference, and the feature sampling is constrained inside the box, failing to

Francis McCann Ramirez, Luka Chkhetiani, Andrew Ehrenberg, Robert McHardy

This paper describes AssemblyAI's industrial-scale automatic speech recognition (ASR) system, designed to meet the requirements of large-scale, multilingual ASR serving various application needs. Our system leverages a diverse training dataset comprising unsupervised (12.5M hours), supervised (188k hours), and pseudo-labeled (1.6M hours) data across four lan

Salah Eddine Oustani, Mohamed Rossafi

One of the most important problems in the studying of frames and its extensions is the invariance of these systems under perturbation. The current paper is concerned with the invariance of Modular biframes for operators under some class of closed range operators.

Ugo Nzongani, Nathanaël Eon, Iván Márquez-Martín, Armando Pérez

Discrete-time Quantum Walks (QWs) are transportation models of single quantum particles over a lattice. Their evolution is driven through causal and local unitary operators. QWs are a powerful tool for quantum simulation of fundamental physics as some of them have a continuum limit converging to well-known physics partial differential equations, such as the

Kangkan Goswami, Suraj Prasad, Neelkamal Mallick, Raghunath Sahoo

n proton-proton and heavy-ion collisions, the study of charm hadrons plays a pivotal role in understanding the QCD medium and provides an undisputed testing ground for the theory of strong interaction, as they are mostly produced in the early stages of collisions via hard partonic interactions. The lightest open-charm, $D^{0}$ meson ($c\Bar{u}$), can origina

Savvas Papaioannou, Christian Vitale, Panayiotis Kolios, Christos G. Panayiotou

Fault-tolerant coverage control involves determining a trajectory that enables an autonomous agent to cover specific points of interest, even in the presence of actuation and/or sensing faults. In this work, the agent encounters control inputs that are erroneous; specifically, its nominal controls inputs are perturbed by stochastic disturbances, potentially

Yuhan Li, Hongyu Liu, Catharine W. K. Lo

This paper focuses on inverse problems arising in studying multi-population aggregations. The goal is to reconstruct the diffusion coefficient, advection coefficient, and interaction kernels of the aggregation system, which characterize the dynamics of different populations. In the theoretical analysis of the physical setup, it is crucial to ensure non-negat

Xiuwei Shang, Shaoyin Cheng, Guoqiang Chen, Yanming Zhang

Binary code analysis plays a pivotal role in various software security applications, such as software maintenance, malware detection, software vulnerability discovery, patch analysis, etc. However, unlike source code, understanding binary code is challenging for reverse engineers due to the absence of semantic information. Therefore, automated tools are need

Xiaoyi Tian, Qingxiang Xu, Chunhong Fu

A term called the quasi-projection pair $(P,Q)$ was introduced recently by the authors, where $P$ is a projection and $Q$ is an idempotent on a Hilbert $C^*$-module $H$ satisfying $Q^*=(2P-I)Q(2P-I)$, in which $Q^*$ is the adjoint operator of the idempotent $Q$ and $I$ is the identity operator on $H$. Some fundamental issues on quasi-projection pairs, such a

Mikkel Abrahamsen, Jack Stade

We show that packing axis-aligned unit squares into a simple polygon $P$ is NP-hard, even when $P$ is an orthogonal and orthogonally convex polygon with half-integer coordinates. It has been known since the early 80s that packing unit squares into a polygon with holes is NP-hard~[Fowler, Paterson, Tanimoto, Inf. Process. Lett., 1981], but the version without

Dario Mazzoleni, Emanuela Radici, Filippo Riva

We propose and analyse a new microscopic second order Follow-the-Leader type scheme to describe traffic flows. The main novelty of this model consists in multiplying the second order term by a nonlinear function of the global density, with the intent of considering the attentiveness of the drivers in dependence on the amount of congestion. Such term makes th

Hongchi Xia, Zhi-Hao Lin, Wei-Chiu Ma, Shenlong Wang

Creating high-quality and interactive virtual environments, such as games and simulators, often involves complex and costly manual modeling processes. In this paper, we present Video2Game, a novel approach that automatically converts videos of real-world scenes into realistic and interactive game environments. At the heart of our system are three core compon

Gagan Aggarwal, Giannis Fikioris, Mingfei Zhao

Advertisers increasingly use automated bidding to optimize their ad campaigns on online advertising platforms. Autobidding optimizes an advertiser's objective subject to various constraints, e.g. average ROI and budget constraints. In this paper, we study the problem of designing online autobidding algorithms to optimize value subject to ROI and budget const

Jiyuan Wang, Chunyu Lin, Lang Nie, Kang Liao

Recently, diffusion-based depth estimation methods have drawn widespread attention due to their elegant denoising patterns and promising performance. However, they are typically unreliable under adverse conditions prevalent in real-world scenarios, such as rainy, snowy, etc. In this paper, we propose a novel robust depth estimation method called D4RD, featur

Yuchen Shi, Deqing Yang, Jingping Liu, Yanghua Xiao

Previous works of negation understanding mainly focus on negation cue detection and scope resolution, without identifying negation subject which is also significant to the downstream tasks. In this paper, we propose a new negation triplet extraction (NTE) task which aims to extract negation subject along with negation cue and scope. To achieve NTE, we devise

Hyeonggeun Yun

In computer vision, explainable AI (xAI) methods seek to mitigate the 'black-box' problem by making the decision-making process of deep learning models more interpretable and transparent. Traditional xAI methods concentrate on visualizing input features that influence model predictions, providing insights primarily suited for experts. In this work, we presen

Alain Le Yaouanc, François Richard

A global interpretation of several significant indications of scalar resonances observed at LHC is achieved using the Georgi Machacek model. Among many other consequences, one predicts large cross sections for the processes ggFH(320)->h(125)h(125) and A(151)A(151) and ggF->A(420)->H(320)Z, where H(320) has been observed in A(420)->H(320)Z->bbbbl+l- and where

Tsung-Han Chou, Brian Wang, Wei-Chen Chiu, Jun-Cheng Chen

Class agnostic counting (CAC) is a vision task that can be used to count the total occurrence number of any given reference objects in the query image. The task is usually formulated as a density map estimation problem through similarity computation among a few image samples of the reference object and the query image. In this paper, we point out a severe is

João A. S. Amarante, Sergey E. Koposov, Chervin F. P. Laporte

We use Legacy Survey photometric data to probe the stellar halo in multiple directions of the sky using a probabilistic methodology to identify Blue Horizontal Branch (BHB) stars. The measured average radial density profile follows a double power law in the range $ 5 < r_{gc}/{\rm kpc} < 120$, with a density break at $r_{gc}\approx20$ kpc. This description,

Yang Gao, Dana Alon, Donald Metzler

A key requirement in developing Generative Language Models (GLMs) is to have their values aligned with human values. Preference-based alignment is a widely used paradigm for this purpose, in which preferences over generation pairs are first elicited from human annotators or AI systems, and then fed into some alignment techniques, e.g., Direct Preference Opti

Dalila Failli, Maria Francesca Marino, Francesca Martella

In the context of network data, bipartite networks are of particular interest, as they provide a useful description of systems representing relationships between sending and receiving nodes. In this framework, we extend the Mixture of Latent Trait Analyzers (MLTA) to perform a joint clustering of sending and receiving nodes, as in the biclustering framework.

Le Chen, Jie Yu, XingWu Chen

This article proposes a multi habitat bio-mimetic robot, named as GuLu XuanYuan.It combines all common types of mobile robots, namely humanoid MIP, unmanned ground vehicle, and unmanned aerial vehicle. These 3 modals imitate human, bird, and reptile, separately. As a transformer, GuLu XuanYuan can transform from one modal to another. Transforming function in

Yuri Kinoshita, Taro Toyoizumi

While neural networks can enjoy an outstanding flexibility and exhibit unprecedented performance, the mechanism behind their behavior is still not well-understood. To tackle this fundamental challenge, researchers have tried to restrict and manipulate some of their properties in order to gain new insights and better control on them. Especially, throughout th

Thomas Alazard, Igor Kukavica, Amjad Tuffaha

We consider the Cauchy problem for an inviscid irrotational fluid on a domain with a free boundary governed by a fourth order linear elasticity equation. We first derive the Craig-Sulem-Zakharov formulation of the problem and then establish the existence of a global weak solution in two space dimensions, in the general case without a damping term, for any in

Felix Taubner, Prashant Raina, Mathieu Tuli, Eu Wern Teh

When working with 3D facial data, improving fidelity and avoiding the uncanny valley effect is critically dependent on accurate 3D facial performance capture. Because such methods are expensive and due to the widespread availability of 2D videos, recent methods have focused on how to perform monocular 3D face tracking. However, these methods often fall short

Luca Parrini, Taha Soliman, Benjamin Hettwer, Jan Micha Borrmann

In-Memory Computing (IMC) introduces a new paradigm of computation that offers high efficiency in terms of latency and power consumption for AI accelerators. However, the non-idealities and defects of emerging technologies used in advanced IMC can severely degrade the accuracy of inferred Neural Networks (NN) and lead to malfunctions in safety-critical appli

Ngoc-Giau Pham, Thanh-Hai Tong Le, Van-Hieu Duong, Hong-Ngoc Tran

In this article, we address the challenges of image super-resolution and noise reduction, which are crucial for enhancing the quality of images derived from low-resolution or noisy data. We compared and assessed several approaches for upgrading low-resolution images to higher resolutions and for eliminating unwanted noise, all while maintaining the essential

Kai Yi, Nidham Gazagnadou, Peter Richtárik, Lingjuan Lyu

The interest in federated learning has surged in recent research due to its unique ability to train a global model using privacy-secured information held locally on each client. This paper pays particular attention to the issue of client-side model heterogeneity, a pervasive challenge in the practical implementation of FL that escalates its complexity. Assum

Wenchuang Guan, Shen Wang, Wenjuan Rui, Jipeng Cheng

In this paper, we mainly investigate Lax structure and tau function for the large BKP hierarchy, which is also known as Toda hierarchy of B type, or Hirota--Ohta--coupled KP hierarchy, or Pfaff lattice. Firstly, the large BKP hierarchy can be derived from fermionic BKP hierarchy by using a special bosonization, which is presented in the form of bilinear equa

Man Wang, Zheng Shi, Yunfei Li, Xianda Wu

This letter proposes a novel hybrid automatic repeat request with chase combining assisted sparse code multiple access (HARQ-CC-SCMA) scheme. Depending on whether the same superimposed packet are retransmitted, synchronous and asynchronous modes are considered for retransmissions. Moreover, factor graph aggregation (FGA) and Log-likelihood ratio combination

Garry Goldstein

In this work we make some progress on studying four center integrals for the Coulomb energy for both Hartree Fock (HF) and Density Functional Theory (DFT) calculations for small molecules. We consider basis wave functions of the form of an arbitrary radial wave function multiplied by a spherical harmonic and study four center Coulomb integrals for them. We r

Arkadiy Dushatskiy, Esther Julien, Leen Stougie, Leo van Iersel

Tree Containment is a fundamental problem in phylogenetics useful for verifying a proposed phylogenetic network, representing the evolutionary history of certain species. Tree Containment asks whether the given phylogenetic tree (for instance, constructed from a DNA fragment showing tree-like evolution) is contained in the given phylogenetic network. In the

Lucas Surmann

In this article we consider tame $ SL_3 $-friezes that arise by specializing a cluster of Pl\"ucker variables in the coordinate ring of the Grassmannian $ \mathscr{G}(3,n) $ to $ 1 $. We show how to calculate arbitrary entries of such friezes from the cluster in question. Let $ \mathscr{F} $ be such a cluster. We study the set $ \mathscr{F}_x $ of cluster va

Christian Varner, Vivak Patel

Optimization problems arising in data science have given rise to a number of new derivative-based optimization methods. Such methods often use standard smoothness assumptions -- namely, global Lipschitz continuity of the gradient function -- to establish a convergence theory. Unfortunately, in this work, we show that common optimization problems from data sc

Haimin Zhang, Min Xu

Message passing has become the dominant framework in graph representation learning. The essential idea of the message-passing framework is to update node embeddings based on the information aggregated from local neighbours. However, most existing aggregation methods have not encoded neighbour-level message interactions into the aggregated message, resulting

Rui Kong, Subham Sahoo, Yongjie Liu, Frede Blaabjerg

Harmonic instability occurs frequently in the power electronic converter system. This paper leverages multi-resolution dynamic mode decomposition (MR-DMD) as a data-driven diagnostic tool for the system stability of power electronic converters, not requiring complex modeling and detailed control information. By combining dynamic mode decomposition (DMD) with

Floriane Magera, Thomas Hoyoux, Olivier Barnich, Marc Van Droogenbroeck

Camera calibration is a crucial component in the realm of sports analytics, as it serves as the foundation to extract 3D information out of the broadcast images. Despite the significance of camera calibration research in sports analytics, progress is impeded by outdated benchmarking criteria. Indeed, the annotation data and evaluation metrics provided by mos

A. D. Boccardo, Z. Zou, M. Simonelli, M. Tong

Additive manufacturing of Ti-6Al-4V alloy via laser powder-bed fusion leads to non-equilibrium $\alpha'$ martensitic microstructures, with high strength but poor ductility and toughness. These properties may be modified by heat treatments, whereby the $\alpha'$ phase decomposes into equilibrium $\alpha+\beta$ structures, while possibly conserving microstruct

Shiyu Liang, Ziyuan Wang, Zhenghua Huang, Hengyuan Wei

Loops are fundamental structures in the magnetized atmosphere of the sun. Their physical properties are crucial for understanding the nature of the solar atmosphere. Transition region loops are relatively dynamic and their physical properties have not yet been fully understood. With spectral data of the line pair of O IV 1399.8 \AA & 1401.2 \AA ($T_{max}=1.4

Wen Ai, Yunlong Yang, Deping Ye

The central focus of this paper is the $L_p$ dual Minkowski problem for $C$-compatible sets, where $C$ is a pointed closed convex cone in $\mathbb{R}^n$ with nonempty interior. Such a problem deals with the characterization of the $(p, q)$-th dual curvature measure of a $C$-compatible set. It produces new Monge-Amp\`{e}re equations for unbounded convex hyper

Tattwamasi Amrutam, Eli Glasner, Yair Glasner

Given a dynamical system $(X, \Gamma)$, the corresponding crossed product $C^*$-algebra $C(X)\rtimes_{r}\Gamma$ is called reflecting, when every intermediate $C^*$-algebra $C^*_r(\Gamma)<\mathcal{A} < C(X)\rtimes_{r}\Gamma$ is of the form $\mathcal{A}=C(Y)\rtimes_{r}\Gamma$, corresponding to a dynamical factor $X \rightarrow Y$. It is called almost reflectin

Saroj Gopali, Akbar S. Namin, Faranak Abri, Keith S. Jones

Cyber attacks continue to pose significant threats to individuals and organizations, stealing sensitive data such as personally identifiable information, financial information, and login credentials. Hence, detecting malicious websites before they cause any harm is critical to preventing fraud and monetary loss. To address the increasing number of phishing a

Rui Kong, Subham Sahoo, Yubo Song, Frede Blaabjerg

This paper proposes a gray-box stability analysis mechanism based on data-driven dynamic mode decomposition (DMD) for commercial grid-tied power electronics converters with limited information on its control parameters and topology. By fusing the underlying physical constraints of the state equations into data snapshots, the system dynamic state matrix and i

Minhao Hong, Qian Yu

In this article, we consider fractional derivatives of local time for $d-$dimensional centered Gaussian processes satisfying certain strong local nondeterminism property. We first give a condition for existence of fractional derivatives of the local time defined by Marchaud derivatives in $L^p(p\ge1)$ and show that these derivatives are H\"older continuous w

Thomas Wolfs, Walter Van Assche

We construct new rational approximants of Euler's constant that improve those of Aptekarev et al. (2007) and Rivoal (2009). The approximants are given in terms of certain (mixed type) multiple orthogonal polynomials associated with the exponential integral. The dual family of multiple orthogonal polynomials leads to new rational approximants of the Gompertz