March 2024 arXiv papers — page 92

Andre Büttner, Andreas Thue Pedersen, Stephan Wiefling, Nils Gruschka

Risk-based authentication (RBA) is used in online services to protect user accounts from unauthorized takeover. RBA commonly uses contextual features that indicate a suspicious login attempt when the characteristic attributes of the login context deviate from known and thus expected values. Previous research on RBA and anomaly detection in authentication has

Supranta S. Boruah, Tim Eifler, Vivian Miranda, Elyas Farah

Validating modeling choices through simulated analyses and quantifying the impact of different systematic effects will form a major computational bottleneck in the preparation for 3$\times$2 analysis with Stage-IV surveys such as Vera Rubin Observatory's Legacy Survey of Space and Time (LSST). We can significantly reduce the computational requirements by usi

Haochen Jiang, Yueming Xu, Yihan Zeng, Hang Xu

3D reconstruction has been widely used in autonomous navigation fields of mobile robotics. However, the former research can only provide the basic geometry structure without the capability of open-world scene understanding, limiting advanced tasks like human interaction and visual navigation. Moreover, traditional 3D scene understanding approaches rely on ex

Sayan Biswas, Davide Frey, Romaric Gaudel, Anne-Marie Kermarrec

Decentralized learning (DL) is an emerging paradigm of collaborative machine learning that enables nodes in a network to train models collectively without sharing their raw data or relying on a central server. This paper introduces Zip-DL, a privacy-aware DL algorithm that leverages correlated noise to achieve robust privacy against local adversaries while e

Guodong Meng, Yimeng Li, Roni Aleksi Koitermaa, Veronika Zadin

Nano-protrusion (NP) on metal surface and its inevitable contamination layer under high electric field is often considered as the primary precursor that leads to vacuum breakdown, which plays an extremely detrimental effect for high energy physics equipment and many other devices. Yet, the NP growth has never been experimentally observed. Here, we conduct fi

Seungpil Lee, Woochang Sim, Donghyeon Shin, Wongyu Seo

The existing methods for evaluating the inference abilities of Large Language Models (LLMs) have been predominantly results-centric, making it challenging to assess the inference process comprehensively. We introduce a novel approach using the Abstraction and Reasoning Corpus (ARC) benchmark to evaluate the inference and contextual understanding abilities of

Jintao Guo, Lei Qi, Yinghuan Shi, Yang Gao

Domain generalization (DG) aims to enhance the model robustness against domain shifts without accessing target domains. A prevalent category of methods for DG is data augmentation, which focuses on generating virtual samples to simulate domain shifts. However, existing augmentation techniques in DG are mainly tailored for convolutional neural networks (CNNs)

Onur Keleş, A. Murat Tekalp

Convolutional neural networks (CNN) are built upon the classical McCulloch-Pitts neuron model, which is essentially a linear model, where the nonlinearity is provided by a separate activation function. Several researchers have proposed enhanced neuron models, including quadratic neurons, generalized operational neurons, generative neurons, and super neurons,

Antonio Pepe, Richard Schussnig, Jianning Li, Christina Gsaxner

Shape reconstruction from imaging volumes is a recurring need in medical image analysis. Common workflows start with a segmentation step, followed by careful post-processing and,finally, ad hoc meshing algorithms. As this sequence can be timeconsuming, neural networks are trained to reconstruct shapes through template deformation. These networks deliver stat

Wenhua Wu, Qi Wang, Guangming Wang, Junping Wang

Road surface reconstruction plays a vital role in autonomous driving systems, enabling road lane perception and high-precision mapping. Recently, neural implicit encoding has achieved remarkable results in scene representation, particularly in the realistic rendering of scene textures. However, it faces challenges in directly representing geometric informati

Xinhui Shan, Yuhong Huang, Zhenshan Bing, Zitao Zhang

This research focuses on developing reinforcement learning approaches for the locomotion generation of small-size quadruped robots. The rat robot NeRmo is employed as the experimental platform. Due to the constrained volume, small-size quadruped robots typically possess fewer and weaker sensors, resulting in difficulty in accurately perceiving and responding

Zehui Zhou

Stochastic gradient descent (SGD) is a promising method for solving large-scale inverse problems, due to its excellent scalability with respect to data size. In this work, we analyze a new data-driven regularized stochastic gradient descent for the efficient numerical solution of a class of nonlinear ill-posed inverse problems in infinite dimensional Hilbert

Preetha Datta, Fedor Vitiugin, Anastasiia Chizhikova, Nitin Sawhney

Extracting hyper-relations is crucial for constructing comprehensive knowledge graphs, but there are limited supervised methods available for this task. To address this gap, we introduce a zero-shot prompt-based method using OpenAI's GPT-3.5 model for extracting hyper-relational knowledge from text. Comparing our model with a baseline, we achieved promising

Nickolas H. Pilgram, Benjamin Baldwin, David S. La Mantia, Stephen P. Eckel

We measure the complete set of transition frequencies necessary to laser cool and trap MgF molecules. Specifically, we report the frequency of multiple low $J$ transitions of the $X^2\Sigma^+(v^{\prime\prime}=0,1) \rightarrow A^2\Pi_{1/2}(v^\prime=0)$, $X^2\Sigma^+(v^{\prime\prime}=1,2) \rightarrow A^2\Pi_{1/2}(v^\prime=1)$, and $X^2\Sigma^+(v^{\prime\prime}

Nicolas Baumann, Edoardo Ghignone, Jonas Kühne, Niklas Bastuck

Autonomous racing in robotics combines high-speed dynamics with the necessity for reliability and real-time decision-making. While such racing pushes software and hardware to their limits, many existing full-system solutions necessitate complex, custom hardware and software, and usually focus on Time-Trials rather than full unrestricted Head-to-Head racing,

R. M. Potvliege

The Python functions distributed with this article can be used for calculating the parameters of multichannel quantum defect theory models describing excited bound states of complex atoms. These parameters are obtained by fitting a model to experimental data provided by the user. The two main formulations of the theory are supported, namely the one in which

Yi Wu, Ziqiang Li, Heliang Zheng, Chaoyue Wang

Drawing on recent advancements in diffusion models for text-to-image generation, identity-preserved personalization has made significant progress in accurately capturing specific identities with just a single reference image. However, existing methods primarily integrate reference images within the text embedding space, leading to a complex entanglement of i

Yongqi Wang, Ruofan Hu, Rongjie Huang, Zhiqing Hong

Recent singing-voice-synthesis (SVS) methods have achieved remarkable audio quality and naturalness, yet they lack the capability to control the style attributes of the synthesized singing explicitly. We propose Prompt-Singer, the first SVS method that enables attribute controlling on singer gender, vocal range and volume with natural language. We adopt a mo

Gerard Memmi

This article focuses on comparing the notions of home spaces and invariants, in Transition Systems and more particularly, in Petri Nets as well as a variety of derived Petri Nets. After recalling basic notions of Petri Nets and semiflows, we then discuss important characteristics of finite generating sets for F, the set of all semiflows with integer coordina

Jonat John Mathew, Rakin Ahsan, Sae Furukawa, Jagdish Gautham Krishna Kumar

Deepfake audio poses a rising threat in communication platforms, necessitating real-time detection for audio stream integrity. Unlike traditional non-real-time approaches, this study assesses the viability of employing static deepfake audio detection models in real-time communication platforms. An executable software is developed for cross-platform compatibi

Han Wu, Kun Lin, Qinghua Zhang, Qian Yu

Hafnia-based ferroelectrics have become a valuable class of electronic functional materials at the nanoscale, showing great potential for next-generation memory and logic devices. However, more robust ferroelectric properties and better understanding of the polarization mechanisms are currently needed both in technology and science. Herein, we report the pro

Wenhua Wu, Guangming Wang, Ting Deng, Sebastian Aegidius

Recent research on Simultaneous Localization and Mapping (SLAM) based on implicit representation has shown promising results in indoor environments. However, there are still some challenges: the limited scene representation capability of implicit encodings, the uncertainty in the rendering process from implicit representations, and the disruption of consiste

Yanjun Li, Haibin Kan, Fangfang Liu, Jie Peng

The study on minimal linear codes has received great attention due to their significant applications in secret sharing schemes and secure two-party computation. Until now, numerous minimal linear codes have been discovered. However, to the best of our knowledge, no infinite family of minimal ternary linear codes was found from vectorial functions. In this pa

Teo Granger, Thomas M. Michelitsch, Michael Bestehorn, Alejandro P. Riascos

We study epidemic spreading in complex networks by a multiple random walker approach. Each walker performs an independent simple Markovian random walk on a complex undirected (ergodic) random graph where we focus on Barab\'asi-Albert (BA), Erd\"os-R\'enyi (ER) and Watts-Strogatz (WS) types. Both, walkers and nodes can be either susceptible (S) or infected an

Yingli Wang, Chunhao Cai, Ping He, QingHua Wang

In this paper, we investigate the scaling limit of heavy-tailed nearly unstable cumulative INAR($\infty$) processes. These processes exhibit a power-law tail of the form $n^{-(1+\alpha)}$ for $\alpha \in (\frac{1}{2}, 1)$, and the $\ell^1$ norm of the kernel vector converges to 1. We demonstrate that the discrete-time scaling limit retains a long-memory prop

Pierre Guetschel, Thomas Moreau, Michael Tangermann

Motivated by the challenge of seamless cross-dataset transfer in EEG signal processing, this article presents an exploratory study on the use of Joint Embedding Predictive Architectures (JEPAs). In recent years, self-supervised learning has emerged as a promising approach for transfer learning in various domains. However, its application to EEG signals remai

Mitja Nikolaus, Milad Mozafari, Nicholas Asher, Leila Reddy

Previous studies have shown that it is possible to map brain activation data of subjects viewing images onto the feature representation space of not only vision models (modality-specific decoding) but also language models (cross-modal decoding). In this work, we introduce and use a new large-scale fMRI dataset (~8,500 trials per subject) of people watching b

S Ganesh

A novel theory was proposed earlier to model systems with thermal gradients, based on the postulate that the spatial and temporal variation in temperature can be recast as a variation in the metric. Combining the variation in the metric due to the thermal variations and gravity, leads to the concept of thermal gravity in a 5-D space-time-temperature setting.

Xiao-Ping Rao, Hyat Huang, Jinbo Yang

We obtained new hairy black hole solutions in Einstein-scalar theory, including asymptotic flat, de Sitter and anti-de Sitter black holes. The theory is inspired by Ref. [1], where traversable wormhole solutions from an Einstein-phantom scalar theory are constructed. In this work, we found new black hole solutions in an Einstein-normal scalar theory. Compari

Himanshu Raj, Shubham Kumar, J Kalaivani

The internet has become a vital resource for job seekers in today's technologically advanced world, particularly for those with impairments. They mainly rely on internet resources to find jobs that fit their particular requirements and skill set. Though some disabled candidates receive prompt responses and job offers, others find it difficult to traverse the

Stanislav Budzinskiy

The theory of low-rank tensor-train approximation is well understood when the approximation error is measured in the Frobenius norm. The entrywise maximum norm is equally important but is significantly weaker for large tensors, making the estimates obtained via the Frobenius norm and norm equivalence pessimistic or even meaningless. In this article, we deriv

Yong-Siang Shih, Manqian Liao, Ruidong Liu, Mirza Basim Baig

Online exams have become popular in recent years due to their accessibility. However, some concerns have been raised about the security of the online exams, particularly in the context of professional cheating services aiding malicious test takers in passing exams, forming so-called "cheating rings". In this paper, we introduce a human-in-the-loop AI cheatin

Vladimir Vovk

The usual way of testing probability forecasts in game-theoretic probability is via construction of test martingales. The standard assumption is that all forecasts are output by the same forecaster. In this paper I will discuss possible extensions of this picture to testing probability forecasts output by several forecasters. This corresponds to multiple hyp

Wenmin Chen, Xiaowei Xu

With the widespread application of deep learning across various domains, concerns about its security have grown significantly. Among these, backdoor attacks pose a serious security threat to deep neural networks (DNNs). In recent years, backdoor attacks on neural networks have become increasingly sophisticated, aiming to compromise the security and trustwort

Yubo Sun, Gennian Ge

An edit refers to a single insertion, deletion, or substitution. This paper aims to construct binary codes that can correct two edits. To do this, a necessary and sufficient condition for a code to be two-edit correctable is provided, showing that a code is a two-edit correcting code if and only if it can correct two deletions, up to two substitutions, and o

Abdul Rehman, Robbert W. E. van de Kruijs, Wesley T. E. van den Beld, Jacobus M. Sturm

Amidst the growing importance of hydrogen in a sustainable future, it is crucial to develop coatings that can protect hydrogen-sensitive system components in reactive hydrogen environments. However, the prediction of the chemical stability of materials in hydrogen is not fully understood. In this study, we show that the work function is a key parameter deter

Yixuan Huang, Jie Yang, Chao-Kai Wen, Shi Jin

Retrieving range information in three-dimensional (3D) radio imaging is particularly challenging due to the limited communication bandwidth and pilot resources. To address this issue, we consider a reconfigurable intelligent surface (RIS)-aided uplink communication scenario, generating multiple measurements through RIS phase adjustment. This study successful

Han Wang, Kostas Margellos, Antonis Papachristodoulou, Claudio De Persis

We study the problem of co-designing control barrier functions (CBF) and linear state feedback controllers for continuous-time linear systems. We achieve this by means of a single semi-definite optimization program. Our formulation can handle mixed-relative degree problems without requiring an explicit safe controller. Different L-norm based input limitation

Seunghyeong Yoo, Jaehyun Kim, Seokjun Park, Mintaek Oh

We investigate full-duplex (FD) multi-user multiple input single-output systems with coarse quantization, aiming to characterize the impact of employing low-resolution analog-to-digital converters (ADCs) on self-interference (SI) and to develop a quantization- and SI-aware beamforming method that alleviates quantization-induced performance degradation in the

Jonas Schramm, Niclas Vödisch, Kürsat Petek, B Ravi Kiran

Semantic scene segmentation from a bird's-eye-view (BEV) perspective plays a crucial role in facilitating planning and decision-making for mobile robots. Although recent vision-only methods have demonstrated notable advancements in performance, they often struggle under adverse illumination conditions such as rain or nighttime. While active sensors offer a s

Zoubida Ameur, Claire-Hélène Demarty, Daniel Menard, Olivier Le Meur

The consumption of a video requires a considerable amount of energy during the various stages of its life-cycle. With a billion hours of video consumed daily, this contributes significantly to the greenhouse gas emission. Therefore, reducing the end-to-end carbon footprint of the video chain, while preserving the quality of experience at the user side, is of

Gabriel Karl Gegenhuber, Philipp Frenzel, Edgar Weippl

In current cellular network generations (4G, 5G) the IMS (IP Multimedia Subsystem) plays an integral role in terminating voice calls and short messages. Many operators use VoWiFi (Voice over Wi-Fi, also Wi-Fi calling) as an alternative network access technology to complement their cellular coverage in areas where no radio signal is available (e.g., rural ter

Junjie Ma, Muhui Jiang, Jinan Jiang, Xiapu Luo

Decentralized Autonomous Organization (DAO) becomes a popular governance solution for decentralized applications (dApps) to achieve decentralized governance. In the DAO, no single entity can arbitrarily control the dApps without approval from the majority of members. However, despite its advantages, DAO has also been targeted by several attacks, leading to t

Jun Yu, Wangyuan Zhu, Jichao Zhu

In this paper, we present the solution to the Emotional Mimicry Intensity (EMI) Estimation challenge, which is part of 6th Affective Behavior Analysis in-the-wild (ABAW) Competition.The EMI Estimation challenge task aims to evaluate the emotional intensity of seed videos by assessing them from a set of predefined emotion categories (i.e., "Admiration", "Amus

Julian Rasch, Florian Perzl, Yannick Weiss, Florian Müller

With the proliferation of VR and a metaverse on the horizon, many multi-user activities are migrating to the VR world, calling for effective collaboration support. As one key feature, traditional collaborative systems provide users with undo mechanics to reverse errors and other unwanted changes. While undo has been extensively researched in this domain and

M. Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Sivan Doveh

Prompt ensembling of Large Language Model (LLM) generated category-specific prompts has emerged as an effective method to enhance zero-shot recognition ability of Vision-Language Models (VLMs). To obtain these category-specific prompts, the present methods rely on hand-crafting the prompts to the LLMs for generating VLM prompts for the downstream tasks. Howe

Yubo Sun, Gennian Ge

Nanopore sequencing is a promising technology for DNA sequencing. In this paper, we investigate a specific model of the nanopore sequencer, which takes a $q$-ary sequence of length $n$ as input and outputs a vector of length $n+\ell-1$ referred to as an $\ell$-read vector where the $i$-th entry is a multi-set composed of the $\ell$ elements located between t

Julia Kamml, Claire Acevedo, David Kammer

The mineralized collagen fibril is the main building block of hard tissues and it directly affects the macroscopic mechanics of biological tissues such as bone. The mechanical behavior of the fibril itself is determined by its structure: the content of collagen molecules, minerals, and cross-links, and the mechanical interactions and properties of these comp

Aditya Narayan Sankaran, Vigneshwaran Shankaran, Sampath Lonka, Rajesh Sharma

Rhymes and poems are a powerful medium for transmitting cultural norms and societal roles. However, the pervasive existence of gender stereotypes in these works perpetuates biased perceptions and limits the scope of individuals' identities. Past works have shown that stereotyping and prejudice emerge in early childhood, and developmental research on causal m

Chuang Yu, Yunpeng Liu, Jinmiao Zhao, Dou Quan

Recently, feature relation learning has drawn widespread attention in cross-spectral image patch matching. However, existing related research focuses on extracting diverse relations between image patch features and ignores sufficient intrinsic feature representations of individual image patches. Therefore, we propose an innovative relational representation l

Yubo Sun, Ziyang Lu, Yiwei Zhang, Gennian Ge

Recently, codes for correcting a burst of errors have attracted significant attention. One of the most important reasons is that bursts of errors occur in certain emerging techniques, such as DNA storage. In this paper, we investigate a type of error, called a $(t,s)$-burst, which deletes $t$ consecutive symbols and inserts $s$ arbitrary symbols at the same

Denys Bulavka, Éric Colin de Verdière, Niloufar Fuladi

We initiate the study of computing shortest non-separating simple closed curves with some given topological properties on non-orientable surfaces. While, for orientable surfaces, any two non-separating simple closed curves are related by a self-homeomorphism of the surface, and computing shortest such curves has been vastly studied, for non-orientable ones t

Christian Leibel, Lutz Bornmann

Wu et al. (2019) proposed the disruption index (DI1) as a bibliometric indicator that measures disruptive and consolidating research. Leibel and Bornmann (2024) recently published a literature overview on the disruption index research in Scientometrics. In this letter to the editor, we point out that the method of calculating the DI1 score of a focal paper c

Nicholas Popovič, Michael Färber

Streaming text generation has become a common way of increasing the responsiveness of language model powered applications, such as chat assistants. At the same time, extracting semantic information from generated text is a useful tool for applications such as automated fact checking or retrieval augmented generation. Currently, this requires either separate

Jiayi Cai, Pierre-Emmanuel Angeli, Jean-Marc Martinez, Guillaume Damblin

Several Tensor Basis Neural Network (TBNN) frameworks aimed at enhancing turbulence RANS modeling have recently been proposed in the literature as data-driven constitutive models for systems with known invariance properties. However, persistent ambiguities remain regarding the physical adequacy of applying the General Eddy Viscosity Model (GEVM). This work a

José Ignacio Burgos Gil, Jürg Kramer

In this paper we extend the arithmetic intersection theory of adelic divisors on quasiprojective varieties developed by X. Yuan and S. W. Zhang to cover certain adelic arithmetic divisors that are not nef nor integrable. The key concept used in this extension is the relative finite energy introduced by T. Darvas, E. Di Nezza, and C. H. Lu. As an application,

Christian P. C. Franssen, Alessandro Zocca, Bernd F. Heidergott

Graphs are commonly used to model various complex systems, including social networks, power grids, transportation networks, and biological systems. In many applications, the connectivity of these networks can be expressed through the Mean First Passage Times (MFPTs) of a Markov chain modeling a random walker on the graph. In this paper, we generalize the net

Philip Matthias Winter, Maria Wimmer, David Major, Dimitrios Lenis

This work addresses flexibility in deep learning by means of transductive reasoning. For adaptation to new data and tasks, e.g., in continual learning, existing methods typically involve tuning learnable parameters or complete re-training from scratch, rendering such approaches unflexible in practice. We argue that the notion of separating computation from m

Lorenzo Amatucci, Giulio Turrisi, Angelo Bratta, Victor Barasuol

This paper presents a novel approach to enhance Model Predictive Control (MPC) for legged robots through Distributed Optimization. Our method focuses on decomposing the robot dynamics into smaller, parallelizable subsystems, and utilizing the Alternating Direction Method of Multipliers (ADMM) to ensure consensus among them. Each subsystem is managed by its o

G S Mamatha, Namya Dimri, Rasha Sinha

The advent of quantum computing poses a profound threat to traditional cryptographic systems, exposing vulnerabilities that compromise the security of digital communication channels reliant on RSA, ECC, and similar classical encryption methods. Quantum algorithms, notably Shor's algorithm, exploit the inherent computational power of quantum computers to effi

Matteo D'Achille, Nathanaël Enriquez, Paul Melotti

We identify the local limit of massive spanning forests on the complete graph. This generalizes a well-known theorem of Grimmett on the local limit of uniform spanning trees on the complete graph.

Deeksha Gupta, Maryna Pankratova, Matthias Riepp, Manuel Pereiro

Femtosecond laser pulses can be used to induce ultrafast changes of the magnetization in magnetic materials. Several microscopic mechanisms have been proposed to explain the observations, including the transport of ultrashort spin-polarized hot-electrons (SPHE). Such ultrafast spin currents find growing interest because of the recent challenges in ultrafast

Alexandre Pannier, Cristopher Salvi

We develop a kernel-based solver for path-dependent PDEs (PPDEs) along with a convergence theory. Our numerical scheme leverages signature kernels, a recently introduced class of kernels on path-space. Specifically, we solve an optimal recovery problem by approximating the solution of a PPDE with an element of minimal norm in the signature reproducing kernel

Victoria Marie Tuck, Pei-Wei Chen, Georgios Fainekos, Bardh Hoxha

Multi-Robot Task Allocation (MRTA) is a problem that arises in many application domains including package delivery, warehouse robotics, and healthcare. In this work, we consider the problem of MRTA for a dynamic stream of tasks with task deadlines and capacitated agents (capacity for more than one simultaneous task). Previous work commonly focuses on the sta

Ryota Namai, Satoshi Higashino, Hirohisa Ishiura, Tomonori Ikeda

Direct detection of weakly interacting massive particles (WIMPs) can provide strong evidence of their existence and the directional method would have an advantage over other methods to detect the clear signal of WIMPs. Time projection chambers with micro-patterned gaseous detectors (MPGDs) are one of the common devices used in directional WIMP searches. A mi

Yuxuan Li, Xiang Li, Yimian Dai, Qibin Hou

Remote sensing images pose distinct challenges for downstream tasks due to their inherent complexity. While a considerable amount of research has been dedicated to remote sensing classification, object detection and semantic segmentation, most of these studies have overlooked the valuable prior knowledge embedded within remote sensing scenarios. Such prior k

Simon Ståhlberg, Blai Bonet, Hector Geffner

GNN-based approaches for learning general policies across planning domains are limited by the expressive power of $C_2$, namely; first-order logic with two variables and counting. This limitation can be overcame by transitioning to $k$-GNNs, for $k=3$, wherein object embeddings are substituted with triplet embeddings. Yet, while $3$-GNNs have the expressive

Piotr Sworowski

Given arbitrary $r\ge1$, we construct an HK$_r$-integrable function which is not P$_1$-integrable. This is an extension of Musial et al.\ construction published recently in [Musial, P., Skvortsov, V., Tulone, F.: The HK$_r$-integral is not contained in the P$_r$-integral. Proc. Amer. Math. Soc. {\bf150}(5), 2107--2114 (2022)].

George Close, Thomas Hain, Stefan Goetze

Within the area of speech enhancement, there is an ongoing interest in the creation of neural systems which explicitly aim to improve the perceptual quality of the processed audio. In concert with this is the topic of non-intrusive (i.e. without clean reference) speech quality prediction, for which neural networks are trained to predict human-assigned qualit

Viktor Novičenko, Šarūnas Vaitekonis

The plant (the system to be controlled) is disturbed by a periodic external force with a broad spectrum of Fourier harmonics. The first Fourier harmonic (sine-type signal) is assumed to be undesirable and should be removed by a control force, whereas the other harmonics should be preserved without distortion. Because the measured plant data have an unknown a

Simon Mataigne, Ralf Zimmermann, Nina Miolane

Since the popularization of the Stiefel manifold for numerical applications in 1998 in a seminal paper from Edelman et al., it has been exhibited to be a key to solve many problems from optimization, statistics and machine learning. In 2021, H\"uper et al. proposed a one-parameter family of Riemannian metrics on the Stiefel manifold, subsuming the well-known

Kento Kawaharazuka, Akihiro Miki, Masahiro Bando, Temma Suzuki

Various musculoskeletal humanoids have been developed so far. While these humanoids have the advantage of their flexible and redundant bodies that mimic the human body, they are still far from being applied to real-world tasks. One of the reasons for this is the difficulty of bipedal walking in a flexible body. Thus, we developed a musculoskeletal wheeled ro

Johannes Fischer, Kevin Rösch, Martin Lauer, Christoph Stiller

Validating robotic systems in safety-critical appli-cations requires testing in many scenarios including rare edgecases that are unlikely to occur, requiring to complement real-world testing with testing in simulation. Generative models canbe used to augment real-world datasets with generated data toproduce edge case scenarios by sampling in a learned latent

Agnieszka Janicka, Fiona Sloothaak, Maria Vlasiou

Cascading failures, wherein the failure of one component triggers subsequent failures in complex interconnected systems, pose a significant risk of disruptions and emerge across various domains. Understanding and mitigating the risk of such failures is crucial to minimize their impact and ensure the resilience of these systems. In multiple applications, the

I. Gyollai, S. Biri, Z. Juhász, Cs. Király

Context. Identifying minerals on asteroid surfaces is difficult as space weathering modifies the minerals infrared spectra. This shouldbe better understood for proper interpretation. Aims. We simulated the space weathering effects on a meteorite and recorded the alterations of the crystalline structure, such as the change in peak positions and full width at

Sebastien Colla, Julien M. Hendrickx

We show that, in many settings, the worst-case performance of a distributed optimization algorithm is independent of the number of agents in the system, and can thus be computed in the fundamental case with just two agents. This result relies on a novel approach that systematically exploits symmetries in worst-case performance computation, framed as Semidefi

E. David, T. Kiss

In the ALICE read-out and trigger system, the present GBT and CRU based solution will also serve for Run4 without major modifications. By now, the GBT protocol has been superseded by lpGBT. Extensions of the ALICE system (e.g. the planned FoCal and ITS3 detector) will therefore require to use lpGBT while keeping the compatibility with the existing system. In

Johannes Pöppelbaum, Andreas Schwung

We propose a novel quaternionic time-series compression methodology where we divide a long time-series into segments of data, extract the min, max, mean and standard deviation of these chunks as representative features and encapsulate them in a quaternion, yielding a quaternion valued time-series. This time-series is processed using quaternion valued neural

Michał Lipka, Michał Parniak

The resolution limits of classical spectroscopy can be surpassed by quantum-inspired methods leveraging the information contained in the phase of the complex electromagnetic field. Their counterpart in spatial imaging has been widely discussed and demonstrated; however, the spectral-domain implementations are few and scarce. We experimentally demonstrate a s

Igor Grzelec, Tomáš Madaras, Alfréd Onderko

The packing of three copies of a graph $G$ is the union of three edge-disjoint copies (with the same vertex set) of $G$. In this paper, we completely solve the problem of the uniqueness of packing of three copies of 2-regular graphs. In particular, we show that $C_3,C_4,C_5,C_6$ and $2C_3$ have no packing of three copies, $C_7,C_8,C_3 \cup C_4, C_4 \cup C_4,

Hiroshi Frusawa

On approaching the dynamical transition temperature, supercooled liquids show heterogeneity over space and time. Static replica theory investigates the dynamical crossover in terms of the free energy landscape (FEL). Two kinds of static approaches have provided a self-consistent equation for determining this crossover, similar to the mode coupling theory for

Takaya Matsuura, Shinichiro Yamano, Yui Kuramochi, Toshihiko Sasaki

We developed new concentration inequalities for a quantum state on an $N$-qudit system or measurement outcomes on it that apply to an adversarial setup, where an adversary prepares the quantum state. Our one-sided concentration inequalities for a quantum state require the $N$-qudit system to be permutation invariant and are thus de-Finetti type, but they are

Alexander I. Bufetov, Yosuke Kawamoto

We investigate the intertwining of Laguerre processes of parameter $\alpha$ in different dimensions. We introduce a Feller kernel that depends on $\alpha $ and intertwines the $\alpha$-Laguerre process in $N+1$ dimensions and that in $N$ dimensions. When $\alpha $ is a non-negative integer, the new kernel is interpreted in terms of the conditional distributi

Taiichi Yamada

The equations of state for symmetric nuclear matter and pure neutron matter are investigated with the tensor-optimized Fermi Sphere method (TOFS) up to the density $\rho=0.5$~fm$^{-3}$. This method is based on a linked-cluster expansion theorem, and the energy per particle of nuclear matter ($E/A$) is calculated variationally with respect to the correlated n

Edgard Schiebelbein, Saalik Hatia, Annette Bieniusa, Gustavo Petri

This paper describes ongoing work on developing a formal specification of a database backend. We present the formalisation of the expected behaviour of a basic transactional system that calls into a simple store API, and instantiate in two semantic models. The first one is a map-based, classical versioned key-value store; the second one, journal-based, appen

Alexander Feike, Juri Fiaschi, Benjamin Fuks, Michael Klasen

To maximise the information obtained from various independent new physics searches conducted at the LHC, it is imperative to consider the combination of multiple analyses. To showcase the exclusion power gained by combining signal regions from different searches, we consider a simplified scenario inspired by supersymmetry, with all particles but one squark f

Éric Gaudron

We establish an adelic version of Dirichlet's approximation theorem on spheres. Let $K$ be a number field, $E$ be a rigid adelic space over $K$ and $q\colon E\to K$ be a quadratic form. Let $v$ be a place of $K$ and $\alpha\in E\otimes_{K}K_{v}$ such that $q(\alpha)=1$. We produce an explicit constant $c$ having the following property. If there exists $x\in

Siqi Wu, Zihan Yang, Xin Ma, Jianhui Dai

We theoretically propose Ac$_3$Ni$_2$O$_7$, La$_2$BaNi$_2$O$_6$F, and La$_2$SrNi$_2$O$_6$F compounds to be benchmark materials for bilayer nickelate superconductivity. The stable phase of Ac$_3$Ni$_2$O$_7$ and La$_2$BaNi$_2$O$_6$F are found to be $I4/mmm$ without the lattice distortion caused by octahedra rotation at ambient pressure, where as the lattice di

Bernhard H. Haak, Markus Haase

Let $f = f(z,t)$ be a function holomorphic in $z \in O \subseteq {\mathbb C}^d$ for fixed $t\in \Omega$ and measurable in $t$ for fixed $z$ and such that$z \mapsto f(z,\cdot)$ is bounded with values in$E := L_{p}(\Omega)$, $1\le p \le \infty$. It is proved (among other things) that \[ \langle t\mapsto \varphi( f(\cdot,t) ) , \mu \rangle= \varphi(z \mapsto \l

Alice Manna, Elisa Pirovano, the n\_TOF Collaboration

The $^{235}$U(n,f) reaction cross section was measured relative to neutron-proton elastic scattering for the first time in the energy region from 10 MeV to 440 MeV at the CERN n\_TOF facility, extending the upper limit of the only previous measurement in the literature by more than 200 MeV. Two independent detection systems were used simultaneously to extrac

Garance Benoit

In 1755, Kant published his General Natural History and Theory of the Heavens, in which he presented his hypothesis on the formation of the solar system, known as the primitive nebula hypothesis. This original theory of the heavens was written in dialogue with the conceptions of celestial matter of his time. On the one hand, Kant recognized Descartes' cosmol

Daichi Okada, Fumito Araoka

Light-matter strong coupling (LMSC) is intriguing state in which light and matter are coherently hybridized inside cavity. It has been gaining widespread recognition as an excellent way for controlling material properties without any chemical modification. Here we show the LMSC is a powerful state to manipulate and improve a chiral nonlinear optical (NLO) ef

Kaijie Ren, Lei Zhang

Visible-Infrared Person Re-identification (VI-ReID) is a challenging cross-modal pedestrian retrieval task, due to significant intra-class variations and cross-modal discrepancies among different cameras. Existing works mainly focus on embedding images of different modalities into a unified space to mine modality-shared features. They only seek distinctive i

Gianluca Morciano, José Manuel Alcalde-Llergo, Andrea Zingoni, Enrique Yeguas-Bolivar

Dyslexia is the most widespread specific learning disorder and significantly impair different cognitive domains. This, in turn, negatively affects dyslexic students during their learning path. Therefore, specific support must be given to these students. In addition, such a support must be highly personalized, since the problems generated by the disorder can

Antonio Alcántara, Carlos Ruiz, Calvin Tsay

Two-stage stochastic programming is a popular framework for optimization under uncertainty, where decision variables are split between first-stage decisions, and second-stage (or recourse) decisions, with the latter being adjusted after uncertainty is realized. These problems are often formulated using Sample Average Approximation (SAA), where uncertainty is

Emilian Postolache, Giorgio Mariani, Luca Cosmo, Emmanouil Benetos

Multi-Source Diffusion Models (MSDM) allow for compositional musical generation tasks: generating a set of coherent sources, creating accompaniments, and performing source separation. Despite their versatility, they require estimating the joint distribution over the sources, necessitating pre-separated musical data, which is rarely available, and fixing the

Yunhao Fan, Sheng Zhang, Gia-Wei Chern

Frustrated itinerant magnets often exhibit complex noncollinear or noncoplanar magnetic orders which support topological electronic structures. A canonical example is the anomalous quantum Hall state with a chiral spin order stabilized by electron-spin interactions on a triangular lattice. While a long-range magnetic order cannot survive thermal fluctuations

Daniel Xiang, Chao Gao

We study a hypothesis testing problem in the context of high-dimensional changepoint detection. Given a matrix $X \in \R^{p \times n}$ with independent Gaussian entries, the goal is to determine whether or not a sparse, non-null fraction of rows in $X$ exhibits a shift in mean at a common index between $1$ and $n$. We focus on three aspects of this problem:

Ruyi Xu, Yuan Yao, Zonghao Guo, Junbo Cui

Visual encoding constitutes the basis of large multimodal models (LMMs) in understanding the visual world. Conventional LMMs process images in fixed sizes and limited resolutions, while recent explorations in this direction are limited in adaptivity, efficiency, and even correctness. In this work, we first take GPT-4V and LLaVA-1.5 as representative examples

Sreeraj Nair, Chandan Mondal, Siqi Xu, Xingbo Zhao

We compute the gravitational form factors (GFFs) and study their applications for the description of the mechanical properties such as the pressure, shear force distributions, and the mechanical radius of the proton from its light-front wave functions (LFWFs) based on basis light-front quantization (BLFQ). The LFWFs of the proton are given by the lowest eige