April 2023 arXiv papers — page 147

Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, Reut Tsarfaty

Disagreement in natural language annotation has mostly been studied from a perspective of biases introduced by the annotators and the annotation frameworks. Here, we propose to analyze another source of bias: task design bias, which has a particularly strong impact on crowdsourced linguistic annotations where natural language is used to elicit the interpreta

Dirk Erhard, Julien Poisat

In this paper we introduce a topology under which the pair empirical measure of a large class of random walks satisfies a strong Large Deviation principle. The definition of the topology is inspired by the recent article by Mukherjee and Varadhan~\cite{MV2016}. This topology is natural for translation-invariant problems such as the downward deviations of the

Chi Zhang, Wenjie Ruan, Fu Wang, Peipei Xu

Verification plays an essential role in the formal analysis of safety-critical systems. Most current verification methods have specific requirements when working on Deep Neural Networks (DNNs). They either target one particular network category, e.g., Feedforward Neural Networks (FNNs), or networks with specific activation functions, e.g., RdLU. In this pape

L Wolff-Trombini, A Ceripa, J Moreau, H Galinat

We propose a combination of microrheological and structural characterizations of fibrin networks to study blood hypercoagulability. Fibrin is the central element of coagulation as its polymerization creates the network of fibers in which platelets and red blood cells are included. This is a controlled process via cascades between various coagulation factors.

Céline Esser, Stéphane Jaffard, Béatrice Vedel

We study the regularity properties of random wavelet series constructed by multiplying the coefficients of a deterministic wavelet series with unbounded I.I.D. random variables. In particular, we show that, at the opposite to what happens for Fourier series, the randomization of almost every continuous function gives an almost surely nowhere locally bounded

Loïc Foissy

Using the formalism of species and twisted objects, we introduce two structures of cointeracting bialgebras on hypergraphs, induced by two notions of induced sub-hypergraphs. We study the associated unique morphisms of cointeracting bialgebras from hypergraphs to the polynomial algebra in one indeterminate: in the first case, this gives the chromatic polynom

Juho Vepsäläinen, Arto Hellas, Petri Vuorimaa

The evolution of the web can be characterized as an emergence of frameworks paving the way from static websites to dynamic web applications. As the scope of web applications has grown, new technical challenges have emerged, leading to the need for new solutions. The latest of these developments is the rise of so-called disappearing web frameworks that questi

Paul Escande

Obtaining guarantees on the convergence of the minimizers of empirical risks to the ones of the true risk is a fundamental matter in statistical learning. Instead of deriving guarantees on the usual estimation error, the goal of this paper is to provide concentration inequalities on the distance between the sets of minimizers of the risks for a broad spectru

Lucas Gréaux, Jonathan Biteau

The extragalactic background light (EBL) is the aggregate of all optical and infrared emissions from thermal processes since the cosmic dark ages. While the integrated light of galaxies is expected to be the main contribution to the EBL, recent measurements beyond Pluto's orbit from the New Horizon probe show a 4$\sigma$ excess in the optical band. This tens

Philippe Laurençot

Convergence to a steady state in the long term limit is established for global weak solutions to a chemotaxis model with degenerate local sensing and consumption, when the motility function is C^1-smooth on [0, $\infty$), vanishes at zero, and is positive on (0, $\infty$). A condition excluding that the large time limit is spatially homogeneous is also provi

Antonio Celentano, Alba Lia Masiello, Gloria Paoli

Symmetry properties of solutions to elliptic quasilinear equations have been widely studied in the context of Dirichlet boundary conditions. We show that, in the context of Robin boundary conditions, the symmetry property \'a la Gidas, Ni and Nirenberg does not hold in dimension $n\geq 2$, even for superharmonic functions, and we provide an explicit example.

Andrey Kudlis, Denis Novokreschenov, Ivan Iorsh, Ilya Tokatly

We consider a system comprising two groups of quantum dimers placed in a common electromagnetic cavity, and controlled by selectively applying a static external potential to one of the groups. We show that in the regime of deep strong coupling to vacuum electromagnetic fluctuations, the emergent photon-assisted interaction between the dimers leads to a stron

Despina-Ekaterini Argiropoulos, Dimitrios Papageorgiou, Michael Maravgakis, Drosakis Drosakis

Task space trajectory tracking for quadruped robots plays a crucial role on achieving dexterous maneuvers in unstructured environments. To fulfill the control objective, the robot should apply forces through the contact of the legs with the supporting surface, while maintaining its stability and controllability. In order to ensure the operation of the robot

Mathukumalli Vidyasagar

In this paper, we present a brief survey of Reinforcement Learning (RL), with particular emphasis on Stochastic Approximation (SA) as a unifying theme. The scope of the paper includes Markov Reward Processes, Markov Decision Processes, Stochastic Approximation algorithms, and widely used algorithms such as Temporal Difference Learning and $Q$-learning.

Anass Bairouk, Marc Chaumont, Dominique Fouchez, Jerome Paquet

Aims. The treatment of astronomical image time series has won increasing attention in recent years. Indeed, numerous surveys following up on transient objects are in progress or under construction, such as the Vera Rubin Observatory Legacy Survey for Space and Time (LSST), which is poised to produce huge amounts of these time series. The associated scientifi

Yu Ichida, Takashi Okuda Sakamoto

This paper reports results on the classification of traveling wave solutions, including nonnegative weak sense, in the spatial 1D degenerate parabolic equation. These are obtained through dynamical systems theory and geometric approaches (in particular, Poincar\'e compactification). Classification of traveling wave solutions means enumerating those that exis

Marcus Nordström, Henrik Hult, Atsuto Maki, Fredrik Löfman

This paper presents a study on the soft-Dice loss, one of the most popular loss functions in medical image segmentation, for situations where noise is present in target labels. In particular, the set of optimal solutions are characterized and sharp bounds on the volume bias of these solutions are provided. It is further shown that a sequence of soft segmenta

Pirmin Lemberger, Antoine Saillenfest

We introduce a new dataset named WikiVitals which contains a large graph of 48k mutually referred Wikipedia articles classified into 32 categories and connected by 2.3M edges. Our aim is to rigorously evaluate the contributions of three distinct sources of information to the label prediction in a semi-supervised node classification setting, namely the conten

Guangkuo Li, Yuhua Li, Feng Ye, Qian Li

We investigate the effect of a lower index oxide layer inclusion within a highly doped silica glass slot waveguide for optimized supercontinuum generation at telecom wavelengths. By controlling the thickness of the oxide slot, we demonstrate that one can engineer the waveguide dispersion profile so that to obtain supercontinua with vastly different spectral

Rishabh Upadhyay, Dmitry S. Golubev, Yu-Cheng Chang, George Thomas

The fragile nature of quantum circuits is a major bottleneck to scalable quantum applications. Operating at cryogenic temperatures, quantum circuits are highly vulnerable to amplifier backaction and external noise. Non-reciprocal microwave devices such as circulators and isolators are used for this purpose. These devices have a considerable footprint in cryo

Jesús A. Álvarez López, Yuri A. Kordyukov, Eric Leichtnam

Given a closed manifold $M$ and a closed regular submanifold $L$, consider the corresponding locally convex space $I=I(M,L)$ of conormal distributions, with its natural topology, and the strong dual $I'=I'(M,L)=I(M,L;\Omega)'$ of the space of conormal densities. It is shown that $I$ is a barreled, ultrabornological, webbed, Montel, acyclic LF-space, and $I'$

James Sikora, Jason Rowe, Saugata Barat, Jacob L. Bean

The early K-type T-Tauri star, V1298 Tau ($V=10\,{\rm mag}$, ${\rm age}\approx20-30\,{\rm Myr}$) hosts four transiting planets with radii ranging from $4.9-9.6\,R_\oplus$. The three inner planets have orbital periods of $\approx8-24\,{\rm d}$ while the outer planet's period is poorly constrained by single transits observed with \emph{K2} and \emph{TESS}. Pla

Emma Hogan, Charles Semple

The classes of bicircular matroids and lattice path matroids are closed under minors. The complete list of excluded minors for the class of lattice path matroids is known, and it has been recently shown that the analogous list for the class of bicircular matroids is finite. In this paper, we establish the complete list of excluded minors for the class of mat

Lei Fu, Paola Torrico Morón, Jorge Peña Queralta, David Hästbacka

Remote identification of Unmanned Aerial Vehicles (UAVs) is becoming increasingly important since more UAVs are being widely used for different needs in urban areas. For example, in the US and in the EU, identification and position broadcasting is already a requirement for the use of drones. However, the current solutions do not validate the position of the

Simon Ellmeyer, Georg C. Hofstätter

Interpolating between the classic notions of intersection and polar centroid bodies, (real) $L_p$-intersection bodies, for $-1<p<1$, play an important role in the dual $L_p$-Brunn--Minkowski theory. Inspired by the recent construction of complex centroid bodies, a complex version of $L_p$-intersection bodies, with range extended to $p>-2$, is introduced, int

Juan Lagos, Urho Lempiö, Esa Rahtu

While the availability of large and diverse datasets has contributed to significant breakthroughs in autonomous driving and indoor applications, forestry applications are still lagging behind and new forest datasets would most certainly contribute to achieving significant progress in the development of data-driven methods for forest-like scenarios. This pape

Suho Lee, Seungwon Seo, Jihyo Kim, Yejin Lee

Recently, source-free unsupervised domain adaptation (SFUDA) has emerged as a more practical and feasible approach compared to unsupervised domain adaptation (UDA) which assumes that labeled source data are always accessible. However, significant limitations associated with SFUDA approaches are often overlooked, which limits their practicality in real-world

Lorenzo Cavallina

A celebrated theorem of Serrin asserts that one overdetermined condition on the boundary is enough to obtain radial symmetry in the so-called one-phase overdetermined torsion problem. It is also known that imposing just one overdetermined condition on the boundary is not enough to obtain radial symmetry in the corresponding multi-phase overdetermined problem

Jakob Ambsdorf

With deep neural models increasingly permeating our daily lives comes a need for transparent and comprehensible explanations of their decision-making. However, most explanation methods that have been developed so far are not intuitively understandable for lay users. In contrast, natural language explanations (NLEs) promise to enable the communication of a mo

Guang Yang, Mingyu Cai, Ahmad Ahmad, Amanda Prorok

We present LQR-CBF-RRT*, an incremental sampling-based algorithm for offline motion planning. Our framework leverages the strength of Control Barrier Functions (CBFs) and Linear Quadratic Regulators (LQR) to generate safety-critical and optimal trajectories for a robot with dynamics described by an affine control system. CBFs are used for safety guarantees,

Léo Baty, Kai Jungel, Patrick S. Klein, Axel Parmentier

With the rise of e-commerce and increasing customer requirements, logistics service providers face a new complexity in their daily planning, mainly due to efficiently handling same day deliveries. Existing multi-stage stochastic optimization approaches that allow to solve the underlying dynamic vehicle routing problem are either computationally too expensive

Yuheng Lu, Chenfeng Xu, Xiaobao Wei, Xiaodong Xie

The goal of open-vocabulary detection is to identify novel objects based on arbitrary textual descriptions. In this paper, we address open-vocabulary 3D point-cloud detection by a dividing-and-conquering strategy, which involves: 1) developing a point-cloud detector that can learn a general representation for localizing various objects, and 2) connecting tex

Katharina Hopf, Ansgar Jüngel

This article is concerned with the development of a theoretical framework of global measure-valued solutions for a class of hyperbolic-parabolic cross-diffusion systems, and its application to the convergence analysis of a fully discrete finite-volume scheme. After introducing an appropriate notion of dissipative measure-valued solutions to the PDE system, a

Stefano Biagi, Giulia Meglioli, Fabio Punzo

We investigate the validity of the Liouville property for a class of elliptic equations with a potential, posed on infinite graphs. Under suitable assumptions on the graph and on the potential, we prove that the unique bounded solution is $u\equiv 0$. We also show that on a special class of graphs the condition on the potential is optimal, in the sense that

Takashi Kurumaji

The in-plane (thermal) Hall effect is an unconventional transverse response when the applied magnetic field is in the (heat) current plane. In contrast to the normal Hall effect, the in-plane Hall effect requires the absence of certain crystal symmetries, and possibly manifests a non-trivial topology of quantum materials. An accurate estimation of the intrin

Wenjie Yin, Ruibo Tu, Hang Yin, Danica Kragic

Data-driven and controllable human motion synthesis and prediction are active research areas with various applications in interactive media and social robotics. Challenges remain in these fields for generating diverse motions given past observations and dealing with imperfect poses. This paper introduces MoDiff, an autoregressive probabilistic diffusion mode

Yanda Li, Zilong Huang, Gang Yu, Ling Chen

Image matting requires high-quality pixel-level human annotations to support the training of a deep model in recent literature. Whereas such annotation is costly and hard to scale, significantly holding back the development of the research. In this work, we make the first attempt towards addressing this problem, by proposing a self-supervised pre-training ap

Giovanni Catino, Alberto Roncoroni

In this paper we prove a closure result for globally hyperbolic spacetimes satisfying, at a certain time, natural assumptions on the deceleration, the pressure and the Hubble constant. The main tool that we use is a general Bonnet-Myers type result.

Youjia Zhang, Teng Xu, Junqing Yu, Yuteng Ye

Recovering the physical attributes of an object's appearance from its images captured under an unknown illumination is challenging yet essential for photo-realistic rendering. Recent approaches adopt the emerging implicit scene representations and have shown impressive results.However, they unanimously adopt a surface-based representation,and hence can not w

Lei Fu, Salma Salimi, Jorge Peña Queralta, Tomi Westerlund

The integration of blockchain technology in robotic systems has been met by the community with a combination of hype and skepticism. The current literature shows that there is indeed potential for more secure and trustable distributed robotic systems. However, it is still unclear in what aspects of robotics beyond high-level decision making can blockchain te

Iacopo Catalano, Jorge Peña Queralta, Tomi Westerlund

Drones have become essential tools in a wide range of industries, including agriculture, surveying, and transportation. However, tracking unmanned aerial vehicles (UAVs) in challenging environments, such cluttered or GNSS-denied environments, remains a critical issue. Additionally, UAVs are being deployed as part of multi-robot systems, where tracking their

Hyeongjun Kwon, Taeyong Song, Somi Jeong, Jin Kim

Recent progress in deterministic prompt learning has become a promising alternative to various downstream vision tasks, enabling models to learn powerful visual representations with the help of pre-trained vision-language models. However, this approach results in limited performance for dense prediction tasks that require handling more complex and diverse ob

Mengyao Ding, Yuzhou Fang, Chao Zhang

We consider the mixed local and nonlocal functionals with nonstandard growth \begin{eqnarray*} u\mapsto\int_{\Omega}(|Du|^p-f(x)u)\,dx+\int_{\mathbb{R}^N}\int_{\mathbb{R}^N}\frac{|u(x)-u(y)|^q}{|x-y|^{N+sq}}\,dxdy \end{eqnarray*} with $1<p\le sq$, $0<s<1$ and $\Omega\subset\mathbb{R}^N$ being a bounded domain. We study, by means of expansion of positivity, l

Hiroshi Kudo, Hiroshi Naramoto, Masao Sataka, Satoshi Ishii

Transmission-type elastic recoil detection analysis (T-ERDA) using 8.02 MeV He has been successfully applied to determine the concentration of ubiquitous deuterium in mylar and PPS films, both containing hydrogen as a component. The determined D/H ratios of $(1.60\pm 0.08) \times 10^{-4}$ and $(1.23\pm 0.08) \times 10^{-4}$ for mylar and PPS, respectively, a

Zhiwei Jia, Vineet Thumuluri, Fangchen Liu, Linghao Chen

We study generalizable policy learning from demonstrations for complex low-level control (e.g., contact-rich object manipulations). We propose a novel hierarchical imitation learning method that utilizes sub-optimal demos. Firstly, we propose an observation space-agnostic approach that efficiently discovers the multi-step subskill decomposition of the demos

Alessia Franchini, Matteo Bonetti, Alessandro Lupi, Giovanni Miniutti

X-ray quasi-periodic eruptions (QPEs) represent a recently discovered example of extreme X-ray variability associated with supermassive black holes. These are high-amplitude bursts recurring every few hours that are detected in the soft X-ray band from the nuclei of nearby galaxies whose optical spectra lack the broad emission lines typically observed in uno

Mireille Tixier, Joël Pouget

Electroactive polymers (EAP) are smart materials that can be used as actuators, sensors or energy harvesters in many fields. We had previously studied an ionic metal-polymer composites (IPMC), which consists in an ionic polymer film such as Nafion saturated with water and coated on both sides with a thin layer of metal acting as electrodes. This system bends

Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi, Ikboljon Sobirov

The number of studies on deep learning for medical diagnosis is expanding, and these systems are often claimed to outperform clinicians. However, only a few systems have shown medical efficacy. From this perspective, we examine a wide range of deep learning algorithms for the assessment of glioblastoma - a common brain tumor in older adults that is lethal. S

Pagdame Tiebekabe, Kouèssi Norbert Adédji, Nadjime Pindra, Mahouton Norbert Hounkonnou

Narayana's sequence is a ternary recurrent sequence defined by the recurrence relation $\mathcal{N}_n=\mathcal{N}_{n-1}+\mathcal{N}_{n-3}$ with initial terms $\mathcal{N}_0=0$ and $\mathcal{N}_1=\mathcal{N}_2=\mathcal{N}_3=1$. Let $\rho\geqslant2$ be a positive integer. In this study, it is proved that the $n$th Narayana's number $ \mathcal{N}_n$ which is co

Yue Feng, Yichen Guo, Yongjun Yuan

We establish the uniform error bound of an exponential wave integrator Fourier pseudospectral (EWI-FP) method for the long-time dynamics of the nonlinear Schr\"odinger equation with wave operator (NLSW), in which the strength of the nonlinearity is characterized by $\varepsilon^{2p}$ with $\varepsilon \in (0, 1]$ a dimensionless parameter and $p \in \mathbb{

Jaewook J. Suh, Jisun Park, Ernest K. Ryu

Recently, the anchor acceleration, an acceleration mechanism distinct from Nesterov's, has been discovered for minimax optimization and fixed-point problems, but its mechanism is not understood well, much less so than Nesterov acceleration. In this work, we analyze continuous-time models of anchor acceleration. We provide tight, unified analyses for characte

Antoine Godichon-Baggioni, Wei Lu

In the context of large samples, a small number of individuals might spoil basic statistical indicators like the mean. It is difficult to detect automatically these atypical individuals, and an alternative strategy is using robust approaches. This paper focuses on estimating the geometric median of a random variable, which is a robust indicator of central te

Ramana Patibandla, Saswata Basak, Anubhab Roy, Ratul Dasgupta

We study a class of initial value problems (IVPs) involving perturbations on a density stratified, quiescent, viscous liquid layer with a free-surface. The geometry is a two-dimensional, rectangular configuration taking into account surface-tension and gravity. Linearised predictions are obtained by solving the IVP analytically for free-surface and vortical

Xiliang Fan, Xing Huang, Zewei Ling

In this paper, we investigate the regularities for a class of distribution dependent SDEs driven by two independent fractional noises $B^H$ and $\ti B^{\ti H}$ with Hurst parameters $H\in(0,1)$ and $\ti H\in(1/2,1)$. We establish the log-Harnack inequalities and Bismut formulas for the Lions derivative to this type of equations with distribution dependent no

Jiakang Bao

We consider the quiver Yangians associated to general affine Dynkin diagrams. Although the quivers are generically not toric, the algebras have some similar structures. The odd reflections of the affine Dynkin diagrams should correspond to Seiberg duality of the quivers, and we investigate the relations of the dual quiver Yangians. We also mention the constr

Henri Lantéri

The purpose of this note is to extend the divergences analyzed in a previous work by application of the Deformed Logarithm in its most general form. In a study on entropic divergences, we have analyzed the different forms of the deformed logarithm and their applications to this type of divergence. A very general form of the deformed logarithm has been highli

Iván Toledano--Juárez, Eduardo de la Fuente, Miguel A. Trinidad, Daniel Tafoya

We present a study of the central zone of the star-forming region L1448 at 217--230 GHz ($\sim$ 1.3 mm) using ALMA observations. Our study focuses on the detection of proto-stellar molecular outflows and the interaction with the surrounding medium toward sources L1448--C(N) and L1448--C(S). Both sources exhibit continuum emission, with L1448--C(N) being the

Malte Lehna, Jan Viebahn, Christoph Scholz, Antoine Marot

The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production. As a consequence, active grid management is reaching its limits with conventional approaches. In the context of the Learning to Run a Power Network challenge, it has been shown that Reinforcement Learning (RL) is an

Jan Wiersig

The Petermann factor and the phase rigidity are convenient measures for various aspects of open quantum and wave systems, such as the sensitivity of energy eigenvalues to perturbations or the magnitude of quantum excess noise in lasers. We discuss the behavior of these two important quantities near non-Hermitian degeneracies, so-called exceptional points. Fo

Jerome White, Chandan Agrawal, Anmol Ojha, Apoorv Agnihotri

This paper presents a dataset of agricultural pest images captured over five years by thousands of small holder farmers and farming extension workers across India. The dataset has been used to support a mobile application that relies on artificial intelligence to assist farmers with pest management decisions. Creation came from a mix of organized data collec

Wei Zhao, Weixian Li, Shenghao Yang, Fang-Wei Fu

Determining the weight distribution of a linear code is a classical and fundamental topic in coding theory that has been extensively investigated. Repeated-root cyclic codes, which form a significant subclass of error-correcting codes, have found broad applications in quantum error-correcting codes, symbol-pair codes, and storage codes. Through polynomial de

Fang Zhao, Zekun Li, Shaoli Huang, Junwu Weng

This paper proposes an anchor-based deformation model, namely AnchorDEF, to predict 3D garment animation from a body motion sequence. It deforms a garment mesh template by a mixture of rigid transformations with extra nonlinear displacements. A set of anchors around the mesh surface is introduced to guide the learning of rigid transformation matrices. Once t

Xing-Jian Lv, Xiao-Jun Bi, Kun Fang, Peng-Fei Yin

Recent studies on cosmic rays (CRs) have reported the possibility of an excess in the antiproton flux around $10-20$ GeV. However, the associated systematic uncertainties have impeded the interpretation of these findings. In this study, we conduct a global Bayesian analysis to constrain the propagation parameters and evaluate the CR antiproton spectrum, whil

Yun-Hin Chan, Zhihan Jiang, Jing Deng, Edith C. -H. Ngai

Federated learning (FL) facilitates edge devices to cooperatively train a global shared model while maintaining the training data locally and privately. However, a common assumption in FL requires the participating edge devices to have similar computation resources and train on an identical global model architecture. In this study, we propose an FL method ca

A. J. Coelho, J. Loizu, P. Ricci, M. Ramisch

We present a validation of a three-dimensional, two-fluid simulation of plasma turbulence in the TJ-K stellarator, a low temperature plasma experiment ideally suited for turbulence measurements. The simulation is carried out by the GBS code, recently adapted to simulate 3D magnetic fields. The comparison shows that GBS retrieves the main turbulence propertie

Khalid Alnujaidi, Ghada Alhabib, Abdulaziz Alodhieb

As the population grows and more land is being used for urbanization, ecosystems are disrupted by our roads and cars. This expansion of infrastructure cuts through wildlife territories, leading to many instances of Wildlife-Vehicle Collision (WVC). These instances of WVC are a global issue that is having a global socio-economic impact, resulting in billions

Duifje Maria van Egmond, Urko Reinosa

We analyze how gauge fixing, which is required by any practical continuum approach to gauge systems, can interfere with the physical symmetries of such systems. In principle, the gauge fixing procedure, which deals with the (unphysical) gauge symmetry, should not interfere with the other (physical) symmetries. In practice, however, there can be an interferen

Xianghua Zeng, Hao Peng, Angsheng Li

Role-based learning is a promising approach to improving the performance of Multi-Agent Reinforcement Learning (MARL). Nevertheless, without manual assistance, current role-based methods cannot guarantee stably discovering a set of roles to effectively decompose a complex task, as they assume either a predefined role structure or practical experience for sel

F. Sarcinella, S. Śmiga, F. Della Sala, E. Fabiano

The development of kinetic energy (KE) functionals is one of the current challenges in density functional theory (DFT). The Yukawa non-local KE functionals [Phys. Rev. B 103, 155127 (2021)] have been shown to describe accurately the Lindhard response of the homogeneous electron gas (HEG) directly in the real space, without any step in the reciprocal space. H

Yujie Tang, Yang Zheng

Direct policy search has achieved great empirical success in reinforcement learning. Recently, there has been increasing interest in studying its theoretical properties for continuous control, and fruitful results have been established for linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) control that are smooth and nonconvex. In this pape

Antoine P. Leeman, Jerome Sieber, Samir Bennani, Melanie N. Zeilinger

This paper addresses the problem of optimally controlling nonlinear systems with norm-bounded disturbances and parametric uncertainties while robustly satisfying constraints. The proposed approach jointly optimizes a nominal nonlinear trajectory and an error feedback, requiring minimal offline design effort and offering low conservatism. This is achieved by

Alexandr Prishlyak, Serhii Stas

We investigate topological propeties of flows with one singular point and without closed orbits on the 2-dimensional disk. To classify such flows, destingueshed graph is used, which is a two-colored rooted tree imbedded in the plane. We construct a code of the flow and have found all possible structures of the flows with no more then 7 sepapratrices.

Jiaojian Shi, Haowei Xu, Christian Heide, Changan HuangFu

Nonlinear optical materials possess wide applications, ranging from terahertz and mid-infrared detection to energy harvesting. Recently, the correlations between nonlinear optical responses and topological properties, such as Berry curvature and the quantum metric tensor, have stimulated great interest. Here, we report giant room-temperature nonlinearities i

Ziyin Zeng, Qingyong Hu, Zhong Xie, Jian Zhou

We study the problem of semantic segmentation of large-scale 3D point clouds. In recent years, significant research efforts have been directed toward local feature aggregation, improved loss functions and sampling strategies. While the fundamental framework of point cloud semantic segmentation has been largely overlooked, with most existing approaches rely o

Rahul K Dash, Shankar Kumar Selvaraja

We propose and demonstrate a hybrid waveguide platform using layered amorphous silicon and silicon nitride. The waveguide offers more degrees of freedom to design waveguides with desired confinement, effective index and polarization birefringence. Unlike single core material, the proposed waveguide offers design flexibility, and light confinement in the laye

Rong Lin, Zhekai Luo, Jiansen He, Lun Xie

An accurate solar wind speed model is important for space weather predictions, catastrophic event warnings, and other issues concerning solar wind - magnetosphere interaction. In this work, we construct a model based on convolutional neural network (CNN) and Potential Field Source Surface (PFSS) magnetograms, considering a solar wind source surface of $R_{\r

Ran Lu

Compared to scalar framelets, multiframelets have certain advantages, such as relatively smaller supports on generators, high vanishing moments, etc. The balancing property of multiframelets is very desired, as it reflects how efficient vector-valued data can be processed under the corresponding discrete multiframelet transform. Most of the literature studyi

Daicong Da, Wei Chen

Data-driven methods have gained increasing attention in computational mechanics and design. This study investigates a two-scale data-driven design for thermal metamaterials with various functionalities. To address the complexity of multiscale design, the design variables are chosen as the components of the homogenized thermal conductivity matrix originating

Wenbo Hu, Hongjian Zhan, Xinchen Ma, Cong Liu

In the field of historical manuscript research, scholars frequently encounter novel symbols in ancient texts, investing considerable effort in their identification and documentation. Although existing object detection methods achieve impressive performance on known categories, they struggle to recognize novel symbols without retraining. To address this limit

Andrea Bisterzo, Alberto Farina, Stefano Pigola

On a complete Riemannian manifold $(M,g)$, we consider $L^{p}_{loc}$ distributional solutions of the the differential inequality $-\Delta u + \lambda u \geq 0$ with $\lambda >0$ a locally bounded function that may decay to $0$ at infinity. Under suitable growth conditions on the $L^{p}$ norm of $u$ over geodesic balls, we obtain that any such solution must b

Shanshan Zhang, Ying Cui, Wen Chen

Massive access has been challenging for the fifth generation (5G) and beyond since the abundance of devices causes communication overload to skyrocket. In an uplink massive access scenario, device traffic is sporadic in any given coherence time. Thus, channels across the antennas of each device exhibit correlation, which can be characterized by the row spars

Jiadong Chen, Samuel R. Cross, Lincoln J. Miara, Jeong-Ju Cho

Efficient synthesis recipes are needed both to streamline the manufacturing of complex materials and to accelerate the realization of theoretically predicted materials. Oftentimes the solid-state synthesis of multicomponent oxides is impeded by undesired byproduct phases, which can kinetically trap reactions in an incomplete non-equilibrium state. We present

Sabri Boughorbel, Fethi Jarray, Abdulaziz Al Homaid, Rashid Niaz

Language modeling have shown impressive progress in generating compelling text with good accuracy and high semantic coherence. An interesting research direction is to augment these powerful models for specific applications using contextual information. In this work, we explore multi-modal language modeling for healthcare applications. We are interested in ou

Sandip Das, Koushik Kumar Dey, Pavan P D, Sagnik Sen

An oriented graph has weak diameter at most $d$ if every non-adjacent pair of vertices are connected by a directed $d$-path. The function $f_d(n)$ denotes the minimum number of arcs in an oriented graph on $n$ vertices having weak diameter $d$. Finding the exact value of $f_d(n)$ is a challenging problem even for $d = 2$. This function was introduced by Kato

Aayush Kumar Tyagi, Chirag Mohapatra, Prasenjit Das, Govind Makharia

Multi-class cell detection and counting is an essential task for many pathological diagnoses. Manual counting is tedious and often leads to inter-observer variations among pathologists. While there exist multiple, general-purpose, deep learning-based object detection and counting methods, they may not readily transfer to detecting and counting cells in medic

Evan Hernandez, Belinda Z. Li, Jacob Andreas

Neural language models (LMs) represent facts about the world described by text. Sometimes these facts derive from training data (in most LMs, a representation of the word "banana" encodes the fact that bananas are fruits). Sometimes facts derive from input text itself (a representation of the sentence "I poured out the bottle" encodes the fact that the bottl

Qianyong Wu, Jiang Hu

The paper discusses a statistical problem related to testing for differences between two sparse networks with community structures. The community-wise edge probability matrices have entries of order $O(n^{-1}/\log n)$, where $n$ represents the size of the network. The authors propose a test statistic that combines a method proposed by Wu et al. \cite{WuTwoSa

Thomas Lu, Albert Lu, Hiu Yung Wong

This paper demonstrates the learning of the underlying device physics by mapping device structure images to their corresponding Current-Voltage (IV) characteristics using a novel framework based on variational autoencoders (VAE). Since VAE is used, domain expertise is not required and the framework can be quickly deployed on any new device and measurement. T

Minjun Zhao, Yichen Yin, Yuren Mao, Qing Liu

Top-k sparsification has recently been widely used to reduce the communication volume in distributed deep learning. However, due to the Sparse Gradient Accumulation (SGA) dilemma, the performance of top-k sparsification still has limitations. Recently, a few methods have been put forward to handle the SGA dilemma. Regrettably, even the state-of-the-art metho

Linhan Yang, Bidan Huang, Qingbiao Li, Ya-Yen Tsai

In this paper, we propose a novel framework for tactile-based dexterous manipulation learning with a blind anthropomorphic robotic hand, i.e. without visual sensing. First, object-related states were extracted from the raw tactile signals by a graph-based perception model - TacGNN. The resulting tactile features were then utilized in the policy learning of a

Jiaojian Shi, Yuejun Shen, Feng Pan, Weiwei Sun

The development of many optical quantum technologies depends on the availability of solid-state single quantum emitters with near-perfect optical coherence. However, a standing issue that limits systematic improvement is the significant sample heterogeneity and lack of mechanistic understanding of microscopic energy flow at the single emitter level and ultra

Richard Howl, Nathan Cooper, Lucia Hackermüller

A promising route to testing quantum gravity in the laboratory is to look for gravitationally-induced entanglement (GIE) between two or more quantum matter systems. Proposals for such tests have principally used microsolid systems, with highly non-classical states, such as N00N states or highly-squeezed states. Here, we consider, for the first time, GIE betw

Sayak Nag, Kyle Min, Subarna Tripathi, Amit K. Roy Chowdhury

The task of dynamic scene graph generation (SGG) from videos is complicated and challenging due to the inherent dynamics of a scene, temporal fluctuation of model predictions, and the long-tailed distribution of the visual relationships in addition to the already existing challenges in image-based SGG. Existing methods for dynamic SGG have primarily focused

Sandeep Manjanna, Tom Z. Jiahao, M. Ani Hsieh

Persistent monitoring of a spatiotemporal fluid process requires data sampling and predictive modeling of the process being monitored. In this paper we present PASST algorithm: Predictive-model based Adaptive Sampling of a Spatio-Temporal process. PASST is an adaptive robotic sampling algorithm that leverages predictive models to efficiently and persistently

Zihao Chen, Xiaomeng Wang, Yuanjiang Huang, Tao Jia

The interpretability of model has become one of the obstacles to its wide application in the high-stake fields. The usual way to obtain interpretability is to build a black-box first and then explain it using the post-hoc methods. However, the explanations provided by the post-hoc method are not always reliable. Instead, we design an intrinsically interpreta

A. U. Abeysekara, A. Albert, R. Alfaro, C. Álvarez

The High-Altitude Water Cherenkov (HAWC) observatory is a second-generation continuously operated, wide field-of-view, TeV gamma-ray observatory. The HAWC observatory and its analysis techniques build on experience of the Milagro experiment in using ground-based water Cherenkov detectors for gamma-ray astronomy. HAWC is located on the Sierra Negra volcano in

Yu Chen, Chao Shang, Xiaolin Huang, Xiang Yin

In this work, we investigate the data-driven safe control synthesis problem for unknown dynamic systems. We first formulate the safety synthesis problem as a robust convex program (RCP) based on notion of control barrier function. To resolve the issue of unknown system dynamic, we follow the existing approach by converting the RCP to a scenario convex progra

Güray Hatipoğlu

This manuscript reports a part of a dedicated study aiming to disentangle sources of signals from James Webb Space Telescope (JWST) Mid-Infrared Instrument (MIRI) imaging mode. An instrumental introduction and characteristics section is present regarding MIRI. Later, a Fast Fourier Transformation-based filtering approach and its results will be discussed.

Linnéa Gyllingberg, Alex Szorkovszky, David J. T. Sumpter

While mathematical models, in particular self-propelled particle (SPP) models, capture many of the observed properties of large fish schools, they do not always capture the interactions of smaller shoals. Nor do these models tend to account for the observation that, when swimming alone or in smaller groups, many species of fish use intermittent locomotion, o

Subhankar Mondal

This paper deals with the problem of identification of a Robin coefficient (also known as impedance coefficient) in a parabolic PDE from terminal observations of the temperature distributions. The problem is ill-posed in the sense that small perturbation in the observation may lead to a large deviation in the solution. Thus, in order to obtain stable approxi