November 2022 arXiv papers — page 46

Eric Bezzam, Martin Vetterli, Matthieu Simeoni

Lensless imaging can provide visual privacy due to the highly multiplexed characteristic of its measurements. However, this alone is a weak form of security, as various adversarial attacks can be designed to invert the one-to-many scene mapping of such cameras. In this work, we enhance the privacy provided by lensless imaging by (1) downsampling at the senso

Shosei Takeda

Takeda-Yano determined the limit of L\'{e}vy processes conditioned to avoid zero via various random clocks in terms of Doob's $h$-transform, where the limit processes may differ according to the choice of random clocks. The purpose of this paper is to investigate sample path behaviors of the limit processes in long time and in short time.

Ildikó Schlotter, András Sebő

Minimizing the weight of an edge set satisfying parity constraints is a challenging branch of combinatorial optimization as witnessed by the binary hypergraph chapter of Alexander Schrijver's book ``Combinatorial Optimization" (Chapter 80). This area contains relevant graph theory problems including open cases of the Max Cut problem and some multiflow proble

Rahma Yasmina Moulay Hachemi, Bernt Øksendal

We study the time-fractional stochastic heat equation driven by time-space white noise with space dimension $d\in\mathbb{N}=\{1,2,...\}$ and the fractional time-derivative is the Caputo derivative of order $\alpha \in (0,2)$. We consider the equation in the sense of distribution, and we find an explicit expression for the $\mathcal{S}'$-valued solution $Y(t,

Md Sakib Nizam Khan, Niklas Reje, Sonja Buchegger

Big data analysis poses the dual problem of privacy preservation and utility, i.e., how accurate data analyses remain after transforming original data in order to protect the privacy of the individuals that the data is about - and whether they are accurate enough to be meaningful. In this paper, we thus investigate across several datasets whether different m

Leonid Iosipoi, Anton Vakhrushev

Gradient Boosted Decision Tree (GBDT) is a widely-used machine learning algorithm that has been shown to achieve state-of-the-art results on many standard data science problems. We are interested in its application to multioutput problems when the output is highly multidimensional. Although there are highly effective GBDT implementations, their scalability t

Gregor Mendel

Mendel performed his experiments from 1856 and 1863, presented his results in two meetings of the Natural Science Society in Brunn in February and March of 1865, and finally published them in the iconical paper of 1866, Versuche uber Plflanzenhybriden. Two main translations to Spanish are available: the one done by Prevosti in 1977, and a more recent one by

Olof Bergvall

We determine the number of Del Pezzo surfaces of degree 2 over finite fields of odd characteristic with specified action of the Frobenius endomorphism, i.e. we solve the "quantitative inverse Galois problem". As applications we determine the number of Del Pezzo surfaces of degree 2 with a given number of points and recover results of Banwait-Fit\'e-Loughran

Peng Wang, Lingzhe Zhao, Ruijie Ma, Peidong Liu

Neural Radiance Fields (NeRF) have received considerable attention recently, due to its impressive capability in photo-realistic 3D reconstruction and novel view synthesis, given a set of posed camera images. Earlier work usually assumes the input images are of good quality. However, image degradation (e.g. image motion blur in low-light conditions) can easi

Nicholas Thomas Walker, Stefan Ultes, Pierre Lison

We present a new approach to dialogue management using conversational knowledge graphs as core representation of the dialogue state. To this end, we introduce a new dataset, GraphWOZ, which comprises Wizard-of-Oz dialogues in which human participants interact with a robot acting as a receptionist. In contrast to most existing work on dialogue management, Gra

Giuseppe L'Erario, Gabriele Nava, Giulio Romualdi, Fabio Bergonti

The general problem of planning feasible trajectories for multimodal robots is still an open challenge. This paper presents a whole-body trajectory optimisation approach that addresses this challenge by combining methods and tools developed for aerial and legged robots. First, robot models that enable the presented whole-body trajectory optimisation framewor

J. Veerababu, G. Sainath, A. Nagesh

Understanding the grain boundary deformation dynamics is very crucial to designing materials with stable microstructures. With this quest, the deformation behavior of coherent twin boundary under cyclic shear loading has been studied in {\alpha}-Fe using molecular dynamics simulations to understand the influence of strain amplitude and temperature. Twin boun

L. Ts. Adzhemyan, A. Kudlis

The stability of $O(n)$-symmetric fixed point regarding the presence of vector-field term ($\sim h p_{\alpha}p_{\beta}$) in the $\varphi^4$ field theory is analyzed. For this purpose, the four-loop renormalization group expansions in $d=4-2\varepsilon$ within Minimal Subtraction (MS) scheme are obtained. This frequently neglected term in the action requires

Hong Gao

Virtual reality (VR) is not a new technology but has been in development for decades, driven by advances in computer technology. Currently, VR technology is increasingly being used in applications to enable immersive, yet controlled research settings. Education and entertainment are two important application areas, where VR has been considered a key enabler

Juan Casado, Yasser Hendy

A primordial group of open clusters containing NGC 6871 is confirmed and described through Gaia DR3 data and the previous literature. It is a star-forming complex containing at least six young OCs, including Teutsch 8, FSR 198 and Biurakan 2. Two nearby OCs (Casado 82 and Casado-Hendy 1) are newly identified and studied in detail and found to be also members

Maria Axenovich

Let $ex(Q_n, H)$ be the largest number of edges in a subgraph $G$ of a hypercube $Q_n$ such that there is no subgraph of $G$ isomorphic to $H$. We show that for any integer $k\geq 3$, $$ex(Q_n, C_{4k+2})= O(n^{\frac{5}{6} + \frac{1}{3(2k-2)}} 2^n).$$

Krystal Guo, Vincent Schmeits

A discrete-time quantum walk is the quantum analogue of a Markov chain on a graph. Zhan [J. Algebraic Combin. 53(4):1187-1213, 2020] proposes a model of discrete-time quantum walk whose transition matrix is given by two reflections, using the face and vertex incidence relations of a graph embedded in an orientable surface. We show that the evolution of a gen

Betul Uysal, Tilman Hartwig

Several studies have shown the influence of the relative streaming velocity (SV) between baryons and dark matter on the formation of structures. For the first time, we constrain the local value of the SV in which the Milky Way was formed. We use the semi-analytical model A-SLOTH to simulate the formation of Milky Way-like galaxies. The high resolution in mas

Jérémie Guilhot, Cédric Lecouvey, Pierre Tarrago

We study a class of commuting Markov kernels whose simplest element describes the movement of $k$ particles on a discrete circle of size $n$ conditioned to not intersect each other. Such Markov kernels are related to the quantum cohomology ring of the Grassmannian, which is an algebraic object counting analytic maps from $\mathbb{P}^1(\mathbb{C})$ to the Gra

Kumar Shridhar, Jakub Macina, Mennatallah El-Assady, Tanmay Sinha

Socratic questioning is an educational method that allows students to discover answers to complex problems by asking them a series of thoughtful questions. Generation of didactically sound questions is challenging, requiring understanding of the reasoning process involved in the problem. We hypothesize that such questioning strategy can not only enhance the

Hae-Ryong Park, Kyung-Yong Park, Kyoung-Min Kim, Jun-Sung Kim

The Anderson transition of Bogoliubov-de Gennes (BdG) quasiparticles in superconducting state has been studied theoretically for last three decades. However, its experimental proof is lacking. In particular, the relationship of the superconducting order-parameter fluctuations and the Anderson transition of BdG quasiparticles have not been well understood. Ou

Amir Abboud, Nathan Wallheimer

In recent years, the expander decomposition method was used to develop many graph algorithms, resulting in major improvements to longstanding complexity barriers. This powerful hammer has led the community to (1) believe that most problems are as easy on worst-case graphs as they are on expanders, and (2) suspect that expander decompositions are the key to b

Xiao Jiang, Zean Tian, Kenli Li

Understanding the dynamic processes of the glassy system continues to be challenging. Recent advances have shown the power of graph neural networks (GNNs) for determining the correlation between structure and dynamics in the glassy system. These methods treat the glassy system as a topological graph. However, the inherent "smoothness" property of the dynamic

Elisa Varani

In general relativity the affine connection is required to be symmetric so torsion is zero while according to the Einsten- Cartan's theory torsion is connected to the spin tensor as expressed by the Cartan's equations. We consider the theory of spinors in general relativity in the light of the results of Einstein Cartan's theory.In general relativity the aff

Mourad Choulli

We establish that the potential appearing in a fractional Schr\"odinger operator is uniquely determined by an internal spectral data.

Sina Honari, Chen Zhao, Mathieu Salzmann, Pascal Fua

Analyzing and training 3D body posture models depend heavily on the availability of joint labels that are commonly acquired through laborious manual annotation of body joints or via marker-based joint localization using carefully curated markers and capturing systems. However, such annotations are not always available, especially for people performing unusua

Qian Liang, Xuekai Ma, Teng Long, Jiannian Yao

Organic circularly polarized (CP) lasers have received increasing attention due to their future photoelectric applications. Here, we demonstrate a CP laser from a pure organic crystal-filled microcavity without any chiral molecules or chiral structures. Benefited from the giant anisotropy and excellent laser gain of organic crystals, optical Rashba-Dresselha

Zhenghao Xing, Tianyu Wang, Xiaowei Hu, Haoran Wu

Instance shadow detection, crucial for applications such as photo editing and light direction estimation, has undergone significant advancements in predicting shadow instances, object instances, and their associations. The extension of this task to videos presents challenges in annotating diverse video data and addressing complexities arising from occlusion

Nico Messikommer, Carter Fang, Mathias Gehrig, Giovanni Cioffi

Because of their high temporal resolution, increased resilience to motion blur, and very sparse output, event cameras have been shown to be ideal for low-latency and low-bandwidth feature tracking, even in challenging scenarios. Existing feature tracking methods for event cameras are either handcrafted or derived from first principles but require extensive p

Beili Ying, Alessandro Bemporad, Li Feng, Nariaki V. Nitta

Stealthy Coronal Mass Ejections (CMEs), lacking low coronal signatures, may result in significant geomagnetic storms. However, the mechanism of stealthy CMEs is still highly debated. In this work, we investigate whether there are differences between the stealthy and standard CMEs in terms of their dynamic behaviors. Seven stealthy and eight standard CMEs wit

Tsu-Jui Fu, Licheng Yu, Ning Zhang, Cheng-Yang Fu

Generating a video given the first several static frames is challenging as it anticipates reasonable future frames with temporal coherence. Besides video prediction, the ability to rewind from the last frame or infilling between the head and tail is also crucial, but they have rarely been explored for video completion. Since there could be different outcomes

Vincent Laude, Yan-Feng Wang

Open phononic systems including resonators radiating inside an unbounded medium support localized phonons characterized by a complex frequency. In this context, the concept of elastic quasinormal mode (QNM) arises naturally, as in the cases of nanophotonic and plasmonic open systems. Based on a complex, unconjugated form of reciprocity theorem for elastodyna

Daniela Di Donato

In this paper, we analyze the 'symmetrized' of the intrinsic Hopf-Lax semigroup introduced by the author in the context of the intrinsically Lipschitz sections in the setting of metric spaces. Indeed, in the usual case, we have that $d(x,y) =d(y,x)$ for any point $x$ and $y$ belong to the metric space $X$; on the other hand, in our intrinsic context, we have

Ahmad Haji Mohammadkhani, Chakkrit Tantithamthavorn, Hadi Hemmati

In recent years, there has been a wide interest in designing deep neural network-based models that automate downstream software engineering tasks on source code, such as code document generation, code search, and program repair. Although the main objective of these studies is to improve the effectiveness of the downstream task, many studies only attempt to e

Kunal Relia

Fairness in multiwinner elections is studied in varying contexts. For instance, diversity of candidates and representation of voters are both separately termed as being fair. A common denominator to ensure fairness across all such contexts is the use of constraints. However, across these contexts, the candidates selected to satisfy the given constraints may

Xin Li, Xuli Tang, Wei Lu

Keeping track of translational research is essential to evaluating the performance of programs on translational medicine. Despite several indicators in previous studies, a consensus measure is still needed to represent the translational features of biomedical research at the article level. In this study, we first trained semantic representations of biomedica

Matteo Dalla Riva, Riccardo Molinarolo, Paolo Musolino

We consider the Laplace equation in a domain of $\mathbb{R}^n$, $n\ge 3$, with a small inclusion of size $\epsilon$. On the boundary of the inclusion we define a nonlinear nonautonomous transmission condition. For $\epsilon$ small enough one can prove that the problem has solutions. In this paper, we study the local uniqueness of such solutions.

Xiao Liu, Soumick Sarker, Ankur Sikarwar, Bryan Atista Kiely

Humans rarely perceive objects in isolation but interpret scenes through relationships among co-occurring elements. How such contextual knowledge is acquired without explicit supervision remains unclear. Here we combine human psychophysics experiments with computational modelling to study the emergence of contextual reasoning. Participants were exposed to no

Thiago de Paiva

A positive braid with at least one full twist is known to be a minimal braid, i.e, it achieves the braid index for its closure. In this paper we find knots that are the closure of positive minimal braids that cannot be represented by positive braids with full twists. More precisely, we show that some satellite knots with companions and patterns given as the

P. L. Krapivsky, J. M. Luck

The Ising chain with kinetic constraints provides many examples of totally irreversible zero-temperature dynamics leading to metastability with an exponentially large number of attractors. In most cases, the constrained zero-temperature dynamics can be mapped onto a model of random sequential adsorption. We provide a brief didactic review, based on the examp

Yang Liu, Yan Kang, Tianyuan Zou, Yanhong Pu

Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with different features about the same set of users jointly train machine learning models without exposing their raw data or model parameters. Motivated by the rapid growth in VFL research and real-world applications, we provide a comprehensive review of the concept and

Hugo Carneiro, Cornelius Weber, Stefan Wermter

The task of emotion recognition in conversations (ERC) benefits from the availability of multiple modalities, as provided, for example, in the video-based Multimodal EmotionLines Dataset (MELD). However, only a few research approaches use both acoustic and visual information from the MELD videos. There are two reasons for this: First, label-to-video alignmen

Annayat Ali, Rameez Raja

For any two non-negative integers h and k, h > k, an L(h, k)-colouring of a graph G is a colouring of vertices such that adjacent vertices admit colours that at least differ by h and vertices that are two distances apart admit colours that at least differ by k. The smallest positive integer {\delta} such that G permits an L(h, k)-colouring with maximum colou

G. Barajas, O. García-Prada

Let $X$ be a compact Riemann surface and $G$ be a connected reductive complex Lie group with centre $Z$. Consider the moduli space $M(X,G)$ of polystable principal holomorphic $G$-bundles on $X$. There is an action of the group $H^1(X,Z)$ of isomorphism classes of $Z$-bundles over $X$ on $M(X,G)$ induced by the multiplication $Z\times G\to G.$ Let $\Gamma$ b

Davide Bigoni, Federico Bosi, Francesco Dal Corso, Diego Misseroni

The discovery of configurational forces acting on elastic structures and its initial applications are reviewed. Configurational forces are related to the possibility that an elastic structure can change its configuration, thus inducing a variation in the potential energy. This concept has already led to several applications (the elastica arm scale, the dripp

Jinglei Xu, Qi Li, Xianxu Yuan, Lin Bi

Kolmogorov's (1941) theory of self-similarity implies the universality of small-scale eddies, and holds promise for a universal sub-grid scale model for large eddy simulation. The fact is the empirical coefficient of a typical sub-grid scale model varies from 0.1 to 0.2 in free turbulence and damps gradually to zero approaching the walls. This work has devel

J. A. Barkai, M. A. W. Verheijen, E. T. Martínez, M. H. F. Wilkinson

The 21 cm spectral line emission of atomic neutral hydrogen (HI) is one of the primary wavelengths observed in radio astronomy. However, the signal is intrinsically faint and the HI content of galaxies depends on the cosmic environment, requiring large survey volumes and survey depth to investigate the HI Universe. As the amount of data coming from these sur

Pinku Routray, H. C. Das, Souhardya Sen, Bharat Kumar

Within the relativistic mean-field model, we investigate the properties of dark matter (DM) admixed neutron stars, considering non-rotating objects made of isotropic matter. We adopt the IOPB-I hadronic equation of state (EOS) by assuming that the fermionic DM within super-symmetric models has already been accreted inside the neutron star (NS). The impact of

Johanna Bürger, Thilo Glißmann, Anthony Lethuillier, Dorothea Bischoff

Optical properties are required for the correct understanding and modelling of protoplanetary and debris discs. By assuming that comets are the most pristine bodies in the solar system, our goal is to derive optical constants of real protoplanetary material. We determine the complex index of refraction of the near-surface material of comet 67P/Churyumov-Gera

Andrei Mandelshtam

Ulam words are binary words defined recursively as follows: the length-$1$ Ulam words are $0$ and $1$, and a binary word of length $n$ is Ulam if and only if it is expressible uniquely as a concatenation of two shorter, distinct Ulam words. We discover, fully describe, and prove a surprisingly rich structure already in the set of Ulam words containing exactl

David Albandea, Luigi Del Debbio, Pilar Hernández, Richard Kenway

The recent introduction of machine learning techniques, especially normalizing flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling efficiency of the traditional HMC algorithm. Naive use of normalizing flows has been shown to lead to bad scaling with the volume. In this talk we propose using local normalizing flows a

Yu Chen, Shaoyuan Li, Xiang Yin

We investigate the problem of synthesizing optimal control policies for Markov decision processes (MDPs) with both qualitative and quantitative objectives. Specifically, our goal is to achieve a given linear temporal logic (LTL) task with probability one, while maximizing the \emph{entropy rate} of the system. The notion of entropy rate characterizes the lon

Roberto Rubboli, Marco Tomamichel

We prove that the relative entropy of entanglement is additive when \emph{at least one of the two states} belongs to some specific class. We show that these classes include bipartite pure, maximally correlated, GHZ, Bell diagonal, isotropic, and generalized Dicke states. Previously, additivity was established only if \textit{both} states belong to the same c

Yu Chen, Shuo Yang, Rahul Mangharam, Xiang Yin

In this paper, we investigate the problem of synthesizing controllers for temporal logic specifications under security constraint. We assume that there exists a passive intruder (eavesdropper) that can partially observe the behavior of the system. For the purpose of security, we require that the system's behaviors are unpredictable in the sense that the intr

Panu Lahti

We introduce a relaxed version of the metric definition of quasiconformality that is natural also for mappings of low regularity, including $W_{\mathrm{loc}}^{1,1}(\mathbb{R}^n;\mathbb{R}^n)$-mappings. Then we show on the plane that this relaxed definition can be used to prove Sobolev regularity, and that these ``finely quasiconformal'' mappings are in fact

Christoffer Olsson, Stephan Wagner

We study the size of the automorphism group of two different types of random trees: Galton--Watson trees and rooted P\'olya trees. In both cases, we prove that it asymptotically follows a log-normal distribution and provide asymptotic formulas for mean and variance of the logarithm of the size of the automorphism group. While the proof for Galton--Watson tre

Antonio Amariti, Simone Rota

We discuss and reinterpret a 4d conformal triality recently discovered in the literature in terms of ordinary Seiberg duality. We observe that a non-abelian global symmetry is explicitly realized by only two out of the three phase. We corroborate the result by matching the superconformal index in terms of an expansion on the fugacities.

Juan Cruz Viotti, Mital Kinderkhedia

In this paper, we present benchmark results for a pre-production implementation of a novel serialization specification: JSON BinPack. JSON BinPack is a schema-driven and schema-less sequential binary serialization specification based on JSON Schema. It is rich in diverse encodings, and is developed to improve network performance and reduce the operational co

Fabio Sauli

A method is proposed to dump the spurious signals induced by fluorescence of the electrodes in gaseous detectors under strong X-Ray irradiation, introducing a special fluorescence suppressor electrode between the sensitive and the amplifying parts of the detector.

Wenbin Gan, Minh-Son Dao, Koji Zettsu

Driver reaction is of vital importance in risk scenarios. Drivers can take correct evasive maneuver at proper cushion time to avoid the potential traffic crashes, but this reaction process is highly experience-dependent and requires various levels of driving skills. To improve driving safety and avoid the traffic accidents, it is necessary to provide all roa

Tanausú del Pino Alemán, Ernest Alsina Ballester, Javier Trujillo Bueno

We study the circular polarization of the Mn I resonance lines at 279.56, 279.91, and 280.19 nm (hereafter, UV multiplet) by means of radiative transfer modeling. In 2019, the CLASP2 mission obtained unprecedented spectropolarimetric data in a region of the solar ultraviolet including the Mg II h and k resonance lines and two lines of a subordinate triplet,

Deepa P Gopinath, Thennal D K, Vrinda V Nair, Swaraj K S

Modern text-to-speech (TTS) systems use deep learning to synthesize speech increasingly approaching human quality, but they require a database of high quality audio-text sentence pairs for training. Malayalam, the official language of the Indian state of Kerala and spoken by 35+ million people, is a low resource language in terms of available corpora for TTS

Bence Horváth, Niels Jakob Laustsen

Let~$\mathcal{A}$ be an almost disjoint family of subsets of an infinite set~$\Gamma$, and denote by~$X_{\mathcal{A}}$ the closed subspace of~$\ell_\infty(\Gamma)$ spanned by the indicator functions of intersections of finitely many sets in~$\mathcal{A}$. We show that if~$\mathcal{A}$ has cardinality greater than~$\Gamma$, then the closed subspace of~$X_{\ma

Diego Misseroni, Phanisri P. Pratapa, Ke Liu, Glaucio H. Paulino

Origami metamaterials are known to display highly tunable Poisson's ratio values depending on their folded state. Most studies on the Poisson effects in deployable origami tessellations are restricted to theory and simulation. Experimental realization of the desired Poisson effects in origami metamaterials requires special attention to the boundary condition

Nikolaos I. Miridakis, Theodoros A. Tsiftsis, Rugui Yao

A multiple-input multiple-output wireless communication system is analytically studied, which operates with the aid of a large-scale reconfigurable intelligent surface (LRIS). LRIS is equipped with multiple passive elements with discrete phase adjustment capabilities, and independent Rician fading conditions are assumed for both the transmitter-to-LRIS and L

Juan Han, Liqiao Yang, Kit Ian Kou, Jifei Miao

Matrix completion is one of the most challenging problems in computer vision. Recently, quaternion representations of color images have achieved competitive performance in many fields. Because it treats the color image as a whole, the coupling information between the three channels of the color image is better utilized. Due to this, low-rank quaternion matri

Xinyu Fu, Irwin King

Heterogeneous graph neural networks (HGNNs) were proposed for representation learning on structural data with multiple types of nodes and edges. To deal with the performance degradation issue when HGNNs become deep, researchers combine metapaths into HGNNs to associate nodes closely related in semantics but far apart in the graph. However, existing metapath-

Yusong Wang, Shaoning Li, Zun Wang, Xinheng He

In the technical report, we provide our solution for OGB-LSC 2022 Graph Regression Task. The target of this task is to predict the quantum chemical property, HOMO-LUMO gap for a given molecule on PCQM4Mv2 dataset. In the competition, we designed two kinds of models: Transformer-M-ViSNet which is an geometry-enhanced graph neural network for fully connected m

Sebastiano Carpi, Tiziano Gaudio, Luca Giorgetti, Robin Hillier

We prove that a haploid associative algebra in a $C^*$-tensor category $\mathcal{C}$ is equivalent to a Q-system (a special $C^*$-Frobenius algebra) in $\mathcal{C}$ if and only if it is rigid. This allows us to prove the unitarity of all the 70 strongly rational holomorphic vertex operator algebras with central charge $c=24$ and non-zero weight-one subspace

Giorgio Picci, Lucia Falconi, Augusto Ferrante, Mattia Zorzi

This paper deals with the estimation of the hidden factor in Dynamic Generalized Factor Analysis via a generalization of Kalman filtering. Asymptotic consistency is discussed and it is shown that the Kalman one-step predictor is not the right tool while the pure filter yields a consistent estimate.

Deshui Yu, Jingbiao Chen, Shougang Zhang

The quantum entanglement enables the precision measurement and frequency metrology beyond the standard quantum limit that is imposed by the quantum projection noise and photon shot noise. Here we propose employing the entangled atoms in the synchronous differential measurement to enhance the sensitivity of the spatial-shift detection. Two ways of engineering

Xiang Gao, Yannic Noller, Abhik Roychoudhury

Automated program repair is an emerging technology which consists of a suite of techniques to automatically fix bugs or vulnerabilities in programs. In this paper, we present a comprehensive survey of the state of the art in program repair. We first study the different suite of techniques used including search based repair, constraint based repair and learni

Ketan Fatania, Kwai Y. Chau, Carolin M. Pirkl, Marion I. Menzel

Current state-of-the-art reconstruction for quantitative tissue maps from fast, compressive, Magnetic Resonance Fingerprinting (MRF), use supervised deep learning, with the drawback of requiring high-fidelity ground truth tissue map training data which is limited. This paper proposes NonLinear Equivariant Imaging (NLEI), a self-supervised learning approach t

Martin Storath, Andreas Weinmann

Smoothing splines are twice differentiable by construction, so they cannot capture potential discontinuities in the underlying signal. In this work, we consider a special case of the weak rod model of Blake and Zisserman (1987) that allows for discontinuities penalizing their number by a linear term. The corresponding estimates are cubic smoothing splines wi

Ali Krayani

Cognitive Radio (CR) is a paradigm shift in wireless communications to resolve the spectrum scarcity issue with the ability to self-organize, self-plan and self-regulate. On the other hand, wireless devices that can learn from their environment can also be taught things by malicious elements of their environment, and hence, malicious attacks are a great conc

Jiacheng Wang, Hongyang Du, Zengshan Tian, Dusit Niyato

With the advancement of network and computer technologies, virtual cyberspace keeps evolving, and Metaverse is the main representative. As an irreplaceable technology that supports Metaverse, the sensing information transmission from the physical world to Metaverse is vital. Inspired by emerging semantic communication, in this paper, we propose a semantic tr

Xingyu Chen, Baoyuan Wang, Heung-Yeung Shum

We present HandAvatar, a novel representation for hand animation and rendering, which can generate smoothly compositional geometry and self-occlusion-aware texture. Specifically, we first develop a MANO-HD model as a high-resolution mesh topology to fit personalized hand shapes. Sequentially, we decompose hand geometry into per-bone rigid parts, and then re-

Zhijun Wang, Xuebo Liu, Min Zhang

Existing research generally treats Chinese character as a minimum unit for representation. However, such Chinese character representation will suffer two bottlenecks: 1) Learning bottleneck, the learning cannot benefit from its rich internal features (e.g., radicals and strokes); and 2) Parameter bottleneck, each individual character has to be represented by

Antonio C. Gutiérrez-Piñeres

In this work, we compute the metric corresponding to a static and spherically symmetric mass distribution in the general relativistic weak field approximation to quadratic order in Fermi-normal coordinates surrounding a radial geodesic. To construct a geodesic and a convenient tetrad transported along it, we first introduce a general metric, use the Cartan f

Wen Ning, Ri-Hua Zheng, Yan Xia, Kai Xu

Although originally predicted in relativistic quantum mechanics, Zitterbewegung can also appear in some classical systems, which leads to the important question of whether Zitterbewegung of Dirac particles is underlain by a more fundamental and universal interference behavior without classical analogs. We here reveal such an interference pattern in phase spa

Wenbin Gan, Minh-Son Dao, Koji Zettsu

Sleep plays a vital role in our physical, cognitive, and psychological well-being. Despite its importance, long-term monitoring of personalized sleep quality (SQ) in real-world contexts is still challenging. Many sleep researches are still developing clinically and far from accessible to the general public. Fortunately, wearables and IoT devices provide the

Yang Li, Guijin Wang, Zhourui Xia, Wenming Yang

Auxiliary diagnosis of cardiac electrophysiological status can be obtained through the analysis of 12-lead electrocardiograms (ECGs). This work proposes a dual-scale lead-separated transformer with lead-orthogonal attention and meta-information (DLTM-ECG) as a novel approach to address this challenge. ECG segments of each lead are interpreted as independent

Huihui Wu

Aiming at the limitation that deep long and short-term memory network(DLSTM) algorithm cannot perform parallel computing and cannot obtain global information, in this paper, feature extraction and feature processing are firstly carried out according to the characteristics of eye movement data and tracking data, then by introducing a convolutional neural netw

Jiaqi Hu, Junning Li, Yanling Lin, Hanlin Long

Quantum chemistry is one of the most promising applications of quantum computers in the near future. For noisy intermediate-scale quantum devices, the quantum-classical hybrid framework based on the variational quantum eigensolver (VQE) has become the method of choice. In the literature, there are many different variants of VQE, but it is not known which one

Junjie Wang, Yao Mu, Dong Li, Qichao Zhang

The latent world model provides a promising way to learn policies in a compact latent space for tasks with high-dimensional observations, however, its generalization across diverse environments with unseen dynamics remains challenging. Although the recurrent structure utilized in current advances helps to capture local dynamics, modeling only state transitio

Xiang Gao, Weihao Gao, Wenzhi Xiao, Zhirui Wang

Machine learning has become a promising approach for molecular modeling. Positional quantities, such as interatomic distances and bond angles, play a crucial role in molecule physics. The existing works rely on careful manual design of their representation. To model the complex nonlinearity in predicting molecular properties in an more end-to-end approach, w

Pierre Chantelot, Detlef Lohse

Ambient air cushions the impact of drops on solid substrates, an effect usually revealed by the entrainment of a bubble, trapped as the air squeezed under the drop drains and liquid-solid contact occurs. The presence of air becomes evident for impacts on very smooth surfaces, where the gas film can be sustained, allowing drops to bounce without wetting the s

Payel Sadhukhan, Sarbani palit, Kausik Sengupta

The relevance of machine learning (ML) in our daily lives is closely intertwined with its explainability. Explainability can allow end-users to have a transparent and humane reckoning of a ML scheme's capability and utility. It will also foster the user's confidence in the automated decisions of a system. Explaining the variables or features to explain a mod

Avik Roy, Mark S. Neubauer

Multivariate techniques and machine learning models have found numerous applications in High Energy Physics (HEP) research over many years. In recent times, AI models based on deep neural networks are becoming increasingly popular for many of these applications. However, neural networks are regarded as black boxes -- because of their high degree of complexit

Neha Sangwan, Mayank Bakshi, Bikash Kumar Dey, Vinod M. Prabhakaran

We study communication over a Multiple Access Channel (MAC) where users can possibly be adversarial. The receiver is unaware of the identity of the adversarial users (if any). When all users are non-adversarial, we want their messages to be decoded reliably. When a user behaves adversarially, we require that the honest users' messages be decoded reliably. An

Xiang Gao, Weihao Gao, Wenzhi Xiao, Zhirui Wang

Machine learning approaches have become popular for molecular modeling tasks, including molecular force fields and properties prediction. Traditional supervised learning methods suffer from scarcity of labeled data for particular tasks, motivating the use of large-scale dataset for other relevant tasks. We propose to pretrain neural networks on a dataset of

Luca Marchetti, Daniele Oriti, Andreas G. A. Pithis, Johannes Thürigen

Controlling the continuum limit and extracting effective gravitational physics are shared challenges for quantum gravity approaches based on quantum discrete structures. The description of quantum gravity in terms of tensorial group field theory (TGFT) has recently led to much progress in its application to phenomenology, in particular cosmology. This applic

Théophile Berteloot, Richard Khoury, Audrey Durand

Association rule mining is one of the most studied research fields of data mining, with applications ranging from grocery basket problems to highly explainable classification systems. Classical association rule mining algorithms have several flaws especially with regards to their execution times, memory usage and number of rules produced. An alternative is t

Atsuhisa Ota, Misao Sasaki, Yi Wang

We present a consistent one-loop calculation for the inflationary tensor power spectrum in the presence of an excited spectator scalar field using the in-in formalism. We find that the super-horizon primordial power spectrum of the tensor mode can be scale-invariantly enhanced or reduced by the loop effects of a subhorizon scalar field. Our calculation also

Xiao Zhang, Min Meng, Zhengping Ji

The control properties of discrete-time switched linear systems (SLS) with switching signals generated by logical dynamic systems are studied using the semi-tensor product (STP) approach. With the algebraic state space representation (ASSR), the linear modes and the logical generators are aggregated as a hybrid system, leading to the criteria of reachability

Siteng Huang, Biao Gong, Yulin Pan, Jianwen Jiang

Many recent studies leverage the pre-trained CLIP for text-video cross-modal retrieval by tuning the backbone with additional heavy modules, which not only brings huge computational burdens with much more parameters, but also leads to the knowledge forgetting from upstream models. In this work, we propose the VoP: Text-Video Co-operative Prompt Tuning for ef

Promod Sharma, M. K. Vemuri

Inductive algebras for a compact group are self-adjoint

M. N. Akhter, S. B. Ivars, M. Botey, R. Herrero

We show that the simultaneous modulation of the propagation constant and of the gain/loss coefficient along the multimode fibers results in unidirectional coupling among the modes, which, depending on the modulation parameters, leads to the enhancement or reduction of the excitation of higher order transverse modes. In the latter case, effective mode-cleanin

Quoc Anh Tran, Gustav Grimstad, Seyed Ali Ghoreishian Amiri

In this paper, we describe a soil-fluid-structure interaction model that combines soil mechanics (saturated sediments), fluid mechanics (seawater or air), and solid mechanics (structures). The formulation combines the Material Point Method, which models large deformation of the porous media and the structure, with the Implicit Continuous-fluid Eulerian, whic

Konstantin Kobs, Michael Steininger, Andreas Hotho

Common Deep Metric Learning (DML) datasets specify only one notion of similarity, e.g., two images in the Cars196 dataset are deemed similar if they show the same car model. We argue that depending on the application, users of image retrieval systems have different and changing similarity notions that should be incorporated as easily as possible. Therefore,