November 2022 arXiv papers — page 107

Huiyuan Man, Alireza Ghasemi, Moein Adnani, Maxime A. Siegler

Little is so far known about the magnetism of the $\rm A_2B_2O_7$ monoclinic layered perovskites that replace the spin-ice supporting pyrochlore structure for $r_A/r_B>1.78$. We show that high quality monoclinic Pr$_2$Ti$_2$O$_7$ single crystals with a three-dimensional network of non-Kramers Pr$^{3+}$ ions that interact through edge-sharing super-exchange i

Simon Welker, Henry N. Chapman, Timo Gerkmann

In this work, we utilize the high-fidelity generation abilities of diffusion models to solve blind JPEG restoration at high compression levels. We propose an elegant modification of the forward stochastic differential equation of diffusion models to adapt them to this restoration task and name our method DriftRec. Comparing DriftRec against an $L_2$ regressi

Stanley S. Coelho, Lucas Queiroz, Danilo T. Alves

Harmonic oscillators with multiple abrupt jumps in their frequencies have been investigated by several authors during the last decades. We investigate the dynamics of a quantum harmonic oscillator with initial frequency $\omega_0$, that undergoes a sudden jump to a frequency $\omega_1$ and, after a certain time interval, suddenly returns to its initial frequ

Michael Greenacre

The approach to analysing compositional data has been dominated by the use of logratio transformations, to ensure exact subcompositional coherence and, in some situations, exact isometry as well. A problem with this approach is that data zeros, found in most applications, have to be replaced to allow the logarithmic transformation. An alternative new approac

Mark Andrea A. de Cataldo, Andres Fernandez Herrero

We show the smoothness over the affine line of the Hodge moduli space of logarithmic t-connections of coprime rank and degree on a smooth projective curve with geometrically integral fibers over an arbitrary Noetherian base. When the base is a field, we also prove that the Hodge moduli space is geometrically integral. Along the way, we prove the same results

Upol Ehsan, Q. Vera Liao, Samir Passi, Mark O. Riedl

Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps. While black-boxing AI systems can make the user experience seamless, hiding the seams risks disempowering users to mitigate fallouts from AI mistakes. Instead of hiding these AI imperfections, can we leverage them to help the user? While Explainable AI (XA

Andreas Vitsos, Konstantinos N. Gourgouliatos

A plausible dark matter candidate is an ultralight bosonic particle referred to as fuzzy dark matter. The equivalent mass-energy of the fuzzy dark matter boson is $\sim 10^{-22}$eV and has a corresponding de Broglie wavelength of kiloparsec scale, thus exhibiting wave behaviour in scales comparable to a galactic core, which could not appear in conventional c

Felix Weitkämper

We generalise the distribution semantics underpinning probabilistic logic programming by distilling its essential concept, the separation of a free random component and a deterministic part. This abstracts the core ideas beyond logic programming as such to encompass frameworks from probabilistic databases, probabilistic finite model theory and discrete lifte

Federico Landini, Mireia Diez, Alicia Lozano-Diez, Lukáš Burget

End-to-end diarization presents an attractive alternative to standard cascaded diarization systems because a single system can handle all aspects of the task at once. Many flavors of end-to-end models have been proposed but all of them require (so far non-existing) large amounts of annotated data for training. The compromise solution consists in generating s

Martin Klazar

We investigate Bertrand's probabilistic paradox through the lens of discrete geometry and old-fashioned but reliable discrete probability. We approximate the plane unit circle with $1/n$ times $1/n$ boxes and count the pairs of boxes separated by distance more than $\sqrt{3}$. For $n\to\infty$ the proportion of such pairs goes to $$ \frac{1+\sqrt{3}}{8}-\fra

Jason R. Wilson

High levels of robot autonomy are a common goal, but there is a significant risk that the greater the autonomy of the robot the lesser the autonomy of the human working with the robot. For vulnerable populations like older adults who already have a diminished level of autonomy, this is an even greater concern. We propose that human autonomy needs to be at th

Alexander Bagnall, Gordon Stewart, Anindya Banerjee

We present Zar: a formally verified compiler pipeline from discrete probabilistic programs with unbounded loops in the conditional probabilistic guarded command language (cpGCL) to proved-correct executable samplers in the random bit model. We exploit the key idea that all discrete probability distributions can be reduced to unbiased coin-flipping schemes. T

Jingda Wu, Dongyang Yang, Jing Liang, Max Werner

Rhombohedrally stacked MoS2 has been shown to exhibit spontaneous polarization down to the bilayer limit and can sustain a strong depolarization field when sandwiched between graphene. Such a field gives rise to a spontaneous photovoltaic effect without needing any p-n junction. In this work, we show the photovoltaic effect has an external quantum efficiency

Hampus Malmberg, Fredrik Feyling, Jose M de la Rosa

In this paper, the design flexibility of the control-bounded analog-to-digital converter principle is demonstrated by considering band-pass analog-to-digital conversion. We show how a low-pass control-bounded analog-to-digital converter can be translated into a band-pass version where the guaranteed stability, converter bandwidth, and signal-to-noise ratio a

Ali Ghalavand, Tamás Réti, Igor Z. Milovanović, Ali Reza Ashrafi

In this study we are interested mainly in investigating the relations between two graph irregularity measures which are widely used for structural irregularity characterization of connected graphs. Our study is focused on the comparison and evaluation of the discriminatory ability of irregularity measures called degree deviation S(G) and degree variance Var(

Sai Chaitanya Balli

Using the Functional Object-Oriented Network, we have implemented three search algorithms for generating the task trees for the given goal nodes. The approach, process, and results are written in this paper.

Yoshiki Masuyama, Kohei Yatabe, Kento Nagatomo, Yasuhiro Oikawa

This paper presents a two-stage online phase reconstruction framework using causal deep neural networks (DNNs). Phase reconstruction is a task of recovering phase of the short-time Fourier transform (STFT) coefficients only from the corresponding magnitude. However, phase is sensitive to waveform shifts and not easy to estimate from the magnitude even with a

Hao Tang, Lei Ding, Songsong Wu, Bin Ren

Video processing and analysis have become an urgent task since a huge amount of videos (e.g., Youtube, Hulu) are uploaded online every day. The extraction of representative key frames from videos is very important in video processing and analysis since it greatly reduces computing resources and time. Although great progress has been made recently, large-scal

Hampus Malmberg, Till Mettler, Thomas Burger, Fredrik Feyling

The paper considers the calibration of control-bounded analog-to-digital converters. It is demonstrated that variations of the analog frontend can be addressed by calibrating the digital estimation filter. In simulations (both behavioral and transistor level) of a leapfrog analog frontend, the proposed calibration method restores essentially the nominal perf

Kaustubh D. Dhole

With only 65% of Indian houses having access to the Internet, digital India faces a significant Internet divide across gender and city types. Rendering essential services inaccessible to almost a third of the population necessitates not only provisioning a fundamental right to Internet access but taking specific constructive steps to assure its simple, affor

Udbhav Bamba, Neeraj Anand, Saksham Aggarwal, Dilip K. Prasad

Binarization is a powerful compression technique for neural networks, significantly reducing FLOPs, but often results in a significant drop in model performance. To address this issue, partial binarization techniques have been developed, but a systematic approach to mixing binary and full-precision parameters in a single network is still lacking. In this pap

Paul Christiano, Eric Neyman, Mark Xu

Mathematical proof aims to deliver confident conclusions, but a very similar process of deduction can be used to make uncertain estimates that are open to revision. A key ingredient in such reasoning is the use of a "default" estimate of $\mathbb{E}[XY] = \mathbb{E}[X] \mathbb{E}[Y]$ in the absence of any specific information about the correlation between $X

Xueshen Li, Hongshan Liu, Xiaoyu Song, Brigitta C. Brott

Histopathological analysis is crucial in artery characterization for coronary artery disease (CAD). However, histology requires an invasive and time-consuming process. In this paper, we propose to generate virtual histology staining using Optical Coherence Tomography (OCT) images to enable real-time histological visualization. We develop a deep learning netw

Adele Padgett

We adapt the construction of the field of logarithmic-exponential transseries of van den Dries, Macintyre, and Marker to build an ordered differential field of sublogarithmic-transexponential series. We use this structure to build a transexponential Hardy field closed under composition. Specifically, we prove that the germs at $+\infty$ of $\mathcal{L}_{\mat

B Swaroopa Reddy, T Uday Kiran Reddy

In this work, we propose a stateless blockchain called CompactChain, which compacts the entire state of the UTXO (Unspent Transaction Output) based blockchain systems into two RSA accumulators. The first accumulator is called Transaction Output (TXO) commitment which represents the TXO set. The second one is called Spent Transaction Output (STXO) commitment

Amir Ghorbani

There are different physics-based approaches for analysing pedestrian movement. Physics-based methods like statistical mechanics-based models apply the laws of physics to drive equations for analysing crowd behaviour. This paper will introduce a physics-based approach based on field theory as a new tool for crowd analysis to determine governing differential

Liang Zhang, Justin Lieffers, Adarsh Pyarelal

Human decision-making often involves combining similar states into categories and reasoning at the level of the categories rather than the actual states. Guided by this intuition, we propose a novel method for clustering state features in deep reinforcement learning (RL) methods to improve their interpretability. Specifically, we propose a plug-and-play fram

Mobasshir Mahbub, Raed M. Shubair

Non-orthogonal multiple access (NOMA) scheme enables serving users with the same resource block i.e. frequency or time by multiplexing the signal of the users. Intelligent reflecting surfaces (IRS) or reconfigurable intelligent surfaces (RIS) is a potential approach for increasing transmission efficiency by modifying signal propagation by tweaking typically

Hugo Mirault

Cryptography is the discipline that allows securing of the exchange of information. In this internship, we will focus on a certain branch of this discipline, secure computation in a network. The main goal of this internship, illustrated in this report, is to adapt a roster of protocols intended to do linear algebra. We want to adapt them to do algebra for ma

Nathan Berkovits

The physical states of D=5 holomorphic Chern-Simons theory correspond to on-shell D=10 open superstring states in the cohomology of $q_+$, where $q_+$ is one of the 16 spacetime supersymmetry generators. Scattering amplitudes of these states can be computed either using the usual Ramond-Neveu-Schwarz (RNS) superstring prescription with N=1 worldsheet supersy

Conghan Dong

In this paper, we show that for a sequence of orientable complete uniformly asymptotically flat $3$-manifolds $(M_i , g_i)$ with nonnegative scalar curvature and ADM mass $m(g_i)$ tending to zero, by subtracting some open subsets $Z_i$, whose boundary area satisfies $\mathrm{Area}(\partial Z_i) \leq Cm(g_i)^{1/2 - \varepsilon}$, for any base point $p_i \in M

Ritesh Ghosh, Manu Kurian

Electric charge transport of hadronic matter at finite temperature and magnetic field is studied within the linear sigma model. Anisotropic transport coefficients associated with the charge transport are estimated both in the weak and strong regimes of the magnetic field using the transport theory approach. In a weakly magnetized medium, the magnetic field e

Hongshan Liu, Xueshen Li, Abdul Latif Bamba, Xiaoyu Song

Optical coherence tomography (OCT) has become increasingly essential in assisting the treatment of coronary artery disease (CAD). Image-guided solutions such as Percutaneous Coronary Intervention (PCI) are extensively used during the treatment of CAD. However, unidentified calcified regions within a narrowed artery could impair the outcome of the PCI. Prior

Alice Minelli, Michele Bellazzini, Alessio Mucciarelli, Piercarlo Bonifacio

We present metallicity and radial velocity for 450 bonafide members of the Sagittarius dwarf spheroidal (Sgr dSph) galaxy, measured from high resolution (R~18000) FLAMES@VLT spectra. The targets were carefully selected (a) to sample the core of the main body of Sgr dSph while avoiding contamination from the central stellar nucleus, and (b) to prevent any bia

Yuda Bi, Anees Abrol, Zening Fu, Vince Calhoun

Vision Transformer (ViT) is a pioneering deep learning framework that can address real-world computer vision issues, such as image classification and object recognition. Importantly, ViTs are proven to outperform traditional deep learning models, such as convolutional neural networks (CNNs). Relatively recently, a number of ViT mutations have been transplant

Isael Herrera, Pedro A. Quinto-Su

In this work we present a simple code to calculate tightly focused vectorial light fields (propagating and evanescent) generated by input fields that have arbitrary amplitude, phase and polarization. The program considers results from previous studies, like integration via fast Fourier transforms to speed up the integration. The calculations are done in a Ca

Chin-Yao Chang, Richard Macwan, Sinnott Murphy

The control of future power grids is migrating from a centralized to a distributed/decentralized scheme to enable a massive penetration of distributed energy resources and bring extreme enhancements of autonomous operations in terms of grid resilience, security, and reliability. Most effort has been on the design of distributed/decentralized controllers; how

Yue Yu, Yulin Chi, Chonghao Zhai, Jieshan Huang

Simulating the dynamic evolutions of physical and molecular systems in a quantum computer is of fundamental interest in many applications. Its implementation requires efficient quantum simulation algorithms. The Lie-Trotter-Suzuki approximation algorithm, also well known as the Trotterization, is a basic algorithm in quantum dynamic simulation. A multi-produ

Jake Ruotolo, Kevin Wang, Fan Wei

Let $G$ be a multipartite graph with partition $V_1, V_2,\ldots, V_k$ of $V(G)$. Let $d_{i,j}$ denote the edge density of the pair $(V_i, V_j)$. An independent transversal is an independent set of $G$ with exactly one vertex in each $V_i$. In this paper, we prove an asymptotically sharp upper bound on the maximum number of independent transversals given the

Liang Zhang, Justin Lieffers, Adarsh Pyarelal

When performing complex tasks, humans naturally reason at multiple temporal and spatial resolutions simultaneously. We contend that for an artificially intelligent agent to effectively model human teammates, i.e., demonstrate computational theory of mind (ToM), it should do the same. In this paper, we present an approach for integrating high and low-resoluti

Rupali Patil, Bhairav Narkhede, Shubham Varma, Shreyans Suraliya

Purpose: An Electrocardiogram (ECG) is the simplest and fastest bio-medical test that is used to detect any heart-related disease. ECG signals are generally stored in paper form, which makes it difficult to store and analyze the data. While capturing ECG leads from paper ECG records, a lot of background information is also captured, which results in incorrec

Hao Tang, Ling Shao, Philip H. S. Torr, Nicu Sebe

We present a novel bipartite graph reasoning Generative Adversarial Network (BiGraphGAN) for two challenging tasks: person pose and facial image synthesis. The proposed graph generator consists of two novel blocks that aim to model the pose-to-pose and pose-to-image relations, respectively. Specifically, the proposed bipartite graph reasoning (BGR) block aim

Carlo Rovelli, Francesca Vidotto

Understanding the quantum aspects of gravity is not only a matter of equations and experiments. Gravity is intimately connected with the structure of space and time, and understanding quantum gravity requires us to find a conceptual structure appropriate to make sense of the quantum aspects of space and time. In the course of the last decades, an extensive d

Shubham Thakar, Dhananjay Kalbande

Business intelligence (BI) is any knowledge derived from existing data that may be strategically applied within a business. Data mining is a technique or method for extracting BI from data using statistical data modeling. Finding relationships or correlations between the various data items that have been collected can be used to boost business performance or

Linshan Jiang, Qun Song, Rui Tan, Mo Li

Mobile cloud offloading is indispensable for inference tasks based on large-scale deep models. However, transmitting privacy-rich inference data to the cloud incurs concerns. This paper presents the design of a system called PriMask, in which the mobile device uses a secret small-scale neural network called MaskNet to mask the data before transmission. PriMa

Alexei A. Pevtsov, T. Woods, V. Martinez-Pillet, D. Hassler

This White Paper argues for the urgent need for the multi-vantage/multi-point observations of the Sun and the heliosphere in the framework of six (6) key science objectives. We further emphasize the critical importance of 5D-``space'': three spatial, one temporal and the magnetic field components. The importance of such observations cannot be overstated both

Victor Robila, Kexin Pei, Junfeng Yang

It is beneficial to develop an efficient machine-learning based method for addition using embedded hexadecimal digits. Through a comparison between human-developed machine learning model and models sampled through Neural Architecture Search (NAS) we determine an efficient approach to solve this problem with a final testing loss of 0.2937 for a human-develope

Abhinav Gupta, Pierre F. J. Lermusiaux

Predictive dynamical models for marine ecosystems are used for a variety of needs. Due to sparse measurements and limited understanding of the myriad of ocean processes, there is however significant uncertainty. There is model uncertainty in the parameter values, functional forms with diverse parameterizations, level of complexity needed, and thus in the sta

Łukasz Baran, Wojciech Rżysko, Luis G. MacDowell

With an ever-increasing interest in water properties, many intermolecular force fields have been proposed to describe the behavior of water. Unfortunately, good models for liquid water usually cannot provide simultaneously an accurate melting point for ice. For this reason, the TIP4P/Ice model was developed at targeting the melting point, and has become the

Alexei A. Pevtsov, V. Martinez-Pillet, H. Gilbert, A. G. de Wijn

Long-term synoptic observations of the Sun are critical for advancing our understanding of Sun as an astrophysical object, understanding the solar irradiance and its role in solar-terrestrial climate, for developing predictive capabilities of solar eruptive phenomena and their impact on our home planet, and heliosphere in general, and as a data provider for

Marina Ghisi, Massimo Gobbino

It is well-known that the classical hyperbolic Kirchhoff equation admits infinitely many simple modes, namely time-periodic solutions with only one Fourier component in the space variables. In this paper we assume that, for a suitable choice of the nonlinearity, there exists a heteroclinic connection between two simple modes with different frequencies. Under

Kyunghoon Ban, Désiré Kédagni

The difference-in-differences (DID) method identifies the average treatment effects on the treated (ATT) under mainly the so-called parallel trends (PT) assumption. The most common and widely used approach to justify the PT assumption is the pre-treatment period examination. If a null hypothesis of the same trend in the outcome means for both treatment and c

N. van Loo, G. P. Mazur, T. Dvir, G. Wang

The proximity effect in semiconductor-superconductor nanowires is expected to generate an induced gap in the semiconductor. The magnitude of this induced gap, together with the semiconductor properties like the spin-orbit coupling and $g$\,-\,factor, depends on the coupling between the materials. It is predicted that this coupling can be adjusted through the

Zongzhu Lin, Daniel K. Nakano

Let $G$ be a complex reductive group and $P$ be a parabolic subgroup of $G$. In this paper the authors address questions involving the realization of the $G$-module of the global sections of the (twisted) cotangent bundle over the flag variety $G/P$ via the cohomology of the small quantum group. Our main results generalize the important computation of the co

Jan Ditzen, Yiannis Karavias, Joakim Westerlund

This paper develops a new toolbox for multiple structural break detection in panel data models with interactive effects. The toolbox includes tests for the presence of structural breaks, a break date estimator, and a break date confidence interval. The new toolbox is applied to a large panel of US banks for a period characterized by massive quantitative easi

Mohammad Akil, Mohamed Balegh, Zayd Hajjej

The purpose of this work is to investigate the exponential stability of a second order coupled wave equations by laplacian with one locally internal viscous damping. Firstly, using a unique continuation theorem combined with a Carleman estimate, we prove that our system is strongly stable without any geometric condition. Secondly, using a combination of the

Chenghong Bian, Yulin Shao, Haotian Wu, Deniz Gunduz

This paper presents a novel deep joint source-channel coding (DeepJSCC) scheme for image transmission over a half-duplex cooperative relay channel. Specifically, we apply DeepJSCC to two basic modes of cooperative communications, namely amplify-and-forward (AF) and decode-and-forward (DF). In DeepJSCC-AF, the relay simply amplifies and forwards its received

Christoph Walker

Schauder's fixed point theorem is used to derive the existence of solutions to a semilinear heat equation. The equation features a nonlinear term that depends on the time-integral of the unknown on the whole, a priori given, interval of existence.

Chris N. Self, Marcello Benedetti, David Amaro

A successful quantum error correction protocol would allow quantum computers to run algorithms without suffering from the effects of noise. However, fully fault-tolerant quantum error correction is too resource intensive for existing quantum computers. In this context we develop a quantum error detection code for implementations on existing trapped-ion compu

Wolfgang Himmler, Ralf Fischer, Michael Barth, Jacob Fuchs

Wires made of topological insulators (TI) are a promising platform for searching for Majorana bound states. These states can be probed by analyzing the fractional ac Josephson effect in Josephson junctions with the TI wire as a weak link. An axial magnetic field can be used to tune the system from trivial to topologically nontrivial. Here we investigate the

Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang

3D Garment modeling is a critical and challenging topic in the area of computer vision and graphics, with increasing attention focused on garment representation learning, garment reconstruction, and controllable garment manipulation, whereas existing methods were constrained to model garments under specific categories or with relatively simple topologies. In

Ryszard Deszcz, Małgorzata Głogowska, Marian Hotloś, Katarzyna Sawicz

We investigate hypersurfaces M isometrically immersed in an (n+1)-dimensional semi-Riemannian space of constant curvature, n > 3, such that the operator A^3, where A is the shape operator of M, is a linear combination of the operators A^2 and A and the identity operator Id. The main result states that on the set U of all points of M at which the square of th

Noushin Raeisi Kheirabadi, Alessandro Chiolerio, Andrew Adamatzky

Pavlovian reflex is an essential mechanism of nervous systems of living beings which allows them to learn. Liquid colloid computing devices offer a high degree of fault-tolerance, reconfigurability and plasticity. As a first step towards designing and prototyping colloidal neuromorphic computing systems we decided to evaluate if it is possible to implement P

F. Haberl, G. Vasilopoulos, C. Maitra, F. Valdes

During the third all-sky survey (eRASS3), eROSITA, the soft X-ray instrument aboard Spectrum-Roentgen-Gamma, detected a new hard X-ray transient, eRASSt J040515.6-745202, in the direction of the Magellanic Bridge. We arranged follow-up observations and searched for archival data to reveal the nature of the transient. Using X-ray observations with XMM-Newton,

Xiaogang Liu Shuang Song

Recent works on salient object detection have made use of multi-scale features in a way such that high-level features and low-level features can collaborate in locating salient objects. Many of the previous methods have achieved great performance in salient object detection. By merging the high-level and low-level features, a large number of feature informat

Tomoya Shiba, Tomohiro Ono, Shoshi Tokuno, Issei Uchino

Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in Japan in the Kitakyushu Science and Research Park. Since 2010, we have annually participated in the RoboCup@Home Japan Open competition in the open platform league (OPL).We participated as an open platform league team in the 2017 Nagoya RoboCup competition and as a domestic standard p

Khen Cohen, Omer Hershko, Homer Levy, David Mendlovic

This work demonstrates a novel, state of the art method to reconstruct colored images via the Dynamic Vision Sensor (DVS). The DVS is an image sensor that indicates only a binary change in brightness, with no information about the captured wavelength (color), or intensity level. We present a novel method to reconstruct a full spatial resolution colored image

Y. Zarghami, S. Mafeld, A. Conway, B. Taati

Pain monitoring is essential to the quality of care for patients undergoing a medical procedure with sedation. An automated mechanism for detecting pain could improve sedation dose titration. Previous studies on facial pain detection have shown the viability of computer vision methods in detecting pain in unoccluded faces. However, the faces of patients unde

Franco Flandoli, Ruojun Huang, Andrea Papini

In the present article we introduce a variant of Smoluchowski's coagulation equation with both position and velocity variables taking a kinetic viewpoint arising as the scaling limit of a system of second-order (microscopic) coagulating particles. We focus on the rigorous study of the PDE system in the spatially-homogeneous case proving existence and uniquen

Federico W. Pasini, Alexandra N. Busch, Ján Mináč, Krishnan Padmanabhan

Although temporal coding through spike-time patterns has long been of interest in neuroscience, the specific structures that could be useful for spike-time codes remain highly unclear. Here, we introduce a new analytical approach, using techniques from discrete mathematics, to study spike-time codes. We focus on the phenomenon of ``phase precession'' in the

Longguang Li, Ru-Han Chen, Jing Zhou

This paper investigates the sum-capacity of two-user optical intensity multiple access channels with per-user peak- or/and average-intensity constraints. By leveraging tools from the decomposition of certain maxentropic distributions, we derive several lower bounds on the sum-capacity. In the high signal-to-noise ratio (SNR) regime, some bounds asymptoticall

Vaisakh Mannalath, Anirban Pathak

Distributing entanglement among multiple users is a fundamental problem in quantum networks, requiring an efficient solution. In this work, a protocol is proposed for extracting maximally entangled (GHZn) states for any number of parties in quantum networks of arbitrary topology. It is based on the graph state formalism and requires minimal assumptions on th

Runzhao Yang, Tingxiong Xiao, Yuxiao Cheng, Jinli Suo

Implicit neural representation (INR) can describe the target scenes with high fidelity using a small number of parameters, and is emerging as a promising data compression technique. However, limited spectrum coverage is intrinsic to INR, and it is non-trivial to remove redundancy in diverse complex data effectively. Preliminary studies can only exploit eithe

Ryotaro Shimizu, Takuma Nakamura, Masayuki Goto

In this study, we propose a technology called the Fashion Intelligence System based on the visual-semantic embedding (VSE) model to quantify abstract and complex expressions unique to fashion, such as ''casual,'' ''adult-casual,'' and ''office-casual,'' and to support users' understanding of fashion. However, the existing VSE model does not support the situa

Yusong Wu, Ke Chen, Tianyu Zhang, Yuchen Hui

Contrastive learning has shown remarkable success in the field of multimodal representation learning. In this paper, we propose a pipeline of contrastive language-audio pretraining to develop an audio representation by combining audio data with natural language descriptions. To accomplish this target, we first release LAION-Audio-630K, a large collection of

Jin Min Yang, Pengxuan Zhu, Rui Zhu

This is a brief overview on the low energy supersymmetry in light of current experiments including the LHC searches, the dark matter (DM) detections, the muon g-2 and the CDF II measurement of the W-boson mass. We focus on the minimal framework of supersymmetry, namely the minimal supersymmetric model (MSSM), and obtain the following conclusions: (i) The MSS

Irina Zubareva

We find geodesics, shortest arcs, cut loci, first conjugate loci, distances between arbitrary elements for some left-invariant sub-Riemannian metrics on the Lie groups $SU(2)\times\mathbb{R}$ and $SO(3)\times\mathbb{R}$.

Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang

Detecting anomalous trajectories has become an important task in many location-based applications. While many approaches have been proposed for this task, they suffer from various issues including (1) incapability of detecting anomalous subtrajectories, which are finer-grained anomalies in trajectory data, and/or (2) non-data driven, and/or (3) requirement o

Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong

Post-click conversion rate (CVR) prediction is an essential task for discovering user interests and increasing platform revenues in a range of industrial applications. One of the most challenging problems of this task is the existence of severe selection bias caused by the inherent self-selection behavior of users and the item selection process of systems. C

Maximilian Mühlbauer

Motivated by problems arising in the complex analysis of perturbative quantum field theory, we investigate the homology of finite unions of certain non-degenerate quadratic affine hypersurfaces of complex dimension $n$ in general position. The homology of such unions and the homology of $\mathbb{C}^{n+1}$ relative to such unions is decomposed into a direct s

Štefko Miklavič, Johannes Pardey, Dieter Rautenbach, Florian Werner

Do\v{s}li\'{c} et al. defined the Mostar index of a graph $G$ as $Mo(G)=\sum\limits_{uv\in E(G)}|n_G(u,v)-n_G(v,u)|$, where, for an edge $uv$ of $G$, the term $n_G(u,v)$ denotes the number of vertices of $G$ that have a smaller distance in $G$ to $u$ than to $v$. They conjectured that $Mo(G)\leq 0.\overline{148}n^3$ for every graph $G$ of order $n$. As a nat

Minrui Xu, Dusit Niyato, Jiawen Kang, Zehui Xiong

In this paper, a novel paradigm of mobile edge-quantum computing (MEQC) is proposed, which brings quantum computing capacities to mobile edge networks that are closer to mobile users (i.e., edge devices). First, we propose an MEQC system model where mobile users can offload computational tasks to scalable quantum computers via edge servers with cryogenic com

Fatemeh Alikhani, Mehdi Ghorbani, Saad Varsaie

The main objective of this article is to extend the concept of transversality to supergeometry. Transversality has two important properties in the classical case, namely " stability" and " genericity", which we show in the following that in the category of smooth supermanifolds, supertransversality has stable property. By extending Sard's theorem to supergeo

Zhongzhi Chen, Guang Liu, Bo-Wen Zhang, Fulong Ye

In this work, we present a conceptually simple and effective method to train a strong bilingual/multilingual multimodal representation model. Starting from the pre-trained multimodal representation model CLIP released by OpenAI, we altered its text encoder with a pre-trained multilingual text encoder XLM-R, and aligned both languages and image representation

Pietro Novelli

Machine learning algorithms designed to learn dynamical systems from data can be used to forecast, control and interpret the observed dynamics. In this work we exemplify the use of one of such algorithms, namely Koopman operator learning, in the context of open quantum system dynamics. We will study the dynamics of a small spin chain coupled with dephasing g

Christophe Duhame, Philippe Lacomme, Caroline Prodhon

Split procedures have been proved to be efficient within global framework optimization for routing problems by splitting giant tour into trips. This is done by generating optimal shortest path within an auxiliary graph built from the giant tour. An efficient application has been introduced for the first time by Lacomme et al. (2001) within a metaheuristic ap

Fleury Gérard, Lacomme Philippe, Prins Christian, Sevaux Marc

The Capacitated Arc Routing Problem (CARP) occurs in applications like urban waste collection or winter gritting. It is usually defined in literature on an undirected graph , with a set of nodes and a set of edges. A fleet of identical vehicles of capacity is based at a depot node. Each edge has a cost (length) and a demand (e.g. an amount of waste), and it

Arjan van der Schaft, Volker Mehrmann

Port-Hamiltonian systems theory provides a systematic methodology for the modeling, simulation and control of multi-physics systems. The incorporation of algebraic constraints has led to a multitude of definitions of port-Hamiltonian differential-algebraic equations (DAE) systems. This paper presents extensions of results in Gernandt, Haller & Reis (2021) an

David Nugent

Credit card fraud is a problem continuously faced by financial institutions and their customers, which is mitigated by fraud detection systems. However, these systems require the use of sensitive customer transaction data, which introduces both a lack of privacy for the customer and a data breach vulnerability to the card provider. This paper proposes a syst

Soobin Cho, Panki Kim, Jaehun Lee

In this paper, we discuss the laws of the iterated logarithm (LIL) for occupation times of Markov processes $Y$ in general metric measure space both near zero and near infinity under some minimal assumptions. We first establish LILs of (truncated) occupation times on balls $B(x,r)$ of radii $r$ up to an function $\Phi (r)$, which is an iterated logarithm of

Hao Fu

Mazur's principle gives a criterion under which an irreducible mod $\ell$ Galois representation arising from a modular form of level $Np$ (with $p$ prime to $N$) can also arise from a modular form of level $N.$ We prove an analogous result showing that a mod $\ell$ Galois representation arising from a stable cuspidal automorphic representation of the unitary

Hajime Koba

We consider the governing equations for the motion of the inviscid fluids in two moving domains and an evolving surface from an energetic point of view. We employ our energetic variational approaches to derive inviscid multiphase flow systems with surface flow and tension. More precisely, we calculate the variation of the flow maps to the action integral for

Ugo Dal Lago, Francesco Gavazzo, Alexis Ghyselen

We introduce a variation on Barthe et al.'s higher-order logic in which formulas are interpreted as predicates over open rather than closed objects. This way, concepts which have an intrinsically functional nature, like continuity, differentiability, or monotonicity, can be expressed and reasoned about in a very natural way, following the structure of the un

Rebecca Waldecker

The year 1954 marks the beginning of a tradition of workshops at the MFO in the area of finite group theory. This is highlighted and put into context in this article (contribution to a book).

Canhui Chen, Zerui Cheng, Shutong Qu, Zhixuan Fang

Proof-of-Work (PoW) consensus mechanism is popular among current blockchain systems, which leads to an increasing concern about the tremendous waste of energy due to massive meaningless computation. To address this issue, we propose a novel and energy-efficient blockchain system, CrowdMine, which exploits useful crowdsourcing computation to achieve decentral

Gerard Valentí-Rojas, Aneirin J. Baker, Alessio Celi, Patrik Öhberg

We introduce topological gauge fields as nontrivial field configurations enforced by topological currents. These fields crucially determine the form of statistical gauge fields that couple to matter and transmute their statistics. We discuss the physical mechanism underlying the composite particle picture and argue that it is a duality of gauge forms that na

Sasan Razmkhah, Ali Bozbey, Pascal Febvre

Readout and control of qubits are limiting factors in scaling quantum computers. An ideal solution is to integrate energy-efficient cryogenic circuits close to the qubits to perform control and pre-processing tasks. With orders of magnitude lower power consumption and hence lower noise, Single Flux Quantum (SFQ) and Adiabatic Quantum Flux Parametron (AQFP) s

Sushi Anna George, Vinay Joseph

We consider the problem of enhancing the delivery of real-time traffic in wireless networks using bandwidth sharing between operators. A key characteristic of real-time traffic is that a packet has to be delivered within a delay deadline for it to be useful. The abundance of real-time traffic is evident in the popularity of applications like video and audio

Yunpeng Qing, Shunyu Liu, Jie Song, Yang Zhou

Reinforcement Learning (RL) is a popular machine learning paradigm where intelligent agents interact with the environment to fulfill a long-term goal. Driven by the resurgence of deep learning, Deep RL (DRL) has witnessed great success over a wide spectrum of complex control tasks. Despite the encouraging results achieved, the deep neural network-based backb

Philipp Scharpf, Moritz Schubotz, Bela Gipp

The increasing number of questions on Question Answering (QA) platforms like Math Stack Exchange (MSE) signifies a growing information need to answer math-related questions. However, there is currently very little research on approaches for an open data QA system that retrieves mathematical formulae using their concept names or querying formula identifier re