November 2022 arXiv papers — page 54

Agnese Barbensi, Daniele Celoria

The problem of finding robust and effective methods for locating entanglement in embedded curves is relevant to both applications and theoretical investigations. Rather than focusing on an exact determination, we introduce the knot intensity distribution, a local quantifier for the contribution of a curve's region to global entanglement. The integral of the

Anthony Genevois

To every semigroup presentation $\mathcal{P}= \langle \Sigma \mid \mathcal{R} \rangle$ and every baseword $w \in \Sigma^+$ can be associated a diagram group $D(\mathcal{P},w)$, defined as the fundamental group of the so-called Squier complex $S(\mathcal{P},w)$. Roughly speaking, $D(\mathcal{P},w)$ encodes the lack of asphericity of $\mathcal{P}$. Examples of

Andjelka B. Kovacevic, Aleksandra Nina, Luka C. Popovic, Milan Radovanovic

Extraction of information in the form of oscillations from noisy data of natural phenomena such as sounds, earthquakes, ionospheric and brain activity, and various emissions from cosmic objects is extremely difficult. As a method for finding periodicity in such challenging data sets, the 2D Hybrid approach, which employs wavelets, is presented. Our technique

Kazuhiro Ishige, Sho Katayama

This paper is concerned with the structure of solutions to the elliptic problem for an Henon type equation with a forcing term. Under suitable assumptions on the forcing term, we give a complete classification of the existence/nonexistence of solutions to the problem.

Tung Nguyen, Alex Scott, Paul Seymour, Stephan Thomasse

It takes $n^2/4$ cliques to cover all the edges of a complete bipartite graph $K_{n/2,n/2}$, but how many cliques does it take to cover all the edges of a graph $G$ if $G$ has no $K_{t,t}$ induced subgraph? We prove that $O(|G|^{2-1/(2t)})$ cliques suffice; and also prove that, even for graphs with no stable set of size four, we may need more than linearly m

Liangyu Chen, Huajia Wang

Causal shadows are bulk space-time regions between the entanglement wedges and the causal wedges, their existence encodes deep aspects of the entanglement wedge reconstruction in the context of subregion duality in AdS/CFT. In this paper, we study the perturbation theory of the causal shadows and their relation to the properties of the associated modular flo

Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós

Composition theorems are general and powerful tools that facilitate privacy accounting across multiple data accesses from per-access privacy bounds. However they often result in weaker bounds compared with end-to-end analysis. Two popular tools that mitigate that are the exponential mechanism (or report noisy max) and the sparse vector technique. They were g

Filippo Boni, Raffaele Carlone

We investigate the existence and the uniqueness of NLS ground states of fixed mass on the half-line in the presence of a point interaction at the origin. The nonlinearity is of power type, and the regime is either $L^2$-subcritical or $L^{2}$-critical, while the point interaction is either attractive or repulsive. In the $L^{2}$-subcritical case, we prove th

Wudu Muluneh, Tadesse Amsalu

The provision of essential urban infrastructure and services for the expanding population is a persistent financial challenge for many of the rapidly expanding cities in developing nations like Ethiopia. The land lease system has received little academic attention as a means of financing urban infrastructure in developing countries. Therefore, the main objec

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We report a search for a heavier partner of the recently observed $Z_{cs}(3985)^{-}$ state, denoted as $Z_{cs}^{\prime -}$, in the process $e^{+} e^{-}\rightarrow K^{+}D_{s}^{*-}D^{* 0}+c.c.$, based on $e^+e^-$ collision data collected at the center-of-mass energies of $\sqrt{s}=4.661$, 4.682 and 4.699 GeV with the BESIII detector. The $Z_{cs}^{\prime -}$ is

Julie Rana, Sönke Rollenske

We consider the stable compactification $\bar {\mathfrak H}$ of the moduli space of Horikawa surfaces with $K_X^2 = 2p_g(X) -4$. When $K_X^2 =8\ell$ we show that the closures of the two components $\mathfrak H^{\mathrm I}$ and $\mathfrak H^{\mathrm {II}}$ of the Gieseker moduli space intersect, for $\ell>2$ in a divisor parametrising explicitly described sem

Taejin Paik, Otto van Koert

In this paper, we study the expectation values of topological invariants of the Vietoris-Rips complex and \v{C}ech complex for a finite set of sample points on a Riemannian manifold. We show that the Betti number and Euler characteristic of the complexes are Lipschitz functions of the scale parameter and that there is an interval such that the Betti curve co

Christopher Aubin, Thomas Blum, Maarten Golterman, Santiago Peris

We present new results for the light-quark connected part of the leading order hadronic-vacuum-polarization (HVP) contribution to the muon anomalous magnetic moment, using $2+1+1$ staggered fermions. We have collected more statistics on previous ensembles, and we added two new ensembles. This allows us to reduce statistical errors on the HVP contribution and

Yu-Qi Dong, Yu-Qiang Liu, Yu-Xiao Liu

In this paper, we investigate the possible parameter space of Palatini-Horndeski theory with gravitational waves in a spatially flat Universe. We find that if the theory satisfies the following condition: in any spatially flat cosmological background, the tensor gravitational wave speed is the speed of light $c$, then only $S = \int d^4x \sqrt{-g} \big[K(\ph

Varun Bhalerao, Santosh Vadawale, Shriharsh Tendulkar, Dipankar Bhattacharya

We present Daksha, a proposed high energy transients mission for the study of electromagnetic counterparts of gravitational wave sources, and gamma ray bursts. Daksha will comprise of two satellites in low earth equatorial orbits, on opposite sides of earth. Each satellite will carry three types of detectors to cover the entire sky in an energy range from 1

Yuan Yao, Tianyu Yu, Ao Zhang, Mengdi Li

Large-scale commonsense knowledge bases empower a broad range of AI applications, where the automatic extraction of commonsense knowledge (CKE) is a fundamental and challenging problem. CKE from text is known for suffering from the inherent sparsity and reporting bias of commonsense in text. Visual perception, on the other hand, contains rich commonsense kno

Maxim V. Barkov, Evgeniy Kalinin, Maxim Lyutikov

In gamma-ray binaries neutron star is orbiting a companion that produces a strong stellar wind. We demonstrate that observed properties of "stellar wind"-"pulsar wind" interaction depend both on the overall wind thrust ratio, as well as more subtle geometrical factors: the relative direction of the pulsar's spin, the plane of the orbit, the direction of moti

Varun Bhalerao, Disha Sawant, Archana Pai, Shriharsh Tendulkar

We present the science case for the proposed Daksha high energy transients mission. Daksha will comprise of two satellites covering the entire sky from 1~keV to $>1$~MeV. The primary objectives of the mission are to discover and characterize electromagnetic counterparts to gravitational wave source; and to study Gamma Ray Bursts (GRBs). Daksha is a versatile

Hao Shen, Zhong-Qiu Zhao, Wandi Zhang

In image denoising networks, feature scaling is widely used to enlarge the receptive field size and reduce computational costs. This practice, however, also leads to the loss of high-frequency information and fails to consider within-scale characteristics. Recently, dynamic convolution has exhibited powerful capabilities in processing high-frequency informat

Sarah Azouvi, Christian Cachin, Duc V. Le, Marko Vukolic

Blockchain protocols implement total-order broadcast in a permissionless setting, where processes can freely join and leave. In such a setting, to safeguard against Sybil attacks, correct processes rely on cryptographic proofs tied to a particular type of resource to make them eligible to order transactions. For example, in the case of Proof-of-Work (PoW), t

Ming Hu, Zeke Xia, Zhihao Yue, Jun Xia

As a promising distributed machine learning paradigm that enables collaborative training without compromising data privacy, Federated Learning (FL) has been increasingly used in AIoT (Artificial Intelligence of Things) design. However, due to the lack of efficient management of straggling devices, existing FL methods greatly suffer from the problems of low i

Yasumasa Kano, Katsuhito Sudoh, Satoshi Nakamura

Simultaneous translation is a task in which translation begins before the speaker has finished speaking. In its evaluation, we have to consider the latency of the translation in addition to the quality. The latency is preferably as small as possible for users to comprehend what the speaker says with a small delay. Existing latency metrics focus on when the t

Ornella Mattei, Vincenzo Gulizzi

The amplitude of a pulse that propagates in a homogeneous material whose properties are instantaneously changed periodically in time will undergo an exponential increase, due to the interference between the reflected and transmitted pulses generated at each sudden switch. Here we resolve the issue by designing suitable reciprocal PT-symmetric space-time micr

Minhyeok Lee, Suhwan Cho, Chaewon Park, Dogyoon Lee

The camouflaged object detection (COD) task aims to identify and segment objects that blend into the background due to their similar color or texture. Despite the inherent difficulties of the task, COD has gained considerable attention in several fields, such as medicine, life-saving, and anti-military fields. In this paper, we propose a novel solution calle

Alexander Ororbia, Ankur Mali

In this work, we develop convolutional neural generative coding (Conv-NGC), a generalization of predictive coding to the case of convolution/deconvolution-based computation. Specifically, we concretely implement a flexible neurobiologically-motivated algorithm that progressively refines latent state feature maps in order to dynamically form a more accurate i

Dogyoon Lee, Minhyeok Lee, Chajin Shin, Sangyoun Lee

Neural Radiance Field (NeRF) has exhibited outstanding three-dimensional (3D) reconstruction quality via the novel view synthesis from multi-view images and paired calibrated camera parameters. However, previous NeRF-based systems have been demonstrated under strictly controlled settings, with little attention paid to less ideal scenarios, including with the

Jiaming Zha, Xiangyu Wu, Ryan Dimick, Mark W. Mueller

We introduce collision-resilient aerial vehicles with icosahedron tensegrity structures, capable of surviving high-speed impacts and resuming operations post-collision. We present a model-based design approach, which guides the selection of the tensegrity components by predicting structural stresses through a dynamics simulation. Furthermore, we develop an a

Lu Pang, Tao Sun, Haibin Ling, Chao Chen

Due to the increasing computational demand of Deep Neural Networks (DNNs), companies and organizations have begun to outsource the training process. However, the externally trained DNNs can potentially be backdoor attacked. It is crucial to defend against such attacks, i.e., to postprocess a suspicious model so that its backdoor behavior is mitigated while i

Chen Zhang, Jing Ren

We propose a new stellar structure of compact stars, the ``cross stars" that consist of a hadronic matter core and a quark matter crust, with an inverted structure compared to the conventional hybrid stars. This distinct stellar structure naturally arises from the quark matter to hadronic matter transition associated with the chemical potential crossing, in

Jian Cheng Wong, Pao-Hsiung Chiu, Chin Chun Ooi, My Ha Da

Physics-Informed Neural Networks (PINNs) have been shown to be an effective way of incorporating physics-based domain knowledge into neural network models for many important real-world systems. They have been particularly effective as a means of inferring system information based on data, even in cases where data is scarce. Most of the current work however a

Mayukh R. Gangopadhyay, Shibesh K. Jas Pacif, M. Sami, Mohit K. Sharma

We consider a scenario of large-scale modification of gravity that does not invoke extra degrees of freedom but includes coupling between baryonic matter and dark matter in the Einstein frame. The total matter energy density follows the standard conservation, and evolution has the character of deceleration in this frame. The model exhibits interesting featur

Yiran Song, Qianyu Zhou, Lizhuang Ma

Implicit Neural Representations (INRs) are powerful to parameterize continuous signals in computer vision. However, almost all INRs methods are limited to low-level tasks, e.g., image/video compression, super-resolution, and image generation. The questions on how to explore INRs to high-level tasks and deep networks are still under-explored. Existing INRs me

Wujie Sun, Defang Chen, Can Wang, Deshi Ye

Although diffusion model has shown great potential for generating higher quality images than GANs, slow sampling speed hinders its wide application in practice. Progressive distillation is thus proposed for fast sampling by progressively aligning output images of $N$-step teacher sampler with $N/2$-step student sampler. In this paper, we argue that this dist

Shengnan Liang, Yichen Liu, Shangzhe Wu, Yu-Wing Tai

We present ONeRF, a method that automatically segments and reconstructs object instances in 3D from multi-view RGB images without any additional manual annotations. The segmented 3D objects are represented using separate Neural Radiance Fields (NeRFs) which allow for various 3D scene editing and novel view rendering. At the core of our method is an unsupervi

Yuki Takazawa, Tomonari Sei

Phylogenetic trees are key data objects in biology, and the method of phylogenetic reconstruction has been highly developed. The space of phylogenetic trees is a nonpositively curved metric space. Recently, statistical methods to analyze the set of trees on this space are being developed utilizing this property. Meanwhile, in Euclidean space, the log-concave

Suhwan Cho, Minhyeok Lee, Seunghoon Lee, Dogyoon Lee

Unsupervised video object segmentation (VOS) aims to detect and segment the most salient object in videos. The primary techniques used in unsupervised VOS are 1) the collaboration of appearance and motion information; and 2) temporal fusion between different frames. This paper proposes two novel prototype-based attention mechanisms, inter-modality attention

Shi Jer Low, Venugopalan, S. G. Raghavan, Harish Gopalan

Data-driven approaches, including deep learning, have shown great promise as surrogate models across many domains. These extend to various areas in sustainability. An interesting direction for which data-driven methods have not been applied much yet is in the quick quantitative evaluation of urban layouts for planning and design. In particular, urban designs

Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim

Forecasting future outcomes from recent time series data is not easy, especially when the future data are different from the past (i.e. time series are under temporal drifts). Existing approaches show limited performances under data drifts, and we identify the main reason: It takes time for a model to collect sufficient training data and adjust its parameter

Boya Du, Shaochuan Lin, Jiong Gao, Xiyu Ji

Online Food Ordering Service (OFOS) is a popular location-based service that helps people to order what you want. Compared with traditional e-commerce recommendation systems, users' interests may be diverse under different spatiotemporal contexts, leading to various spatiotemporal data distribution, which limits the fitting capacity of the model. However, nu

Honggu Zhou, Xiaogang Peng, Jiawei Mao, Zizhao Wu

Some self-supervised cross-modal learning approaches have recently demonstrated the potential of image signals for enhancing point cloud representation. However, it remains a question on how to directly model cross-modal local and global correspondences in a self-supervised fashion. To solve it, we proposed PointCMC, a novel cross-modal method to model multi

Jongho Park, Jinchao Xu, Xiaofeng Xu

In this paper, we propose a novel algorithm called Neuron-wise Parallel Subspace Correction Method (NPSC) for the finite neuron method that approximates numerical solutions of partial differential equations (PDEs) using neural network functions. Despite extremely extensive research activities in applying neural networks for numerical PDEs, there is still a s

Yuheng Shi, Xinxiao Wu, Hanxi Lin

Few-shot action recognition in videos is challenging for its lack of supervision and difficulty in generalizing to unseen actions. To address this task, we propose a simple yet effective method, called knowledge prompting, which leverages commonsense knowledge of actions from external resources to prompt a powerful pre-trained vision-language model for few-s

Igor I. Strakovsky, William J. Briscoe, Olga Cortes Becerra, Michael Dugger

We have evaluated pseudoscalar and scalar neutral pion photoproduction in $\vec{\gamma}p\to\pi^0p$ and $\vec{\gamma}p\to a_0^0p$ above the resonance region and within Regge phenomenology. Our fit, including GlueX $\Sigma$ pseudoscalar photoproduction data, shows that previous SLAC $\Sigma$ measurements for $\vec{\gamma}p \to \pi^0p$ above $E_\gamma = 4~\math

Jiwei Li, Lingyun Qiu, Zhongjing Wang, Hui Yu

This paper proposes a new mathematical formulation for flow measurement based on the inverse source problem for wave equations with partial boundary measurement. Inspired by the design of acoustic Doppler current profilers (ADCPs), we formulate an inverse source problem that can recover the flow field from the observation data on a few boundary receivers. To

Sourav Bhattacharya, Nitin Joshi

We consider a massless, minimally coupled quantum scalar field theory with an asymmetric self interaction, $V (\phi) = \lambda\phi^4/4!+\beta\phi^3/3!$ ($\lambda >0$) in the inflationary de Sitter spacetime. The potential is bounded from below. While the $\beta=0$ case has been much well studied, the motivation behind taking such a hybrid potential correspon

Nurimangul Nurmamat, Yong-Feng Huang, Jin-Jun Geng, Abdusattar Kurban

FRB 180916 is an important repeating fast radio burst (FRB) source. Interestingly, the activity of FRB 180916 shows a well-regulated behavior, with a period of 16.35 days. The bursts are found to occur in a duty circle of about 5 days in each period. In this study, we suggest that the bursts of FRB 180916 are produced by a strange star interacting with its p

Wanming Qi, Lei-Han Tang, Hugues Chaté

We study the order-disorder transition in two-dimensional incompressible systems of motile particles with alignment interactions through extensive numerical simulations of the incompressible Toner-Tu (ITT) field theory and a detailed finite-size scaling (FSS) analysis. The transition looks continuous in the explored parameter space, but the effective suscept

Andong Li, Guochen Yu, Wenzhe Liu, Xiaodong Li

Despite the promising performance of existing frame-wise all-neural beamformers in the speech enhancement field, it remains unclear what the underlying mechanism exists. In this paper, we revisit the beamforming behavior from the beam-space dictionary perspective and formulate it into the learning and mixing of different beam-space components. Based on that,

Abhijit Suprem, Sanjyot Vaidya, Joao Eduardo Ferreira, Calton Pu

Recent advances in text classification and knowledge capture in language models have relied on availability of large-scale text datasets. However, language models are trained on static snapshots of knowledge and are limited when that knowledge evolves. This is especially critical for misinformation detection, where new types of misinformation continuously ap

Rabin Banerjee, Soumya Bhattacharya

In this paper, we discuss Galilean relativistic Maxwell theory in detail. We first provide a set of mapping relations, derived systematically, that connect the covariant and contravariant vectors in the Lorentz relativistic and Galilean relativistic formulations. Exploiting this map, we construct the two limits of Galilean relativistic Maxwell theory from us

Vedant Sandeep Joshi, Sivanagaraja Tatinati, Yubo Wang

On current {\it e-}learning platforms, live classes are an important tool that provides students with an opportunity to get more involved while learning new concepts. In such classes, the element of interaction with teachers and fellow peers helps in removing learning silos and gives each student a chance to experience some aspects relevant to offline learni

Daniel P. Arnold, Yaxin Xu, Sho C. Takatori

The spatial organization of cell membrane glycoproteins and glycolipids is critical for mediating the binding of ligands, receptors, and macromolecules on the plasma membrane. However, we currently do not have the methods to quantify the spatial heterogeneities of macromolecular crowding on live cell surfaces. In this work, we combine experiment and simulati

Hansi Liu, Kristin Dana, Marco Gruteser, Hongsheng Lu

In Smart City and Vehicle-to-Everything (V2X) systems, acquiring pedestrians' accurate locations is crucial to traffic safety. Current systems adopt cameras and wireless sensors to detect and estimate people's locations via sensor fusion. Standard fusion algorithms, however, become inapplicable when multi-modal data is not associated. For example, pedestrian

Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio

Mitigating the climate crisis requires a rapid transition towards lower-carbon energy. Catalyst materials play a crucial role in the electrochemical reactions involved in numerous industrial processes key to this transition, such as renewable energy storage and electrofuel synthesis. To reduce the energy spent on such activities, we must quickly discover mor

Hari Govindha A., Pallavi Katre, Saravanan Balusamy, Sayak Banerjee

We experimentally investigate the evaporation characteristics of a sessile ethanol droplet containing Al$_2$O$_3$ and Cu nanoparticles of sizes 25 nm and 75 nm on a heated substrate using shadowgraphy and infrared imaging techniques. Our results demonstrate that the droplet contact line dynamics resulting from the presence of various nanoparticles plays a do

Yuxi Xiao, Nan Xue, Tianfu Wu, Gui-Song Xia

This paper presents a neural incremental Structure-from-Motion (SfM) approach, Level-S$^2$fM, which estimates the camera poses and scene geometry from a set of uncalibrated images by learning coordinate MLPs for the implicit surfaces and the radiance fields from the established keypoint correspondences. Our novel formulation poses some new challenges due to

Aditya Parik, Tadd Truscott, Som Dutta

Secondary fragmentation of an impulsively accelerated drop depends on fluid properties and velocity of the ambient. The critical Weber number $(\mathit{We}_{cr})$, the minimum Weber number at which a drop undergoes non-vibrational breakup, depends on density ratio $(\rho)$, the drop $(\mathit{Oh}_d)$, and the ambient $(\mathit{Oh}_o)$ Ohnesorge numbers. The

Mohamed Amine ben Salem, Karim Said Barsim, Bin Yang

Mining genuine mechanisms underlying the complex data generation process in real-world systems is a fundamental step in promoting interpretability of, and thus trust in, data-driven models. Therefore, we propose a variation-based cause effect identification (VCEI) framework for causal discovery in bivariate systems from a single observational setting. Our fr

Cunyuan Jiang, Enrico Beneduce, Matteo Baggioli, Chandan Setty

Phonon softening is a ubiquitous phenomenon in condensed matter systems which is often associated with charge density wave (CDW) instabilities and anharmonicity. The interplay between phonon softening, CDW and superconductivity is a topic of intense debate. In this work, the effects of anomalous soft phonon instabilities on superconductivity are studied base

Stefan Schoder, Felix Czwielong

We revisit the online repository, the data source, the details of the experiments, and selected numerical results of the EAA benchmark case of a low-pressure axial fan. We present the whole aeroacoustic simulation process and its validation by experimental results. A successful computation of the flow and acoustic involves the following procedure, including

Subhash Singha

We report the measurements of spin alignment ($\rho_{00}$) for $K^{*0}$, $\overline{K^{*0}}$, $K^{*+}$, and $K^{*-}$ vector mesons in RHIC isobar collisions (Zr+Zr and Ru+Ru) at $\sqrt{s_{\mathrm {NN}}}$ = 200 GeV. We observe the first non-zero spin alignment for $K^{*\pm}$ in heavy-ion collisions. The $K^{*\pm}$ $\rho_{00}$ is about 3.9$\sigma$ larger than

Shoudao Wen, Huazhen Lin

The literature on high-dimensional functional data focuses on either the dependence over time or the correlation among functional variables. In this paper, we propose a factor-guided functional principal component analysis (FaFPCA) method to consider both temporal dependence and correlation of variables so that the extracted features are as sufficient as pos

Jie Su, Yan Li

SDSS J111215.82+111745.0 is the second pulsating extremely low-mass white dwarf discovered. Two short-period pulsations, 107.56 and 134.275 s, were detected on this star, which would be the first observed pressure mode ($p$-mode) pulsations observed on a white dwarf. While the two potential $p$-modes have yet to be confirmed, they make SDSS J111215.82+111745

Naoya Kuroda, Ayaki Sunaga, Masato Senami

The enhancement of the parity-violating energy difference (PVED) by electronic excitation is studied for H$_2X_2$ ($X =$ O, S, Se, Te), CHFClBr, CHFClI, and CHFBrI. To clarify the enhancement mechanism, the dihedral angle dependence of the PVED of H$_2X_2$ in excited states is studied. If the contribution from the highest occupied molecular orbital (HOMO) to

Kumail Abbas, Muhammad Saeed, M. Imad Khan, Khandakar Ahmed

There has been a significant increase in the adoption of technology in cricket recently. This trend has created the problem of duplicate work being done in similar computer vision-based research works. Our research tries to solve one of these problems by segmenting ball deliveries in a cricket broadcast using deep learning models, MobileNet and YOLO, thus en

Jizhe Cui, Haozhi Sha, Wenfeng Yang, Rong Yu

Atomic-scale characterization of spin textures in solids is essential for understanding and tuning properties of magnetic materials and devices. While high-energy electrons are employed for atomic-scale imaging of materials, they are insensitive to the spin textures. In general, the magnetic contribution to the phase of high-energy electron wave is 1000 time

Alexander Mednykh, Ilya Mednykh, Ivan Yudin

In the present paper we compute the Jacobian group of $\Delta$-graph $\Delta(n; k, l, m).$ The notion of $\Delta$-graph continues the list of families of $I$-, $Y$- and $H$-graphs well-known in the graph theory. In particular, graph $\Delta(n; 1, 1, 1)$ is isomorphic to discrete torus $C_3\times C_n.$ It this case, the structure of the Jacobian group will be

Xuan Wu, Xinhao Zhu, Yizheng Zhao, Xinyu Dai

Neural-symbolic computing aims at integrating robust neural learning and sound symbolic reasoning into a single framework, so as to leverage the complementary strengths of both of these, seemingly unrelated (maybe even contradictory) AI paradigms. The central challenge in neural-symbolic computing is to unify the formulation of neural learning and symbolic r

Sizhe Chen, Geng Yuan, Xinwen Cheng, Yifan Gong

As data becomes increasingly vital, a company would be very cautious about releasing data, because the competitors could use it to train high-performance models, thereby posing a tremendous threat to the company's commercial competence. To prevent training good models on the data, we could add imperceptible perturbations to it. Since such perturbations aim a

Susan Athey, Undral Byambadalai, Vitor Hadad, Sanath Kumar Krishnamurthy

We design and implement an adaptive experiment (a ``contextual bandit'') to learn a targeted treatment assignment policy, where the goal is to use a participant's survey responses to determine which charity to expose them to in a donation solicitation. The design balances two competing objectives: optimizing the outcomes for the subjects in the experiment (`

Nasser Alzahrani, Maria Spichkova, James Harland

Metamorphic testing (MT) is a general approach for the testing of a specific kind of software systems -- so-called ``non-testable'', where the ``classical'' testing approaches are difficult to apply. MT is an effective approach for addressing the test oracle problem and test case generation problem. The test oracle problem is when it is difficult to determin

Lin Lee Cheong, Tesfagabir Meharizghi, Wynona Black, Yang Guang

Recent advances in deep learning have led to interest in training deep learning models on longitudinal healthcare records to predict a range of medical events, with models demonstrating high predictive performance. Predictive performance is necessary but insufficient, however, with explanations and reasoning from models required to convince clinicians for su

Peter Wu, L. H. Ford, Enrico D. Schiappacasse

Observing physical effects of large quantum stress tensor fluctuations requires knowledge of the interactions between the probe and the particles of the underlying quantum fields. The quantum stress tensor operators must first be averaged in time alone or space and time to confer meaningful results, the details of which may correspond to the physical measure

Injy Hamed, Nizar Habash, Slim Abdennadher, Ngoc Thang Vu

We present our work on collecting ArzEn-ST, a code-switched Egyptian Arabic - English Speech Translation Corpus. This corpus is an extension of the ArzEn speech corpus, which was collected through informal interviews with bilingual speakers. In this work, we collect translations in both directions, monolingual Egyptian Arabic and monolingual English, forming

Kevin Liang

The presence of off-axis tilt and Petzval curvature, two of the lowest-order off-axis Seidel aberrations, is shown to improve the Fisher information of two-point separation estimation in an incoherent imaging system compared to an aberration-free system. Our results show that the practical localization advantages of modal imaging techniques within the field

Banibrata Mukhopadhyay, Mukul Bhattacharya

Over the past several years, there has been enormous interest in massive neutron stars and white dwarfs due to either their direct or indirect evidence. The recent detection of gravitational wave event GW190814 has confirmed the existence of compact stars with masses as high as $\sim2.5-2.67M_{\odot}$ within the so-called mass gap, indicating the existence o

Jinsun Liu, Yifei Shao, Lucas Lymburner, Hansen Qin

Performing real-time receding horizon motion planning for autonomous vehicles while providing safety guarantees remains difficult. This is because existing methods to accurately predict ego vehicle behavior under a chosen controller use online numerical integration that requires a fine time discretization and thereby adversely affects real-time performance.

Maosen Xu

In this paper, we classify the following simple $\mathbb{Z}$-graded Lie conformal algebras $\mathcal{L}=\bigoplus_{i\in \mathbb{Z}}\mathcal{L}_i$ such that (1)$rank\mathcal{L}_i\leq 1$, (2)$\mathcal{L}_0$ is the Virasoro Lie conformal algebra.

Yen-Jie Lee, Yu-Chen Chen, Yi Chen, Paoti Chang

We present the first measurement of two-particle angular correlations of charged particles produced in $e^+e^-$ annihilation up to $\sqrt{s}=$ 209 GeV. This analysis utilized the archived hadronic $e^+e^-$ data at center-of-mass energy between 91 and 209 GeV collected with the ALEPH detector at LEP between 1992 and 2000. The angular correlation functions are

Jiahui Liu, Hart Montgomery, Mark Zhandry

Public verification of quantum money has been one of the central objects in quantum cryptography ever since Wiesner's pioneering idea of using quantum mechanics to construct banknotes against counterfeiting. So far, we do not know any publicly-verifiable quantum money scheme that is provably secure from standard assumptions. In this work, we provide both neg

Alexandra L. Uitdenbogerd, Maria Spichkova, Mona Alzahrani

Many websites and other user interfaces include animated elements, particularly for advertisements. However, these can have a negative impact on users, with some cohorts, such as autistic users, being more affected. In our mixed methods study on the effect of irrelevant animations on usability we observed the effect on search activities. For those greatly im

Dan Zhu, Khai-Ming Wong, Guo-Quan Wong

We present the first numerical solution that corresponds to a pair of Cho-Maison monopole and antimonopole (MAP) in the SU(2)$\times$U(1) Weinberg-Salam (WS) theory. The monopoles are finitely separated, while each pole carries magnetic charge $\pm 4\pi/e$. The positive pole is situated in the upper hemisphere, whereas the negative pole is in the lower hemis

Brian C. Alden, Jack O. Burns

The first James Webb Space Telescope (JWST) image released was of galaxy cluster SMACSJ0723.3- 7327, a lensing cluster at z=0.39 showing detail only JWST can provide. While the majority of the focus has been on the brilliantly lensed galaxies at redshifts far beyond it, there is more to the story than it being just a lensing cluster. The Chandra X-ray temper

Nicholas Parsly, Jinning Wang, Nick West, Qiwei Zhang

This paper introduces the messaging environment and the geographical visualization tool of the CURENT Large-scale Testbed (LTB) that can be used for large-scale power system closed-loop simulation. First, Distributed Messaging Environment (DiME) implements an asynchronous shared workspace to enable high-concurrent data exchange. Second, Another Grid Visualiz

Wen-Chao Dong, Zhi-Gang Wang

Stimulated by the recent experimental progress on the $T_{\psi\psi}$ states, the fully charmed tetraquark spectroscopy is systemically investigated by dint of the Godfrey-Isgur relativized diquark model, the modified Godfrey-Isgur relativized diquark model with the color screening effects, and the nonrelativistic diquark model. The theoretical results of the

Zihao Lu, Fei Liu, Xianke Lin

This paper reviews vision-based localization methods in GPS-denied environments and classifies the mainstream methods into Relative Vision Localization (RVL) and Absolute Vision Localization (AVL). For RVL, we discuss the broad application of optical flow in feature extraction-based Visual Odometry (VO) solutions and introduce advanced optical flow estimatio

Andrè van Renssen, Yuan Sha, Yucheng Sun, Sampson Wong

Spanner construction is a well-studied problem and Delaunay triangulations are among the most popular spanners. Tight bounds are known if the Delaunay triangulation is constructed using an equilateral triangle, a square, or a regular hexagon. However, all other shapes have remained elusive. In this paper, we extend the restricted class of spanners for which

Jonathan Jedwab, Shuxing Li

The combination of the group ring setting with the methods of character theory allows an elegant and powerful analysis of various combinatorial structures, via their character sums. These combinatorial structures include difference sets, relative difference sets, partial difference sets, bent functions, hyperplanes, spreads, and LP-packings. However, the lit

Javier Cóppola, Andrea Solotar

We prove the graded braided commutativity of the Hochschild cohomology of $A$ with trivial coefficients, where $A$ is a braided Hopf algebra in the category of Yetter-Drinfeld modules over the group algebra of an abelian group, under some finiteness conditions on a projective resolution of $A$ as $A$-bimodule. This is a generalization of a result by Mastnak,

Shan-Shan Zhao, Lei Huang, Rusen Lu, Zhiqiang Shen

The Event Horizon Telescope (EHT), with $\sim$20 $\mu$as high angular resolution, recently resolved the millimeter image of the suppermassive black hole in the Galaxy, Sagittarius A*. This opens a new window to study the plasma on horizon scales. The accreting disk probably contains a small fraction of nonthermal electrons and their emissions should contribu

Zhongwei Qiu, Kai Qiu, Jianlong Fu, Dongmei Fu

Modern deep learning-based 3D pose estimation approaches require plenty of 3D pose annotations. However, existing 3D datasets lack diversity, which limits the performance of current methods and their generalization ability. Although existing methods utilize 2D pose annotations to help 3D pose estimation, they mainly focus on extracting 2D structural constrai

Guangsen Wang, Samson Tan, Shafiq Joty, Gang Wu

We present BotSIM, a data-efficient end-to-end Bot SIMulation toolkit for commercial text-based task-oriented dialog (TOD) systems. BotSIM consists of three major components: 1) a Generator that can infer semantic-level dialog acts and entities from bot definitions and generate user queries via model-based paraphrasing; 2) an agenda-based dialog user Simulat

Xiong-bin Yan, Zhi-Qin John Xu, Zheng Ma

Fractional diffusion equations have been an effective tool for modeling anomalous diffusion in complicated systems. However, traditional numerical methods require expensive computation cost and storage resources because of the memory effect brought by the convolution integral of time fractional derivative. We propose a Bayesian Inversion with Neural Operator

Sasmita Mishra, Urjit A. Yajnik

The growing evidence of gravitational waves from binary black hole mergers has renewed the interest in study of primordial black holes (PBH). Here we study a mechanism for the formation of PBH from collapse of pseudo-topological domain walls which form out of equilibrium during inflation and then collapse post inflation. We apply the study to domain wall for

Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Toyotaro Suzumura

Learning on evolving(dynamic) graphs has caught the attention of researchers as static methods exhibit limited performance in this setting. The existing methods for dynamic graphs learn spatial features by local neighborhood aggregation, which essentially only captures the low pass signals and local interactions. In this work, we go beyond current approaches

Jianfeng Lin, Ruikang Xiao, Miao Li, Xiaohui Xiao

The stiffness modulation mechanism for soft robotics has gained considerable attention to improve deformability, controllability, and stability. However, for the existing stiffness soft actuator, high lateral stiffness and a wide range of bending stiffness are hard to be provided at the same time. This paper presents a bioinspired bidirectional stiffening so

Junfeng Yu, Shaojie Shen

Loop closure can effectively correct the accumulated error in robot localization, which plays a critical role in the long-term navigation of the robot. Traditional appearance-based methods rely on local features and are prone to failure in ambiguous environments. On the other hand, object recognition can infer objects' category, pose, and extent. These objec

Jinniu Hu, Chencan Wang

As the residual interaction of quantum chromodynamics in low-energy region, the nucleon-nucleon (NN) potential can only be exactly described by the model picture now. In the Bonn potential, one of the most well-known NN interaction models, the nucleons interact with each other through exchanging the pion and several heavier mesons, where the pion plays an es

Tianping Zhang, Zheyu Zhang, Zhiyuan Fan, Haoyan Luo

The goal of automated feature generation is to liberate machine learning experts from the laborious task of manual feature generation, which is crucial for improving the learning performance of tabular data. The major challenge in automated feature generation is to efficiently and accurately identify effective features from a vast pool of candidate features.

Megh Manoj Bhalerao, Anurag Singh, Soma Biswas

Semi-supervised domain adaptation aims to classify data belonging to a target domain by utilizing a related label-rich source domain and very few labeled examples of the target domain. Here, we propose a novel framework, Pred&Guide, which leverages the inconsistency between the predicted and the actual class labels of the few labeled target examples to effec