July 2022 arXiv papers — page 21

Xin Cao, Jingzhong Yang, Pengji Li, Tom Fandrich

The surface of semiconductor nanostructures has a major impact on their electronic and optical properties. Disorder and defects in the surface layer typically cause degradation of charge carrier transport and radiative recombination dynamics. However, surface vicinity is inevitable for many scalable nano-optical applications. Epitaxially grown quantum dots a

Takuya Saito

A diffusive trajectory drawn by the generalized Langevin equation (GLE) for a colloidal particle evokes a random fractal of a static polymer configuration. This article proposes a static GLE-like description that enables the generation of a single configuration of a polymer chain with the noise formulated to satisfy the static fluctuation-response relation (

Zetian Qin, Yubai Li, Benye Niu, Qingyao Li

Under a low Signal-to-Noise Ratio (SNR), the Orthogonal Frequency-Division Multiplexing (OFDM) signal symbol rate is limited. Existing carrier number estimation algorithms lack adequate methods to deal with low SNR. This paper proposes an algorithm with a low error rate under low SNR by correlating the signal and applying a Fast Fourier Transform (FFT) opera

Joydev Lahiri, Debasis Atta, D. N. Basu

We address the issues of crustal properties of neutron stars such as crustal mass, crustal radius, crustal fraction of moment of inertia and investigate the crustal and structural properties related to the glitching mechanism observed in pulsars. The mass, radius and crustal fraction of moment of inertia in neutron stars have been determined using $\beta$-eq

Hongtao Wang, Hao Wang, Qifeng Ruan, John You En Chan

The orbital angular momentum (OAM) of light holds great promise for applications in optical communication, super-resolution imaging, and high-dimensional quantum computing. However, the spatio-temporal coherence of the light source has been essential for generating OAM beams, as incoherent ambient light would result in polychromatic and obscured OAM beams in

Renhao Xue, Jialei Tan, Yutao Shi

The recent upsurge of diversified mobile applications, especially those supported by AI, is spurring heated discussions on the future evolution of wireless communications. While 5G is being deployed around the world, efforts from industry and academia have started to look beyond 5G and conceptualize 6G. We envision 6G to experience an unprecedented transform

Oleg Mazonka

This paper describes a sufficiently simple modular multiplication algorithm, which uses only carry-save addition with bit inspection Boolean logic and without number comparison or carry propagation.

Mingjie Wang, Jianxiong Guo, Sirui Li, Dingwen Xiao

Deep neural networks have significantly advanced person re-identification (ReID) applications in the realm of the industrial internet, yet they remain vulnerable. Thus, it is crucial to study the robustness of ReID systems, as there are risks of adversaries using these vulnerabilities to compromise industrial surveillance systems. Current adversarial methods

Jingrun Chen, Xurong Chi, Weinan E, Zhouwang Yang

One of the oldest and most studied subject in scientific computing is algorithms for solving partial differential equations (PDEs). A long list of numerical methods have been proposed and successfully used for various applications. In recent years, deep learning methods have shown their superiority for high-dimensional PDEs where traditional methods fail. Ho

Gintaras Valiukevičius

We are checking the closed categories beginning with the category of sets and ending with the category of categories. The novelty is a generalizing the notion of adjoint functors to the joint pair of functors in the category of directed graphs. We have described for what condition we get a bijective name mapping for graphs transports. Graphs aren't instances

Xuanyu Yi, Kaihua Tang, Xian-Sheng Hua, Joo-Hwee Lim

Conventional de-noising methods rely on the assumption that all samples are independent and identically distributed, so the resultant classifier, though disturbed by noise, can still easily identify the noises as the outliers of training distribution. However, the assumption is unrealistic in large-scale data that is inevitably long-tailed. Such imbalanced t

Ehud de Shalit

For a lattice \Lambda in the complex plane, let K_{\Lambda} be the field of \Lambda-elliptic functions. For two relatively prime integers p (respectively q) greater than 1, consider the endomorphisms \psi (resp. \phi) of K_{\Lambda} given by multiplication by p (resp. q) on the elliptic curve \mathbb{C}/\Lambda. We prove that if f (resp. g) are complex Laure

Ding-Fu Shao, Shu-Hui Zhang, Rui-Chun Xiao, Zi-An Wang

Anomalous Hall effect (AHE) is a fundamental spin-dependent transport property that is widely used in spintronics. It is generally expected that currents carrying net spin polarization are required to drive the AHE. Here we demonstrate that, in contrast to this common expectation, a spin-neutral tunneling AHE (TAHE), i.e. a TAHE driven by spin-neutral curren

Vee-Liem Saw, Luca Vismara, Suryadi, Bo Yang

Predicting the origin-destination (OD) probability distribution of agent transfer is an important problem for managing complex systems. However, prediction accuracy of associated statistical estimators suffer from underdetermination. While specific techniques have been proposed to overcome this deficiency, there still lacks a general approach. Here, we propo

Yusheng Wang, Yunfan Lu, Ye Gao, Lin Wang

Video deblurring is a highly under-constrained problem due to the spatially and temporally varying blur. An intuitive approach for video deblurring includes two steps: a) detecting the blurry region in the current frame; b) utilizing the information from clear regions in adjacent frames for current frame deblurring. To realize this process, our idea is to de

Shu-Yu Ho

In this paper, we construct the first asymmetric strongly interacting massive particles (SIMP) dark matter (DM) model, where a new vector-like fermion and a new complex scalar both having nonzero chemical potentials can be asymmetric DM particles. After the spontaneous breaking of a U(1)$^{}_\textsf{D}$ dark gauge symmetry, these two particles can have accid

Arindam Das, Shinya Kanemura, Prasenjit Sanyal

We propose an anomaly free gauged U$(1)$ extension of the SM where three right handed heavy neutrinos, being charged under the general U$(1)$ gauge group, are introduced to explain the origin of the tiny neutrino mass through the seesaw mechanism after the general U$(1)$ symmetry is broken. Due to the breaking of the general U$(1)$ symmetry a neutral beyond

W. G. Parrott, C. Bouchard, C. T. H. Davies

We use HPQCD's recent lattice QCD determination of $B \to K$ scalar, vector and tensor form factors to determine Standard Model differential branching fractions for $B \to K \ell^+\ell^-$, $B\to K \ell_1^+\ell_2^-$ and $B \to K\nu \overline{\nu}$. These form factors are calculated across the full $q^2$ range of the decay and have smaller uncertainties than p

Mikiya Kusunoki, Shogo Yoshida, Haoran Xie

Recently, haptic gloves have been extensively explored for various practical applications, such as manipulation learning. Previous glove devices have different force-driven systems, such as shape memory alloys, servo motors and pneumatic actuators; however, these proposed devices may have difficulty in fast finger movement, easy reproduction, and safety issu

Priti Gupta, Takafumi Kakehi, Takahiro Tanaka

Extreme-mass-ratio inspirals (EMRIs) are promising target sources for space-based interferometers such as LISA, Taiji, and Tianqin. Depending on the astrophysical environment, such as close perturbers or an accretion disk, EMRI orbital evolution may deviate from the predictions of general relativity in vacuum. In particular, we focus on the resonance jumps,

Xiao-Long Wang, Min Fang, Yu Gao, Hong-Xin Zhang

Identifying the young optically visible population in a star-forming region is essential for fully understanding the star formation event. In this paper, We identify 211 candidate members of the Perseus molecular cloud based on Gaia astronomy. We use LAMOST spectra to confirm that 51 of these candidates are new members, bringing the total census of known mem

Camille Ruppli, Pietro Gori, Roberto Ardon, Isabelle Bloch

Current contrastive learning methods use random transformations sampled from a large list of transformations, with fixed hyperparameters, to learn invariance from an unannotated database. Following previous works that introduce a small amount of supervision, we propose a framework to find optimal transformations for contrastive learning using a differentiabl

Qing Zhao, Masaaki Kimura, Bo Zhou, Seung-heon Shin

The alpha clustering in the 10Be and 12Be has been studied within the framework of the real-time evolution method (REM). By using the effective interaction tuned to reproduce the charge radii and the threshold energies, we have evaluated the alpha reduced width amplitude (RWA) and spectroscopic factor (S-factor) for the ground and excited states. With severa

David Berghaus, Hartmut Monien, Danylo Radchenko

We present two approaches that can be used to compute modular forms on noncongruence subgroups. The first approach uses Hejhal's method for which we improve the arbitrary precision solving techniques so that the algorithm becomes about up to two orders of magnitude faster in practical computations. This allows us to obtain high precision numerical estimates

Xingzhi Zhou, Nevin L. Zhang

A deep clustering model conceptually consists of a feature extractor that maps data points to a latent space, and a clustering head that groups data points into clusters in the latent space. Although the two components used to be trained jointly in an end-to-end fashion, recent works have proved it beneficial to train them separately in two stages. In the fi

Nguyen Bin

In this note, we construct some minimal smooth surfaces of general type with canonical map of degree $ 13, 15, 17, 18, 21, 22 $. These surfaces are constructed as $ \mathbb{Z}_{3}^2$-covers of a blow-up of $ \mathbb{P}^1 \times \mathbb{P}^1 $.

Geng Chen, Si-Jie Liu, Yu-Jia Sun, Ge-Peng Ji

Camouflaged object detection (COD) aims to identify the objects that conceal themselves in natural scenes. Accurate COD suffers from a number of challenges associated with low boundary contrast and the large variation of object appearances, e.g., object size and shape. To address these challenges, we propose a novel Context-aware Cross-level Fusion Network (

Shalini Jain, Yashas Andaluri, S. VenkataKeerthy, Ramakrishna Upadrasta

The ever increasing memory requirements of several applications has led to increased demands which might not be met by embedded devices. Constraining the usage of memory in such cases is of paramount importance. It is important that such code size improvements should not have a negative impact on the runtime. Improving the execution time while optimizing for

Yang Liu, Jing Liu, Mengyang Zhao, Dingkang Yang

Video anomaly detection is a challenging task in the computer vision community. Most single task-based methods do not consider the independence of unique spatial and temporal patterns, while two-stream structures lack the exploration of the correlations. In this paper, we propose spatial-temporal memories augmented two-stream auto-encoder framework, which le

Hao-Hao Peng, Jian Deng, Sen-Yue Lou, Qun Wang

The dynamics of vortices in Bose-Einstein condensates of dilute cold atoms can be well formulated by Gross-Pitaevskii equation. To better understand the properties of vortices, a systematic method to solve the nonlinear differential equation for the vortex to a very high precision is proposed. Through two-point Pad$\acute{\text{e}}$ approximants, these solut

Tony Mroczkowski, Megan Donahue, Joshiwa van Marrewijk, Tracy E. Clarke

We present a multiwavelength study of RXC J2014.8-2430, the most extreme cool-core cluster in the Representative $XMM-Newton$ Cluster Structure Survey (REXCESS), using $Chandra$ X-ray, Southern Astrophysical Research (SOAR) Telescope, Atacama Large Millimeter/submillimeter Array (ALMA), Very Large Array (VLA), and Giant Metrewave Radio Telescope (GMRT) obser

Hasan Hassan, Ataberk Olgun, A. Giray Yaglikci, Haocong Luo

The memory controller is in charge of managing DRAM maintenance operations (e.g., refresh, RowHammer protection, memory scrubbing) to reliably operate modern DRAM chips. Implementing new maintenance operations often necessitates modifications in the DRAM interface, memory controller, and potentially other system components. Such modifications are only possib

Rami Ezzine, Moritz Wiese, Christian Deppe, Holger Boche

Over the past decades, the problem of communication over finite-state Markov channels (FSMCs) has been investigated in many researches and the capacity of FSMCs has been studied in closed form under the assumption of the availability of partial/complete channel state information at the sender and/or the receiver. In our work, we focus on infinite-state Marko

A. V. Antipov, E. O. Kiktenko, A. K. Fedorov

We describe a class of "neighboring-blocks" stabilizer quantum error correction codes and demonstrate that such class of codes can be implemented in a resource-efficient manner using a single ancilla and circular near-neighbor qubit connectivity. We propose an implementation for syndrome-measurement circuits for codes from the class and illustrate its workin

Yanping Lu

In this paper, we consider the statistical inference of the drift parameter $\theta$ of non-ergodic Ornstein-Uhlenbeck~(O-U) process driven by a general Gaussian process $(G_t)_{t\ge 0}$. When $H \in (0, \frac 12) \cup (\frac 12,1) $ the second order mixed partial derivative of $R (t, s) = E [G_t G_s] $ can be decomposed into two parts, one of which coincide

Mengsay Loem, Sho Takase, Masahiro Kaneko, Naoaki Okazaki

Impressive performance of Transformer has been attributed to self-attention, where dependencies between entire input in a sequence are considered at every position. In this work, we reform the neural $n$-gram model, which focuses on only several surrounding representations of each position, with the multi-head mechanism as in Vaswani et al.(2017). Through ex

Hongje Seong, Seoung Wug Oh, Brian Price, Euntai Kim

Recent studies made great progress in video matting by extending the success of trimap-based image matting to the video domain. In this paper, we push this task toward a more practical setting and propose One-Trimap Video Matting network (OTVM) that performs video matting robustly using only one user-annotated trimap. A key of OTVM is the joint modeling of t

Giacomo De Nicola, Victor H. Tuekam Mambou, Göran Kauermann

The COVID-19 pandemic brought upon a massive wave of disinformation, exacerbating polarization in the increasingly divided landscape of online discourse. In this context, popular social media users play a major role, as they have the ability to broadcast messages to large audiences and influence public opinion. In this paper, we make use of openly available

F. Ruppin, M. McDonald, J. Hlavacek-Larrondo, M. Bayliss

We analyze the cooling and feedback properties of 48 galaxy clusters at redshifts $0.4 < z < 1.3$ selected from the South Pole Telescope (SPT) catalogs to evolve like the progenitors of massive and well-studied systems at $z{\sim}0$. We estimate the radio power at the brightest cluster galaxy (BCG) location of each cluster from an analysis of Australia Teles

Benedikt Geuchen, Katharina Oberpriller, Thorsten Schmidt

In this work we consider one-dimensional generalized affine processes under the paradigm of Knightian uncertainty (so-called non-linear generalized affine models). This extends and generalizes previous results in Fadina et al. (2019) and L\"utkebohmert et al. (2022). In particular, we study the case when the payoff is allowed to depend on the path, like it i

Yuan Da Liao, Xiao Yan Xu, Zi Yang Meng, Yang Qi

Inspired by our recent works[1, 2] of SU(2) and SU(4) Dirac fermions subjected to plaquette interactions on square lattice, here we extend the large-scale quantum Monte Carlo investigations to the phase digram of correlated Dirac fermions with SU(6) and SU(8) symmetries subjected to the plaquette interaction on the same lattice. From SU(2) to SU(8), the rich

Anders Aufderhorst-Roberts, Sophie Cussons, David J. Brockwell, Lorna Dougan

Folded protein hydrogels are prime candidates as tuneable biomaterials but it is unclear to what extent their mechanical properties have mesoscopic, as opposed to molecular origins. To address this, we probe hydrogels of the muscle-derived protein $I27_5$, using a multimodal rheology approach. Across multiple protocols, the hydrogels consistently exhibit pow

Kangrou Guo, Eiichiro Kokubo

The presence of an early-formed giant planet in the protoplanetary disk has mixed influence on the growth of other planetary embryos. Gravitational perturbation from the planet can increase the relative velocities of planetesimals at the mean motion resonances to very high values and impede accretion at those locations. However, gas drag can also align the o

Misha Gromov

We approximate boundaries of convex polytopes by smooth hypersurfaces $Y=Y_\varepsilon$ with {\it positive mean curvatures} and, by using basic geometric relations between the scalar curvatures of Riemannin manifolds and the mean curvatures of their boundaries, establish {\it lower bound on the dihedral angles} of these polytopes.

Piotr Wzorek, Tomasz Kryjak

In recent years, event cameras (DVS - Dynamic Vision Sensors) have been used in vision systems as an alternative or supplement to traditional cameras. They are characterised by high dynamic range, high temporal resolution, low latency, and reliable performance in limited lighting conditions -- parameters that are particularly important in the context of adva

Rakesh John Amala Arokia Nathan, Indrajit Kurmi, Oliver Bimber

We present Inverse Airborne Optical Sectioning (IAOS) an optical analogy to Inverse Synthetic Aperture Radar (ISAR). Moving targets, such as walking people, that are heavily occluded by vegetation can be made visible and tracked with a stationary optical sensor (e.g., a hovering camera drone above forest). We introduce the principles of IAOS (i.e., inverse s

Dexun Li, Pradeep Varakantham

Restless multi-armed bandits (RMAB) is a framework for allocating limited resources under uncertainty. It is an extremely useful model for monitoring beneficiaries and executing timely interventions to ensure maximum benefit in public health settings (e.g., ensuring patients take medicines in tuberculosis settings, ensuring pregnant mothers listen to automat

Yu Xiang, Shuming Cheng, Qihuang Gong, Zbigniew Ficek

Einstein-Rosen-Podolsky (EPR) steering or quantum steering describes the "spooky-action-at-a-distance" that one party is able to remotely alter the states of the other if they share a certain entangled state. Generally, it admits an operational interpretation as the task of verifying entanglement without trust in the steering party's devices, making it lying

Victor Bouvier, Simona Maggio, Alexandre Abraham, Léo Dreyfus-Schmidt

If Uncertainty Quantification (UQ) is crucial to achieve trustworthy Machine Learning (ML), most UQ methods suffer from disparate and inconsistent evaluation protocols. We claim this inconsistency results from the unclear requirements the community expects from UQ. This opinion paper offers a new perspective by specifying those requirements through five down

Kwonyoung Kim, Jungin Park, Jiyoung Lee, Dongbo Min

Online stereo adaptation tackles the domain shift problem, caused by different environments between synthetic (training) and real (test) datasets, to promptly adapt stereo models in dynamic real-world applications such as autonomous driving. However, previous methods often fail to counteract particular regions related to dynamic objects with more severe envi

Zhanpeng Feng, Shiliang Zhang, Rinyoichi Takezoe, Wenze Hu

Active learning is an important technology for automated machine learning systems. In contrast to Neural Architecture Search (NAS) which aims at automating neural network architecture design, active learning aims at automating training data selection. It is especially critical for training a long-tailed task, in which positive samples are sparsely distribute

Zi-Ao Wang, Weishan Xue, Faguang Yan, Wenkai Zhu

Charge transfer plays a key role at the interfaces of heterostructures, which can affect electronic structures and ultimately the physical properties of the materials. However, charge transfer is difficult to manipulate externally once the interface formed. Here, we report electrically tunable charge transfer in Fe3GeTe2/Cr2Ge2Te6/Fe3GeTe2 all-magnetic van d

Xin Chen, Ke Ding

Recent advances of semantic image segmentation greatly benefit from deeper and larger Convolutional Neural Network (CNN) models. Compared to image segmentation in the wild, properties of both medical images themselves and of existing medical datasets hinder training deeper and larger models because of overfitting. To this end, we propose a novel two-stream U

Anton Baranov, Yurii Belov, Alexander Kuznetsov

We study the properties of a system biorthogonal to a complete and minimal system of exponentials in $L^2(E)$, where $E$ is a finite union of intervals, and show that in the case when $E$ is a union of two or three intervals the biorthogonal system is also complete.

Hutao Song, Hua Guo, Xiyong Zhang, Yapeng Wu

Permutation polynomials with coefficients 1 over finite fields attract researchers' interests due to their simple algebraic form. In this paper, we first construct four classes of fractional permutation polynomials over the cyclic subgroup of $ \mathbb{F}_{2^{2m}} $. From these permutation polynomials, three new classes of permutation polynomials with coeffi

Chuncheng Zhang, Zheyi Yao, Zhengyue Qin, Guohua Gu

Multimode fibres offer the advantages of high resolution and miniaturization over single mode fibers in the field of optical imaging. However, multimode fibre's imaging is susceptible to perturbations of MMF that can lead to secondary spatial distortions in the transmitted image. Perturbations include random disturbances in the fiber as well as environmental

Madhavaraj A, Bharathi Pilar, Ramakrishnan A G

In this paper, we present specially designed automatic speech recognition (ASR) systems for the highly agglutinative and inflective languages of Tamil and Kannada that can recognize unlimited vocabulary of words. We use subwords as the basic lexical units for recognition and construct subword grammar weighted finite state transducer (SG-WFST) graphs for word

Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, Ronan Le Bras

We introduce REALTIME QA, a dynamic question answering (QA) platform that announces questions and evaluates systems on a regular basis (weekly in this version). REALTIME QA inquires about the current world, and QA systems need to answer questions about novel events or information. It therefore challenges static, conventional assumptions in open-domain QA dat

Madhavaraj A, Bharathi Pilar, Ramakrishnan A G

We present automatic speech recognition (ASR) systems for Tamil and Kannada based on subword modeling to effectively handle unlimited vocabulary due to the highly agglutinative nature of the languages. We explore byte pair encoding (BPE), and proposed a variant of this algorithm named extended-BPE, and Morfessor tool to segment each word as subwords. We have

Piotr Graczyk, Hideyuki Ishi, Bartosz Kołodziejek

We consider multivariate centered Gaussian models for the random vector $(Z^1,\ldots, Z^p)$, whose conditional structure is described by a homogeneous graph and which is invariant under the action of a permutation subgroup. The following paper concerns with model selection within colored graphical Gaussian models, when the underlying conditional dependency g

Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang

E-commerce has gone a long way in empowering merchants through the internet. In order to store the goods efficiently and arrange the marketing resource properly, it is important for them to make the accurate gross merchandise value (GMV) prediction. However, it's nontrivial to make accurate prediction with the deficiency of digitized data. In this article, w

Labh Singh, Tapender, Monal Kashav, Surender Verma

The trimaximal mixing scheme (TM$_2$) results in \textit{``magic"} neutrino mass matrix ($M_\nu$) which is known to accommodate neutrino oscillation data. In this paper, we propose a phenomenological ansatz for $M_\nu$ by extending the magic symmetry that leads to further reduction in the number of free parameters, thereby, increasing the predictability of t

Liang Li, Lu Guo, K. Godbey, A. S. Umar

Quantum shell effects drive many aspects of many-body quantal systems and their interactions. Among these are the quasifission reactions that impede the formation of a compound nucleus in superheavy element (SHE) searches. Fragment production in quasifission is influenced by shell effects as a nontrivial manifestation of microscopic dynamics hindering the fu

Daizong Liu, Wei Hu, Xin Li

With the increasing attention in various 3D safety-critical applications, point cloud learning models have been shown to be vulnerable to adversarial attacks. Although existing 3D attack methods achieve high success rates, they delve into the data space with point-wise perturbation, which may neglect the geometric characteristics. Instead, we propose point c

Mengxue Qu, Yu Wu, Wu Liu, Qiqi Gong

In this paper, we investigate how to achieve better visual grounding with modern vision-language transformers, and propose a simple yet powerful Selective Retraining (SiRi) mechanism for this challenging task. Particularly, SiRi conveys a significant principle to the research of visual grounding, i.e., a better initialized vision-language encoder would help

Hanpu Liu, Gregory J. Herczeg, Doug Johnstone, Carlos Contreras-Peña

FU Ori type objects (FUors) are decades-long outbursts of accretion onto young stars that are strong enough to viscously heat disks so that the disk outshines the central star. We construct models for FUor objects by calculating emission components from a steady-state viscous accretion disk, a passively-heated dusty disk, magnetospheric accretion columns, an

A. Sagalovych, S. Dudnik, V. Sagalovych

The investigations of the reactive magnetron depositing of the stoichiometric coatings metal-metalloid were done. The dependences between sputtering parameters of a target and processes of plasmochemical formation on the surface of sample metal-metalloid and formations of coatings of the appropriate structure were investigated. Experimental data on stoichiom

Robbe de Mey, Spencer W. Jolly, Alexandre Locquet, Martin Virte

We experimentally study a semiconductor laser subject to two optical feedbacks in a free space setup. We show that the time delay signature, manifesting itself in the chaotic output intensity, can be better suppressed than in a laser with single feedback. We demonstrate that the control of the feedback phase is essential to suppress the time delay signature,

Abhishek Chakraborty, Daniel Xing, Yuntao Liu, Ankur Srivastava

The functionality of a deep learning (DL) model can be stolen via model extraction where an attacker obtains a surrogate model by utilizing the responses from a prediction API of the original model. In this work, we propose a novel watermarking technique called DynaMarks to protect the intellectual property (IP) of DL models against such model extraction att

Gayoung Lee, Hyunsu Kim, Junho Kim, Seonghyeon Kim

Recent methods for conditional image generation benefit from dense supervision such as segmentation label maps to achieve high-fidelity. However, it is rarely explored to employ dense supervision for unconditional image generation. Here we explore the efficacy of dense supervision in unconditional generation and find generator feature maps can be an alternat

Paul Glasserman, Mike Li

Regulatory stress tests have become one of the main tools for setting capital requirements at the largest U.S. banks. The Federal Reserve uses confidential models to evaluate bank-specific outcomes for bank-specific portfolios in shared stress scenarios. As a matter of policy, the same models are used for all banks, despite considerable heterogeneity across

Prateek Dwivedi, Atishay Shrivastava, Dipin Pillai, Rahul Mangal

Typical bodily and environmental fluids encountered by biological swimmers consist of dissolved macromolecules such as proteins and polymers, often rendering them non Newtonian. To mimic such scenarios, we investigate the motion of swimming droplets in an ambient medium doped with polymers as macromolecular solutes. Active droplets mimic the essential propul

Cong Wang, Hongmin Xu, Xiong Zhang, Li Wang

Vision Transformers (ViTs) have recently dominated a range of computer vision tasks, yet it suffers from low training data efficiency and inferior local semantic representation capability without appropriate inductive bias. Convolutional neural networks (CNNs) inherently capture regional-aware semantics, inspiring researchers to introduce CNNs back into the

Lin Li, Jun Xiao, Hanrong Shi, Hanwang Zhang

Nearly all existing scene graph generation (SGG) models have overlooked the ground-truth annotation qualities of mainstream SGG datasets, i.e., they assume: 1) all the manually annotated positive samples are equally correct; 2) all the un-annotated negative samples are absolutely background. In this paper, we argue that neither of the assumptions applies to

Yixuan Fan, Zhaopeng Dou, Yali Li, Shengjin Wang

We propose a task we name Portrait Interpretation and construct a dataset named Portrait250K for it. Current researches on portraits such as human attribute recognition and person re-identification have achieved many successes, but generally, they: 1) may lack mining the interrelationship between various tasks and the possible benefits it may bring; 2) desig

Philipp König, Thomas Richthammer

Let $X_n, n \ge 0$ be a Markov chain with finite state space $M$. If $x,y \in M$ such that $x$ is transient we have $P^y(X_n = x) \to 0$ for $n \to \infty$, and under mild aperiodicity conditions this convergence is monotone in that for some $N$ we have $\forall n \ge N: P^y(X_n = x)$ $\ge P^y(X_{n+1} = x)$. We use bounds on the rate of convergence of the Ma

Grace H. Wolff, Cuihua Shen

This study examines how active participation, financial commitment, and passive participation in the leading social live-streaming service, Twitch.tv, relate to individuals' psychological well-being. The three dimensions of social capital-structural, relational, and cognitive-as well as parasocial relationship are explored as mediators. Cross-sectional surve

Siddharth Iyer, Michael Whitmeyer

Given a function $f$ on $\mathbb{F}_2^n$, we study the following problem. What is the largest affine subspace $\mathcal{U}$ such that when restricted to $\mathcal{U}$, all the non-trivial Fourier coefficients of $f$ are very small? For the natural class of bounded Fourier degree $d$ functions $f:\mathbb{F}_2^n \to [-1,1]$, we show that there exists an affine

Xin Zhao, Zhiwei Fang, Yuchen Guo, Jie He

A combinatorial recommender (CR) system feeds a list of items to a user at a time in the result page, in which the user behavior is affected by both contextual information and items. The CR is formulated as a combinatorial optimization problem with the objective of maximizing the recommendation reward of the whole list. Despite its importance, it is still a

Tyler E. Maltba, Vishwas Rao, Daniel Adrian Maldonado

A machine learning technique is proposed for quantifying uncertainty in power system dynamics with spatiotemporally correlated stochastic forcing. We learn one-dimensional linear partial differential equations for the probability density functions of real-valued quantities of interest. The method is suitable for high-dimensional systems and helps to alleviat

Donglin Xie, Ruonan Yu, Gongfan Fang, Jie Song

In this paper, we explore a new knowledge-amalgamation problem, termed Federated Selective Aggregation (FedSA). The goal of FedSA is to train a student model for a new task with the help of several decentralized teachers, whose pre-training tasks and data are different and agnostic. Our motivation for investigating such a problem setup stems from a recent di

Alejandro R. Urzúa, Kurt Bernardo Wolf

Using the coefficients introduced by Bargmann and Moshinsky for the reduction of the su($3$) algebra of Cartesian three-dimensional oscillator multiplet states into so($3$) angular momentum submultiplets, we implement unitary rotations of three-dimensional Cartesian arrays that form finite pixellated "volume images." Transforming between the Cartesian and sp

Loïc Paulevé

Boolean networks (BNs) are discrete dynamical systems with applications to the modeling of cellular behaviors. In this paper, we demonstrate how the software BoNesis can be employed to exhaustively identify combinations of perturbations which enforce properties on their fixed points and attractors. We consider marker properties, which specify that some compo

Tomoya Nitta, Tsubasa Hirakawa, Hironobu Fujiyoshi, Toru Tamaki

In this paper we propose an extension of the Attention Branch Network (ABN) by using instance segmentation for generating sharper attention maps for action recognition. Methods for visual explanation such as Grad-CAM usually generate blurry maps which are not intuitive for humans to understand, particularly in recognizing actions of people in videos. Our pro

Harshita Raj, C. Theiler, A. Thornton, O. Fevrier

Nitrogen seeded detachment has been achieved in the Tokamak a Configuration Variable (TCV) in advanced divertor configurations (ADCs), namely X-divertor and X-point target, with and without baffles in H-mode plasmas with high core confinement. Both ADCs show a remarkable reduction in the inter-ELM particle and heat fluxes to the target compared to the standa

Abhishek Mukherjee, Juan Carlos Cajas, Guillaume Houzeaux, Oriol Lehmkuhl

Communities around the world are increasingly interested in nature-based solutions to mitigation of coastal risks like coastal forests, but it remains unclear how much protective benefits vegetation provides, particularly in the limit of highly energetic flows after tsunami impact. The current study, using a three-dimensional incompressible computational flu

Mikhail Altaisky, Robin Raj

We present a model showing that our four-dimensional spacetime with the signature $(+,-,-,-)$ and almost vanishing positive curvature may have originated from a $b$-ary tree-like branching of a single discrete entity, and the $AdS_5$ space related to this branching process.

Naoki Kitazawa

Morse functions with exactly two singular points on spheres and canonical projections of spheres belong to the class of a certain good class of smooth maps: special generic maps. We mainly investigate information on cohomology of closed and simply-connected manifolds admitting such maps into the $5$-dimensional Euclidean spaces by investigating the embedded

Almas Sadreev, Evgeny Bulgakov, Artem Pilipchuk, Andrey Miroshnichenko

We consider square and equilateral triangular open acoustic resonators with the $C_{4v}$ and $C_{3v}$ symmetries, respectively. There is an unique property of square and triangular resonators of accidental number four-fold degeneracy of eigenstates that gives rise to two-fold degenerate Friedrich-Wintgen (FW) BICs. Compared to usual FW BICs the degenerate FW

Samik Basu, Bikramjit Kundu

In this paper, we consider the flag manifold of $p$ orthogonal subspaces of equal dimension which carries an action of the cyclic group of order $p$. We provide a complete calculation of the associated Fadell-Husseini index. This may be thought of as an odd primary version of the computations of Barali\'c et al [Forum Math., 30 (2018), pp. 1539--1572] for th

Taizo Suzuki, Seisuke Kyochi, Yuichi Tanaka

This letter proposes a fast implementation of the regularity-constrained discrete sine transform (R-DST). The original DST \textit{leaks} the lowest frequency (DC: direct current) components of signals into high frequency (AC: alternating current) subbands. This property is not desired in many applications, particularly image processing, since most of the fr

Yinhe Peng, Guozhen Shen, Liuzhen Wu

It is shown that the existence of an infinite set $A$ such that $A^2$ maps onto $2^A$ is consistent with $\mathsf{ZF}$.

Hiroki Ohata, Hideo Suganuma

Aiming at the relation between QCD and the quark model, we consider projections of gauge configurations generated in quenched lattice QCD simulations in the Coulomb gauge on a 16$^{\rm 3}$ $\rm \times$ 32, $\rm \beta$ = 6.0 lattice. First, we focus on a fact that the static quark-antiquark potential is independent of spatial gauge fields. We explicitly confi

François Hug, Simon Avrillon, Jaime Ibáñez, Dario Farina

Understanding how movement is controlled by the central nervous system remains a major challenge, with ongoing debate about basic features underlying this control. In this review, we introduce a new conceptual framework for the distribution of common input to spinal motor neurons. Specifically, this framework is based on the following assumptions: 1) motor n

Mukund Varma T, Peihao Wang, Xuxi Chen, Tianlong Chen

We present Generalizable NeRF Transformer (GNT), a transformer-based architecture that reconstructs Neural Radiance Fields (NeRFs) and learns to renders novel views on the fly from source views. While prior works on NeRFs optimize a scene representation by inverting a handcrafted rendering equation, GNT achieves neural representation and rendering that gener

Ladislaus Alexander Bányai, Mircea Bundaru

We describe here the coherent formulation of electromagnetism in the non-relativistic quantum-mechanical many-body theory of interacting charged particles. We use the mathematical frame of the field theory and its quantization in the spirit of the QED. This is necessary because a manifold of misinterpretations emerged especially regarding the magnetic field

Hongjae Lee, Changwoo Han, Jun-Sang Yoo, Seung-Won Jung

Semantic segmentation for autonomous driving should be robust against various in-the-wild environments. Nighttime semantic segmentation is especially challenging due to a lack of annotated nighttime images and a large domain gap from daytime images with sufficient annotation. In this paper, we propose a novel GPS-based training framework for nighttime semant

Chenguang Li, Bo Xiong, Tao Chu

Polarization-compatible receivers are indispensable in transceivers used for wavelength division multiplexing (WDM) optical communications, as light polarization is unpredictable after transmission through network fibers. However, the strong waveguide birefringence makes it difficult to realize a polarization-independent wavelength demultiplexer in a silicon

Ralph Joseph S. D. Ligueran, Manuel Luis C. Delos Santos, Ronaldo S. Tinio, Emmanuel H. Valencia

This study focuses on the application of a specific subfield of artificial intelligence referred to as computer vision in the analysis of 2-dimensional lung x-ray images for the assisted medical diagnosis of ordinary pneumonia. A convolutional neural network algorithm was implemented in a Python-coded, Flask-based web application that can analyze x-ray image

Ivan Gonzalez Garcia, Jesus Jeronimo Castro, Diana Janett Verdusco Hernandez, Efren Morales Amaya

In this paper we proved the following: \emph{Let $K, L\subset \mathbb R^3$ be two $O$-symmetric convex bodies with $L\subset \emph{int} K$ strictly convex. Suppose that from every $x$ in $\emph{bd} K$ the graze $\Sigma(L,x)$ is a planar curve and $K$ is almost free with respect to $L$. Then $L$ is an ellipsoid.}