March 2023 arXiv papers — page 140

Kai Pfeiffer, Adrien Escande, Pierre Gergondet, Abderrahmane Kheddar

This work links optimization approaches from hierarchical least-squares programming to instantaneous prioritized whole-body robot control. Concretely, we formulate the hierarchical Newton's method which solves prioritized non-linear least-squares problems in a numerically stable fashion even in the presence of kinematic and algorithmic singularities of the a

Yusuke Mukuta, Tatsuya Harada

This paper proposes a method to construct pretext tasks for self-supervised learning on group equivariant neural networks. Group equivariant neural networks are the models whose structure is restricted to commute with the transformations on the input. Therefore, it is important to construct pretext tasks for self-supervised learning that do not contradict th

Nicolas Heist, Heiko Paulheim

Entity Linking (EL) is the task of detecting mentions of entities in text and disambiguating them to a reference knowledge base. Most prevalent EL approaches assume that the reference knowledge base is complete. In practice, however, it is necessary to deal with the case of linking to an entity that is not contained in the knowledge base (NIL entity). Recent

Abhishikta Das, Hijaz Ahmad, T. Bag

The objective of this work is the construction of `Boyd-Wong fixed point theorem' in the setting of generalized parametric metric space and discussion its application on existence criteria of solutions to a second order initial value problem. Also an analogue of `Banach type fixed point theorem of generalized parametric metric space is proved and its applica

Yudai Kobayashi, Daisuke Takaishi, Yusuke Tsukamoto

We study the formation and early evolution of young stellar objects (YSOs) using three-dimensional non-ideal magnetohydrodynamic (MHD) simulations to investigate the effect of cosmic ray ionization rate and dust fraction (or amount of dust grains) on circumstellar disk formation. Our simulations show that a higher cosmic ray ionization rate and a lower dust

Justus Renkhoff, Wenkai Tan, Alvaro Velasquez, illiam Yichen Wang

Deep Learning (DL) is being applied in various domains, especially in safety-critical applications such as autonomous driving. Consequently, it is of great significance to ensure the robustness of these methods and thus counteract uncertain behaviors caused by adversarial attacks. In this paper, we use gradient heatmaps to analyze the response characteristic

V. O. Manturov, I. M. Nikonov

Using the recoupling theory, we define a representation of the pure braid group and show that it is not trivial.

Zhi-Cheng Shi, Cheng Zhang, Li-Tuo Shen, Jie Song

We propose a concatenated approach for implementing transitionless quantum driving regardless of adiabatic conditions while being robustness with respect to all kinds of systematic errors induced by pulse duration, pulse amplitude, detunings, and Stark shift, etc. The current approach is particularly efficient for all time-dependent pulses with arbitrary sha

Xiaopeng Cheng, Ilje Cho, Tomohisa Kawashima, Motoki Kino

In this work, we studied the Galactic Center supermassive black hole (SMBH), Sagittarius A* (Sgr A*), with the KVN and VERA Array (KaVA)/East Asian VLBI Network (EAVN) monitoring observations. Especially on 13 May 2019, Sgr A* experienced an unprecedented bright near infra-red (NIR) flare; so, we find a possible counterpart at 43 GHz (7 mm). As a result, a l

S. S. Afonin, T. D. Solomko

We consider the soft-wall holographic model with the linear dilaton background. The model leads to a Hydrogen-like meson spectrum which can be interpreted as the static limit with very large quark masses when the Coulomb interaction dominates. The mass scale introduced by the linear dilaton is matched to the quark mass. The resulting model is analyzed for th

Dennis Gallenmüller, Raphael Wagner, Emil Wiedemann

Fluids can behave in a highly irregular, turbulent way. It has long been realised that, therefore, some weak notion of solution is required when studying the fundamental partial differential equations of fluid dynamics, such as the compressible or incompressible Navier-Stokes or Euler equations. The standard concept of weak solution (in the sense of distribu

Sevim Cengiz, Ibrahim Almakky, Mohammad Yaqub

Deep learning models have been effective for various fetal ultrasound segmentation tasks. However, generalization to new unseen data has raised questions about their effectiveness for clinical adoption. Normally, a transition to new unseen data requires time-consuming and costly quality assurance processes to validate the segmentation performance post-transi

Abdu Saif, Kamarul Ariffin bin Noordin, Kaharudin Dimyati, Nor Shahida Mohd Shah

Device-to-Device (D2D) communication is one of the enabling technologies for 5G networks that support proximity-based service (ProSe) for wireless network communications. This paper proposes a power control algorithm based on the Nash equilibrium and game theory to eliminate the interference between the cellular user device and D2D links. This leads to relia

A. Bagheri Tudeshki, G. H. Bordbar, B. Eslam Panah

The presence of massive gravitons in the field of massive gravity is considered as an important factor in investigating the structure of compact objects. Hence, we are encouraged to study the dark energy star structure in the Vegh's massive gravity. We consider that the equation of state governing the inner spacetime of the star is the extended Chaplygin gas

Qizhao Chen, Morgane Austern, Vasilis Syrgkanis

Estimating optimal dynamic policies from offline data is a fundamental problem in dynamic decision making. In the context of causal inference, the problem is known as estimating the optimal dynamic treatment regime. Even though there exists a plethora of methods for estimation, constructing confidence intervals for the value of the optimal regime and structu

Zhao-Qing Feng

The hyperon dynamics in heavy-ion collisions near threshold energy has been investigated within the quantum molecular dynamics transport model. The isospin and momentum dependent hyperon-nucleon potential and the threshold energy correction on the hyperon elementary cross section are included in the model. It is found that the high-density symmetry energy is

Malong Ke, Zhen Gao, Mingyu Zhou, Dezhi Zheng

This paper proposes a unified semi-blind detection framework for sourced and unsourced random access (RA), which enables next-generation ultra-reliable low-latency communications (URLLC) with massive devices. Specifically, the active devices transmit their uplink access signals in a grant-free manner to realize ultra-low access latency. Meanwhile, the base s

Yang Cheng, Zhen Chen, Daming Liu

Power line detection is a critical inspection task for electricity companies and is also useful in avoiding drone obstacles. Accurately separating power lines from the surrounding area in the aerial image is still challenging due to the intricate background and low pixel ratio. In order to properly capture the guidance of the spatial edge detail prior and li

P. Wiseman, Y. Wang, S. Hönig, N. Castro-Segura

We present observations from X-ray to mid-infrared wavelengths of the most energetic non-quasar transient ever observed, AT2021lwx. Our data show a single optical brightening by a factor $>100$ to a luminosity of $7\times10^{45}$ erg s$^{-1}$, and a total radiated energy of $1.5\times10^{53}$ erg, both greater than any known optical transient. The decline is

Galen T. Craven, Abraham Nitzan

The realization of single-molecule thermal conductance measurements has driven the need for theoretical tools to describe conduction processes that occur over atomistic length scales. In macroscale systems, the principle that is typically used to understand thermal conductivity is Fourier's law. At molecular length scales, however, deviations from Fourier's

Piper Fowler-Wright, Kristín B. Arnardóttir, Peter Kirton, Brendon W. Lovett

For a model with many-to-one connectivity it is widely expected that mean-field theory captures the exact many-particle $N\to\infty$ limit, and that higher-order cumulant expansions of the Heisenberg equations converge to this same limit whilst providing improved approximations at finite $N$. Here we show that this is in fact not always the case. Instead, wh

Olivier Ramaré

The quadratic form $V(\varphi,Q)=\sum_{q\sim Q}\sum_{a\mod^* q}|S(\varphi,a/q)|^2$ and its eigenvalues are well understood when $Q=o(\sqrt{N})$, while $V(\varphi,Q)$ is expected to behave like a Riemann sum when $N=o(Q)$. The behavior in the range $Q\in[\sqrt{N},100 N]$ is still mysterious. In the present work we present a full spectral analysis when $Q\ge N

Shirun Shen, Huiya Zhou, Kejun He, Lan Zhou

In this paper, we propose a novel model to analyze serially correlated two-dimensional functional data observed sparsely and irregularly on a domain which may not be a rectangle. Our approach employs a mixed effects model that specifies the principal component functions as bivariate splines on triangulations and the principal component scores as random effec

Shanshan Liu, Liangyun Chen

In this paper, we use the higher derived bracket to give the controlling algebra of pre-LieDer pairs. We give the cohomology of pre-LieDer pairs by using the twist $L_\infty$-algebra of this controlling algebra. In particular, we define the cohomology of regular pre-LieDer pairs. We study infinitesimal deformations of pre-LieDer pairs, which are characterize

Sorb Yesudhas, Valery I. Levitas, Feng Lin, K. K. Pandey

Pressure-induced phase transformations (PTs) between numerous phases of Si, the most important electronic material, have been studied for decades. This is not the case for plastic strain-induced PTs. Here, we revealed in-situ various unexpected plastic strain-induced PT phenomena. Thus, for 100 nm Si, strain-induced PT Si-I to Si-II (and Si-I to Si-III) init

Bohang Zhang, Zhaoujun Nan, Sheng Zhou, Zhisheng Niu

The introduction of 5G has changed the wireless communication industry. Whereas previous generations of cellular technology are mainly based on communication for people, the wireless industry is discovering that 5G may be an era of communications that is mainly focused on machine-to-machine communication. The application of Ultra Reliable Low Latency Communi

Minseok Seo, Yeji Choi, Hyungon Ry, Heesun Park

Geostationary satellite imagery has applications in climate and weather forecasting, planning natural energy resources, and predicting extreme weather events. For precise and accurate prediction, higher spatial and temporal resolution of geostationary satellite imagery is important. Although recent geostationary satellite resolution has improved, the long-te

Shixiong Qi, Ziteng Zeng, Leslie Monis, K. K. Ramakrishnan

Traditional network resident functions (e.g., firewalls, network address translation) and middleboxes (caches, load balancers) have moved from purpose-built appliances to software-based components. However, L2/L3 network functions (NFs) are being implemented on Network Function Virtualization (NFV) platforms that extensively exploit kernel-bypass technology.

X. Yang, Y. Tian, I. Schicker, A. Jung

The current fossil fuel and climate crisis has led to an increased demand for renewable energy sources, such as wind power. In northern Europe, the efficient use of wind power is crucial for achieving carbon neutrality. To assess the potential of wind energy for private households in Finland, we have conducted a high spatiotemporal resolution analysis. Our m

Maicon J. Karling, Marc G. Genton, Simos G. Meintanis

We employ a general Monte Carlo method to test composite hypotheses of goodness-of-fit for several popular multivariate models that can accommodate both asymmetry and heavy tails. Specifically, we consider weighted L2-type tests based on a discrepancy measure involving the distance between empirical characteristic functions and thus avoid the need for employ

Chang-Long Yao

We consider isoperimetric sets, i.e., sets with minimal vertex boundary for a prescribed volume, of the infinite cluster of supercritical site percolation on the triangular lattice. Let $p$ be the percolation parameter and let $p_c$ be the critical point. By adapting the proof of Biskup, Louidor, Procaccia and Rosenthal [6] for isoperimetry in bond percolati

Eliot Jane Walton

An analysis of barriers to women's participation in physics education is presented. It is expected that in undergraduate physics the most common situation for a women is that she is cisgender and one of a numerical minority in the classroom. The effects of other intersectional identities are not considered. The analysis is based on evidence from the author's

Sayantani Datta

The Laser Interferometer Space Antenna (LISA) will provide us with a unique opportunity to observe the early inspiral phase of supermassive binary black holes (SMBBHs) in the mass range of $10^5-10^6\,M_{\odot}$, that lasts for several years. It will also detect the merger and ringdown phases of these sources. Therefore, such sources are extremely useful for

Go-Eum Cha, Wonse Jo, Byung-Cheol Min

This paper explores how the personality traits of robot operators can influence their task performance during remote control of robots. It is essential to explore the impact of personal dispositions on information processing, both directly and indirectly, when working with robots on specific tasks. To investigate this relationship, we utilize the open-access

Eren Mehmet Kıral, Thomas Möllenhoff, Mohammad Emtiyaz Khan

The Bayesian Learning Rule provides a framework for generic algorithm design but can be difficult to use for three reasons. First, it requires a specific parameterization of exponential family. Second, it uses gradients which can be difficult to compute. Third, its update may not always stay on the manifold. We address these difficulties by proposing an exte

Takuya Asayama

A perfect field $K$ is said to be Kummer-faithful if the Mordell-Weil group of every semi-abelian variety over every finite extension of $K$ has no nonzero divisible element. The class of Kummer-faithful fields contains that of sub-$p$-adic fields and is thought to be suitable for developing anabelian geometry. In this paper, we investigate a function field

Chen Qian, Yongchun Fang, Fan jia, Jifu Yan

Tried-and-true flapping wing robot simulation is essential in developing flapping wing mechanisms and algorithms. This paper presents a novel application-oriented flapping wing platform, highly compatible with various mechanical designs and adaptable to different robotic tasks. First, the blade element theory and the quasi-steady model are put forward to com

Sebastian M. Dawid, Md Habib E Islam, Raúl A. Briceño

We investigate the relativistic scattering of three identical scalar bosons interacting via pair-wise interactions. Extending techniques from the non-relativistic three-body scattering theory, we provide a detailed and general prescription for solving and analytically continuing integral equations describing the three-body reactions. We use these techniques

Jinghan Ru, Jun Tian, Zhekai Du, Chengwei Xiao

Multimedia applications are often associated with cross-domain knowledge transfer, where Unsupervised Domain Adaptation (UDA) can be used to reduce the domain shifts. Open Set Domain Adaptation (OSDA) aims to transfer knowledge from a well-labeled source domain to an unlabeled target domain under the assumption that the target domain contains unknown classes

Amaael Antonini, Rita Gimelshein, Richard Wesel

Horstein, Burnashev, Shayevitz and Feder, Naghshvar et al. and others have studied sequential transmission of a K-bit message over the binary symmetric channel (BSC) with full, noiseless feedback using posterior matching. Yang et al. provide an improved lower bound on the achievable rate using martingale analysis that relies on the small-enough difference (S

Xinming Wu, Ji Dai

Reading emotions precisely from segments of neural activity is crucial for the development of emotional brain-computer interfaces. Among all neural decoding algorithms, deep learning (DL) holds the potential to become the most promising one, yet progress has been limited in recent years. One possible reason is that the efficacy of DL strongly relies on train

Karthik Gangavarapu, Xiang Ji, Guy Baele, Mathieu Fourment

The rapid growth in genomic pathogen data spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters of these phylogenetic models where the dimensions of the parameters increase with the number of sequences $N$. HMC requires repeated calculation of the gradient of the data log-like

Jeong-Ho Lee, Zhizhou Zhang, Grace X. Gu

Dynamic homogenization theories are powerful tools for describing and understanding the behavior of heterogeneous media such as composites and metamaterials. However, a major challenge in the dynamic homogenization theory is determining Green's function of these media, which makes it difficult to predict their effective constitutive relations, particularly f

Hector D. Perez, Shivank Joshi, Ignacio E. Grossmann

We present a Julia package, DisjunctiveProgramming.jl, that extends the functionality in JuMP.jl to allow modeling problems via logical propositions and disjunctive constraints. Such models can then be reformulated into Mixed-Integer Programs (MIPs) that can be solved with the various MIP solvers supported by JuMP. To do so, logical propositions are converte

He Zhu, Ren Togo, Takahiro Ogawa, Miki Haseyama

We present a novel multimodal interpretable VQA model that can answer the question more accurately and generate diverse explanations. Although researchers have proposed several methods that can generate human-readable and fine-grained natural language sentences to explain a model's decision, these methods have focused solely on the information in the image.

S. Husremović, B. H. Goodge, M. Erodici, K. Inzani

High-density phase change memory (PCM) storage is proposed for materials with multiple intermediate resistance states, which have been observed in 1$T$-TaS$_2$ due to charge density wave (CDW) phase transitions. However, the metastability responsible for this behavior makes the presence of multistate switching unpredictable in TaS$_2$ devices. Here, we demon

Yan Li, Guanghui Lan

Explicit exploration in the action space was assumed to be indispensable for online policy gradient methods to avoid a drastic degradation in sample complexity, for solving general reinforcement learning problems over finite state and action spaces. In this paper, we establish for the first time an $\tilde{\mathcal{O}}(1/\epsilon^2)$ sample complexity for on

Alexei Sytov, Laura Bandiera, Kihyeon Cho, Soonwook Hwang

Electromagnetic processes of charged particles interaction with oriented crystals provide a wide variety of innovative applications such as beam steering, crystal-based extraction/collimation of leptons and hadrons in an accelerator, a fixed-target experiment on magnetic and electric dipole moment measurement, X-ray and gamma radiation source for radiotherap

Zhenrong Zhang, Pengfei Hu, Jiefeng Ma, Jun Du

Table structure recognition is an indispensable element for enabling machines to comprehend tables. Its primary purpose is to identify the internal structure of a table. Nevertheless, due to the complexity and diversity of their structure and style, it is highly challenging to parse the tabular data into a structured format that machines can comprehend. In t

Shinobu Hosono, Atsushi Kanazawa

We introduce the BCOV formula for the lattice polarized K3 surfaces. We find that it yields cusp forms expressed by certain eta products for many families of rank 19 lattice polarized K3 surfaces over $\mathbb{P}^{1}$. Moreover, for Clingher-Doran's family of $U\oplus E_{8}(-1)\oplus E_{7}(-1)$-polarized K3 surfaces, we obtain the Igusa cusp forms $\chi_{10}

Yukie Kitaoka, Hiroshi Imamura

Perpendicular magnetic anisotropy (PMA) is a key property of magnetoresistive random access memory (MRAM). To increase areal density of MRAM it is important to find a way to enhance the PMA. Recently a strong enhancement of the PMA by inserting an ultrathin LiF layer at an Fe/MgO interface was reported [T. Nozaki et al., NPG Asia Materials (2022) 14: 5]. To

Erik Jones, Anca Dragan, Aditi Raghunathan, Jacob Steinhardt

Auditing large language models for unexpected behaviors is critical to preempt catastrophic deployments, yet remains challenging. In this work, we cast auditing as an optimization problem, where we automatically search for input-output pairs that match a desired target behavior. For example, we might aim to find a non-toxic input that starts with "Barack Oba

Craig D. Hodgson, Andrew J. Kricker, Rafał M. Siejakowski

We study spaces of circle-valued angle structures, introduced by Feng Luo, on ideal triangulations of 3-manifolds. We prove that the connected components of these spaces are enumerated by certain cohomology groups of the 3-manifold with $\mathbb{Z}_2$-coefficients. Our main theorem shows that this establishes a geometrically natural bijection between the con

Jiaming Wang, Zhihao Du, Shiliang Zhang

Recently, end-to-end neural diarization (EEND) is introduced and achieves promising results in speaker-overlapped scenarios. In EEND, speaker diarization is formulated as a multi-label prediction problem, where speaker activities are estimated independently and their dependency are not well considered. To overcome these disadvantages, we employ the power set

Zhun Deng, Cynthia Dwork, Linjun Zhang

Multi-calibration is a powerful and evolving concept originating in the field of algorithmic fairness. For a predictor $f$ that estimates the outcome $y$ given covariates $x$, and for a function class $\mathcal{C}$, multi-calibration requires that the predictor $f(x)$ and outcome $y$ are indistinguishable under the class of auditors in $\mathcal{C}$. Fairnes

Liangliang Yao, Changhong Fu, Sihang Li, Guangze Zheng

Vision-based object tracking has boosted extensive autonomous applications for unmanned aerial vehicles (UAVs). However, the dynamic changes in flight maneuver and viewpoint encountered in UAV tracking pose significant difficulties, e.g. , aspect ratio change, and scale variation. The conventional cross-correlation operation, while commonly used, has limitat

Gargi Shaw, Gary Ferland, M. Chatzikos

Here we present our current update of CLOUDY on gas-phase chemical reactions for the formation and destruction of the SiS molecule, its energy levels, and collisional rate coefficients with H$_2$, H, and He over a wide range of temperatures. As a result, henceforth the spectral synthesis code CLOUDY predicts SiS line intensities and column densities for vari

Seunghoon Lee, Suhwan Cho, Dogyoon Lee, Minhyeok Lee

Unsupervised Video Object Segmentation (UVOS) refers to the challenging task of segmenting the prominent object in videos without manual guidance. In recent works, two approaches for UVOS have been discussed that can be divided into: appearance and appearance-motion-based methods, which have limitations respectively. Appearance-based methods do not consider

Hector D. Perez, Ignacio E. Grossmann

Optimization problems with discrete-continuous decisions are traditionally modeled in algebraic form via (non)linear mixed-integer programming. A more systematic approach to modeling such systems is to use Generalized Disjunctive Programming (GDP), which extends the Disjunctive Programming paradigm proposed by Egon Balas to allow modeling systems from a logi

Silin Gao, Zhe Zhang, Muhan Wang, Yan Zhang

This paper focuses on the gridless direction-of-arrival (DoA) estimation for data acquired by non-uniform linear arrays (NLAs) in automotive applications. Atomic norm minimization (ANM) is a promising gridless sparse recovery algorithm under the Toeplitz model and solved by convex relaxation, thus it is only applicable to uniform linear arrays (ULAs) with ar

Francesc Castella, Giada Grossi, Christopher Skinner

Let $E/\mathbb{Q}$ be an elliptic curve, let $p>2$ be a prime of good reduction for $E$, and assume that $E$ admits a rational $p$-isogeny with kernel $\mathbb{F}_p(\phi)$. In this paper we prove the cyclotomic Iwasawa main conjecture for $E$, as formulated by Mazur in 1972, when $\phi\vert_{G_p}\neq 1,\omega$, where $G_p$ is a decomposition group at $p$ and

Praveen Manju, Rajendra Kumar Sharma

Leo Creedon and Kieran Hughes in [18] studied derivations of a group ring $RG$ (of a group $G$ over a commutative unital ring $R$) in terms of generators and relators of group $G$. In this article, we do that for $(\sigma, \tau)$-derivations. We develop a necessary and sufficient condition such that a map $f:X \rightarrow RG$ can be extended uniquely to a $(

Oscar Casas-Barrera, Shirley Gómez Páez, William J. Herrera

We analyze the transport properties of a Cooper pair splitter device composed of two-point electrodes in contact with a ferromagnetic/superconductor (F/S) junction constructed on the surface of a topological insulator (TI). For the pair potential in the S region, we consider s- and d-wave symmetries, while for the F region, we focus on a magnetization vector

Kento Katagiri, Tatiana Pikuz, Lichao Fang, Bruno Albertazzi

The motion of line defects (dislocations) has been studied for over 60 years but the maximum speed at which they can move is unresolved. Recent models and atomistic simulations predict the existence of a limiting velocity of dislocation motions between the transonic and subsonic ranges at which the self-energy of dislocation diverges, though they do not deny

Xing Huang

The couplings by change of measure are applied to establish log-Harnack inequality(equivalently the entropy-cost estimate) for conditional McKean-Vlasov SDEs and derive the quantitative conditional propagation of chaos in relative entropy for mean field interacting particle system with common noise. For the log-Harnack inequality, two different types of coup

Yuri V. Gusev

The kernel of the evolution equation is used to build a mathematical theory of thermal phenomena of gaseous and condensed matter. The group velocity of sound and the molar density are proposed to be its two thermal variables that replace the over-complete set of temperature, pressure and volume. The defining constants of the New SI (2019) of physical units a

Akio Kawauchi

Whitehead aspherical conjecture says that every connected subcomplex of every aspherical 2-complex is aspherical. By an argument on ribbon sphere-links, it is confirmed that the conjecture is true for every contractible finite 2-complex. In this paper, by generalizing this argument, this conjecture is confirmed to be true for every aspherical 2-complex.

Danijela Damjanovic, Bassam Fayad, Maria Saprykina

We show the following dichotomy for a linear parabolic $\mathbb Z^2$-action $\rho_L$ on the torus with at least one step-2 generator: (i) Any affine $\mathbb Z^2$-action with linear part $\rho_L$ has a $\mathbb Z$-factor that is either identity or genuinely parabolic, and is thus not KAM-rigid, or (ii) Almost every affine $\mathbb Z^2$-action with linear par

Yiyang Zhou, Qinghai Zheng, Shunshun Bai, Jihua Zhu

In this work, we devote ourselves to the challenging task of Unsupervised Multi-view Representation Learning (UMRL), which requires learning a unified feature representation from multiple views in an unsupervised manner. Existing UMRL methods mainly concentrate on the learning process in the feature space while ignoring the valuable semantic information hidd

Jun Shi, Bingcai Wei, Gang Zhou, Liye Zhang

Although Convolutional Neural Networks (CNN) have made good progress in image restoration, the intrinsic equivalence and locality of convolutions still constrain further improvements in image quality. Recent vision transformer and self-attention have achieved promising results on various computer vision tasks. However, directly utilizing Transformer for imag

Xing Gao, Xiaogang Jia, Yikang Li, Hongkai Xiong

Due to the complex and changing interactions in dynamic scenarios, motion forecasting is a challenging problem in autonomous driving. Most existing works exploit static road graphs to characterize scenarios and are limited in modeling evolving spatio-temporal dependencies in dynamic scenarios. In this paper, we resort to dynamic heterogeneous graphs to model

Ning Jiang, Yi-Long Luo, Di Ma

In this work, we study the so-called Allen-Cahn-Navier-Stokes equations, a diffuse-interface model for two-phase incompressible flows with different densities. We first prove the local-in-time existence and uniqueness of classical solutions with finite initial energy over the smooth bounded domain $\Omega$. The key point is to transform the boundary values o

N. Salikhov, A. Shepetov, G. Pak, V. Saveliev

After an explosive eruption of the Hunga Tonga volcano on January 15, 2022, disturbances were observed at a distance of about 12000km in Northern Tien Shan among the variations of the atmosphere pressure, of telluric current, and of the Doppler frequency shift of ionospheric signal. At 16:00:55UTC a pulse of atmospheric pressure was detected there with a pea

Sumanta Bhattacharyya, Ramesh Manuvinakurike, Sahisnu Mazumder, Saurav Sahay

In this work, we develop a prompting approach for incremental summarization of task videos. We develop a sample-efficient few-shot approach for extracting semantic concepts as an intermediate step. We leverage an existing model for extracting the concepts from the images and extend it to videos and introduce a clustering and querying approach for sample effi

Ruixiang Tang, Xiaotian Han, Xiaoqian Jiang, Xia Hu

Recent advancements in large language models (LLMs) have led to the development of highly potent models like OpenAI's ChatGPT. These models have exhibited exceptional performance in a variety of tasks, such as question answering, essay composition, and code generation. However, their effectiveness in the healthcare sector remains uncertain. In this study, we

Ryan Hynd

We revisit a classic proof of the Blaschke-Lebesgue theorem. It is based on the support function of a convex curve and the approximation of constant width curves by Reuleaux polygons.

Mun Kim, Armin Tabesh, Tyler Zegray, Shabir Barzanjeh

Incorporating cavity magnonics has opened up a new avenue in controlling non-reciprocity. This work examines a yttrium iron garnet sphere coupled to a planar microwave cavity at milli-Kelvin temperature. Non-reciprocal device behavior results from the cooperation of coherent and dissipative coupling between the Kittel mode and a microwave cavity mode. The de

Minghao Yue, Xiaohui Fan, Jinyi Yang, Feige Wang

We present the first results from a new survey for high-redshift $(z\gtrsim5)$ gravitationally lensed quasars and close quasar pairs. We carry out candidate selection based on the colors and shapes of objects in public imaging surveys, then conduct follow-up observations to confirm the nature of high-priority candidates. In this paper, we report the discover

Taisuke Kobayashi

Soft actor-critic (SAC) in reinforcement learning is expected to be one of the next-generation robot control schemes. Its ability to maximize policy entropy would make a robotic controller robust to noise and perturbation, which is useful for real-world robot applications. However, the priority of maximizing the policy entropy is automatically tuned in the c

D. John Hillier

Photoionization and its inverse, electron-ion recombination, are key processes that influence many astrophysical plasmas (and gasses), and the diagnostics that we use to analyse the plasmas. In this review we provide a brief overview of the importance of photoionization and recombination in astrophysics. We highlight how the data needed for spectral analyses

Siqi Liu, Qianqian Yu, Hao Zhou, Dong Sheng

This paper presents a compact low-temperature atomic vector magnetometer for weak field measurements, using an atomic cell containing two orthogonal multipass cavities. At the working temperature of 75 $^\circ$C, the magnetic field sensitivities at all three axes are better than 45 fT/Hz$^{1/2}$ at 10~Hz limited by photon noise, and 85 fT/Hz$^{1/2}$ at 0.1~H

Devangi N. Parikh, Robert A. van de Geijn, Greg M. Henry

This paper lays out insights and opportunities for implementing higher-precision matrix-matrix multiplication (GEMM) from (in terms of) lower-precision high-performance GEMM. The driving case study approximates double-double precision (FP64x2) GEMM in terms of double precision (FP64) GEMM, leveraging how the BLAS-like Library Instantiation Software (BLIS) fr

Robert E. Wray, Steven J. Jones, John E. Laird

Human behavior is conditioned by codes and norms that constrain action. Rules, ``manners,'' laws, and moral imperatives are examples of classes of constraints that govern human behavior. These systems of constraints are "messy:" individual constraints are often poorly defined, what constraints are relevant in a particular situation may be unknown or ambiguou

Wenbang Deng, Kaihong Huang, Qinghua Yu, Huimin Lu

Open-world Instance Segmentation (OIS) is a challenging task that aims to accurately segment every object instance appearing in the current observation, regardless of whether these instances have been labeled in the training set. This is important for safety-critical applications such as robust autonomous navigation. In this paper, we present a flexible and

Ahmad Biniaz

A covering path for a planar point set is a path drawn in the plane with straight-line edges such that every point lies at a vertex or on an edge of the path. A covering tree is defined analogously. Let $\pi(n)$ be the minimum number such that every set of $n$ points in the plane can be covered by a noncrossing path with at most $\pi(n)$ edges. Let $\tau(n)$

Wenhan Yu, Terence Jie Chua, Jun Zhao

The Metaverse and its promises are fast becoming reality as maturing technologies are empowering the different facets. One of the highlights of the Metaverse is that it offers the possibility for highly immersive and interactive socialization. Virtual reality (VR) technologies are the backbone for the virtual universe within the Metaverse as they enable a hy

Karim Khanaki

This is an expository paper in Persian on Grothendieck's double limit theorem and its connection with the (neo-)stability project. We review recent results/observations and discuss historical and philosophical issues.

Yiming Meng, Jun Liu

The essential step of abstraction-based control synthesis for nonlinear systems to satisfy a given specification is to obtain a finite-state abstraction of the original systems. The complexity of the abstraction is usually the dominating factor that determines the efficiency of the algorithm. For the control synthesis of discrete-time nonlinear stochastic sy

Tong Bu, Wei Fang, Jianhao Ding, PengLin Dai

Spiking Neural Networks (SNNs) have gained great attraction due to their distinctive properties of low power consumption and fast inference on neuromorphic hardware. As the most effective method to get deep SNNs, ANN-SNN conversion has achieved comparable performance as ANNs on large-scale datasets. Despite this, it requires long time-steps to match the firi

Linzhi Huang, Yulong Li, Hongbo Tian, Yue Yang

In this paper, we delve into semi-supervised 2D human pose estimation. The previous method ignored two problems: (i) When conducting interactive training between large model and lightweight model, the pseudo label of lightweight model will be used to guide large models. (ii) The negative impact of noise pseudo labels on training. Moreover, the labels used fo

Mostafa Tanhayi Ahari, Yaroslav Tserkovnyak

We study a hybrid structure of a ferromagnetic-insulator and a superconductor connected by a weak link, which accommodates Andreev bound states whose spin degeneracy is lifted due to the exchange interaction with the ferromagnet. The resultant spin-resolved energy levels realize a two-state quantum system, provided that a single electron is trapped in the bo

Xiulong Yang, Shihao Ji

Energy-based models (EBMs) exhibit a variety of desirable properties in predictive tasks, such as generality, simplicity and compositionality. However, training EBMs on high-dimensional datasets remains unstable and expensive. In this paper, we present a Manifold EBM (M-EBM) to boost the overall performance of unconditional EBM and Joint Energy-based Model (

Luna Lima e Silva, Daniel Jost Brod

Quantum walks have been used to develop quantum algorithms since their inception, and can be seen as an alternative to the usual circuit model; combining single-particle quantum walks on sparse graphs with two-particle scattering on a line lattice is sufficient to perform universal quantum computation. In this work we solve the problem of two-particle scatte

Xianghui Yang, Guosheng Lin, Zhenghao Chen, Luping Zhou

Deep neural networks (DNNs) are widely applied for nowadays 3D surface reconstruction tasks and such methods can be further divided into two categories, which respectively warp templates explicitly by moving vertices or represent 3D surfaces implicitly as signed or unsigned distance functions. Taking advantage of both advanced explicit learning process and p

Muzi Peng, Jiangwei Wang, Dongjin Song, Fei Miao

Deep learning is the method of choice for trajectory prediction for autonomous vehicles. Unfortunately, its data-hungry nature implicitly requires the availability of sufficiently rich and high-quality centralized datasets, which easily leads to privacy leakage. Besides, uncertainty-awareness becomes increasingly important for safety-crucial cyber physical s

Chase Yakaboski, Eugene Santos

Successful machine learning methods require a trade-off between memorization and generalization. Too much memorization and the model cannot generalize to unobserved examples. Too much over-generalization and we risk under-fitting the data. While we commonly measure their performance through cross validation and accuracy metrics, how should these algorithms c

Yingcong Li, Samet Oymak

Constructing useful representations across a large number of tasks is a key requirement for sample-efficient intelligent systems. A traditional idea in multitask learning (MTL) is building a shared representation across tasks which can then be adapted to new tasks by tuning last layers. A desirable refinement of using a shared one-fits-all representation is

Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng

In large-scale multi-agent systems like taxi fleets, individual agents (taxi drivers) are self-interested (maximizing their own profits) and this can introduce inefficiencies in the system. One such inefficiency is with regard to the "required" availability of taxis at different time periods during the day. Since a taxi driver can work for a limited number o

Guillaume Berger, Manik Dhingra, Antoine Mercier, Yashesh Savani

In this work, we present QuickSRNet, an efficient super-resolution architecture for real-time applications on mobile platforms. Super-resolution clarifies, sharpens, and upscales an image to higher resolution. Applications such as gaming and video playback along with the ever-improving display capabilities of TVs, smartphones, and VR headsets are driving the

Xize Wang, John L. Renne

Using the 2017 National Household Travel Survey (NHTS), this study analyzes America's urban travel trends compared with earlier nationwide travel surveys, and examines the variations in travel behaviors among a range of socioeconomic groups. The most noticeable trend for the 2017 NHTS is that although private automobiles continue to be the dominant travel mo