March 2023 arXiv papers — page 46

Kamil Mikolaj, Manxi Lin, Zahra Bashir, Morten Bo Søndergaard Svendsen

Confounding information in the form of text or markings embedded in medical images can severely affect the training of diagnostic deep learning algorithms. However, data collected for clinical purposes often have such markings embedded in them. In dermatology, known examples include drawings or rulers that are overrepresented in images of malignant lesions.

Tiago S. Fernandes, Samuel J. Vieira, Antonio Onofre, Juan Calderón Bustillo

We investigate the use of Convolutional Neural Networks (including the modern ConvNeXt network family) to classify transient noise signals (i.e.~glitches) and gravitational waves in data from the Advanced LIGO detectors. First, we use models with a supervised learning approach, both trained from scratch using the Gravity Spy dataset and employing transfer le

Junji Otsuka, Masakazu Yoshimura, Takeshi Ohashi

Unprocessed sensor outputs (RAW images) potentially improve both low-level and high-level computer vision algorithms, but the lack of large-scale RAW image datasets is a barrier to research. Thus, reversed Image Signal Processing (ISP) which converts existing RGB images into RAW images has been studied. However, most existing methods require camera-specific

Theresa Bender, Philip Gemke, Ennio Idrobo-Avila, Henning Dathe

Electrocardiography analysis is widely used in various clinical applications and Deep Learning models for classification tasks are currently in the focus of research. Due to their data-driven character, they bear the potential to handle signal noise efficiently, but its influence on the accuracy of these methods is still unclear. Therefore, we benchmark the

Alberto Zingaro, Christian Vergara, Luca Dede', Francesco Regazzoni

We present a novel mathematical model that simulates myocardial blood perfusion by embedding multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, reduced valve modeling, and a multicompartment Darcy model of perfusion. We consider a fully coupled electromechanical model of the lef

Han Xue, Wenqiang Xu, Jieyi Zhang, Tutian Tang

Garments are important to humans. A visual system that can estimate and track the complete garment pose can be useful for many downstream tasks and real-world applications. In this work, we present a complete package to address the category-level garment pose tracking task: (1) A recording system VR-Garment, with which users can manipulate virtual garment mo

Zhong Zhang, Jian-liang Wu, Cun-quan Qu, Fei Jing

The dissemination of information and the development of public opinion are essential elements of most social media platforms and are often described as distinct, man-made occurrences. However, what is often disregarded is the interdependence between these two phenomena. Information dissemination serves as the foundation for the formation of public opinion, w

Congcong Zheng, Xutao Yu, Kun Wang

In this work, we present a protocol for comparing the performance of arbitrary quantum processes executed on spatially or temporally disparate quantum platforms using Local Operations and Classical Communication (LOCC). The protocol involves sampling local unitary operators, which are then communicated to each platform via classical communication to construc

Chang-Youn Moon

We investigate the connection between the local electron correlation and the momentum dependence of the spin susceptibility and the superconducting gap functions in Sr$_2$RuO$_4$, using density-functional theory combined with dynamical mean-field theory. Adopting frequency-dependent twoparticle vertex moves the zero energy spin susceptibility peaks towards t

Takuhiro Kaneko, Hirokazu Kameoka, Kou Tanaka, Shogo Seki

In speech synthesis, a generative adversarial network (GAN), training a generator (speech synthesizer) and a discriminator in a min-max game, is widely used to improve speech quality. An ensemble of discriminators is commonly used in recent neural vocoders (e.g., HiFi-GAN) and end-to-end text-to-speech (TTS) systems (e.g., VITS) to scrutinize waveforms from

Joost de Graaf, Kim William Torre, Wilson C. K. Poon, Michiel Hermes

Attractive colloids diffuse and aggregate to form gels, solid-like particle networks suspended in a fluid. Gravity is known to strongly impact the stability of gels once they are formed. However, its effect on the process of gel formation has seldom been studied. Here, we simulate the effect of gravity on gelation using both Brownian dynamics and a lattice-B

Zhong Wang

"Q Zhang's Problem" is a teaching problem proposed by Qian Zhang, a science teacher at Dongjiao Minxiang Primary School in Dongcheng District, Beijing. In 2022, she proposed that: (1) when explaining the knowledge points of frequency in the "Sound" unit, experiments on the vibration of objects such as rubber bands and steel rulers were used to assist student

T Kathiravan, K Srinivas, Usha K Sangale

Let $b_{\ell, k}(n), b_{\ell, k, r}(n)$ count the number of $(\ell, k)$, $(\ell, k, r)$-regular partitions respectively. In this paper we shall derive infinite families of congruences for $b_{\ell, k}(n)$ modulo $2$ when $ (\ell, k) = (3,8), (4, 7)$, for $b_{\ell, k}(n)$ modulo $8$, modulo $9$ and modulo $12$ when $(\ell, k) = (4, 9)$ and $b_{\ell, k, r}(n)$

Sébastien Ott

Two proofs of the Central Limit Theorem using a renormalization group approach are presented. The first proof is conducted under a third moment assumption and shows that a suitable renormalization group map is a contraction over the space of probability measures with a third moment. The second proof uses Lyapunov stability and works under a second moment con

Wiebke Bennecke, Andreas Windischbacher, David Schmitt, Jan Philipp Bange

Harnessing the optoelectronic response of organic semiconductors requires a thorough understanding of the fundamental light-matter interaction that is dominated by the excitation of correlated electron-hole pairs, i.e. excitons. The nature of these excitons would be fully captured by knowing the quantum-mechanical wavefunction, which, however, is difficult t

Timo Häckel, Philipp Meyer, Mehmet Mueller, Jan Schmitt-Solbrig

Modern In-Vehicle Networks (IVNs) are composed of a large number of devices and services linked via an Ethernet-based time-sensitive network. Communication in future IVNs will become more dynamic as services can be updated, added, or removed during runtime. This requires a flexible and adaptable IVN, for which Software-Defined Networking (SDN) is a promising

Santu Prasad Jana, Suraina Gupta, Anjan K. Gupta

Electrical conductivity with gate-sweep in a few layer MoS$_2$-on-SiO$_2$ field-effect-transistor shows an abrupt reduction in hysteresis when cooled. The hysteresis and time dependent conductivity of the MoS$_2$ channel are modeled using the dynamics of interface traps' occupancy. The reduction in hysteresis is found to be steepest at a blocking temperature

Clément Sarrazin, Bernhard Schmitzer

Optimal transport is a geometrically intuitive, robust and flexible metric for sample comparison in data analysis and machine learning. Its formal Riemannian structure allows for a local linearization via a tangent space approximation. This in turn leads to a reduction of computational complexity and simplifies combination with other methods that require a l

Juan L. González-Santander, Fernando Sánchez Lasheras

We calculate some infinite sums containing the digamma function in closed-form. These sums are related either to the incomplete beta function or to the Bessel functions. The calculations yield interesting new results as by-products, such as parameter differentiation formulas for the beta incomplete function, reduction formulas of $_{3}F_{2}$ hypergeometric f

Nicolas Lazzari, Andrea Poltronieri, Valentina Presutti

Structure perception is a fundamental aspect of music cognition in humans. Historically, the hierarchical organization of music into structures served as a narrative device for conveying meaning, creating expectancy, and evoking emotions in the listener. Thereby, musical structures play an essential role in music composition, as they shape the musical discou

Qi Wang, Lucas Mahler, Julius Steiglechner, Florian Birk

Learning based single image super resolution (SISR) task is well investigated in 2D images. However, SISR for 3D Magnetics Resonance Images (MRI) is more challenging compared to 2D, mainly due to the increased number of neural network parameters, the larger memory requirement and the limited amount of available training data. Current SISR methods for 3D volu

Longhui Yuan, Binhui Xie, Shuang Li

Test-time adaptation (TTA) intends to adapt the pretrained model to test distributions with only unlabeled test data streams. Most of the previous TTA methods have achieved great success on simple test data streams such as independently sampled data from single or multiple distributions. However, these attempts may fail in dynamic scenarios of real-world app

Zhiheng Ma, Xiaopeng Hong, Beinan Liu, Yabin Wang

Although data-free incremental learning methods are memory-friendly, accurately estimating and counteracting representation shifts is challenging in the absence of historical data. This paper addresses this thorny problem by proposing a novel incremental learning method inspired by human analogy capabilities. Specifically, we design an analogy-making mechani

L. Gil

We show that a network of non-identical nodes, with excitable dynamics, pulse-coupled, with coupling delays depending on the Euclidean distance between nodes, is able to adapt the topology of its connections to obtain spike frequency synchronization. The adapted network exhibits remarkable properties: sparse, anti-cluster, necessary presence of a minimum of

Grigorios G Chrysos, Bohan Wang, Jiankang Deng, Volkan Cevher

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising performance and improved interpretability but have yet to reach the performance of the powerful DNN bas

Zheng Zhao, Juha Sarmavuori

Stochastic filtering refers to estimating the probability distribution of the latent stochastic process conditioned on the observed measurements in time. In this paper, we introduce a new class of convergent filters that represent the filtering distributions by their moments. The key enablement is a quadrature method that uses orthonormal polynomials spanned

Shrihari Sridharan, Subith G., Atma Ram Tiwari

In this paper, we consider polynomial correspondences $f (x, y)$ in $\mathbb{C}[x, y]$ of degree $d \ge 2$ in both the variables and obtain necessary and sufficient conditions in order that the equation $f (x, y) = 0$ can be expressed as $\phi (x) = \psi (y)$, where $\phi$ and $\psi$ are fractional degree $d$ rational maps in the Riemann sphere. In the absen

Peter Giblin, Graham Reeve

The classical van der Waals equation, applied to one or two mixing fluids, and the Helmholtz (free) energy function $A$ yield, for fixed temperature $T$, a curve in the plane $\mathbb{R}^2$ (one fluid) or a surface in 3-space $\mathbb{R}^3$ (binary fluid). A line tangent to this curve in two places (bitangent line), or a set of planes tangent to this surface

B. P. Kondratyev, V. S. Kornoukhov, E. N. Kireeva

The problem of mutual gravitational energy $W_{mut}$ for a system of two homogeneous prolate spheroids, whose symmetry axes are on the same line, is set and solved. The method of equigravitating elements is applied, where the external potentials of three-dimensional spheroids are represented by the potentials of one-dimensional inhomogeneous focal rods. The

Noam Berger, Diana Conache, Anders Johannson, Anders Öberg

In this paper we solve two open problems in ergodic theory. We prove first that if a Doeblin function $g$ (a $g$-function) satisfies \[\limsup_{n\to\infty}\frac{\mbox{var}_n \log g}{n^{-1/2}} < 2,\] then we have a unique Doeblin measure ($g$-measure). This result indicates a possible phase transition in analogy with the long-range Ising model. Secondly, we p

Giacomo Ascione, Mladen Savov, Bruno Toaldo

In this article densities (and their derivatives) of subordinators and inverse subordinators are considered. Under minor restrictions, generally milder than the existing in the literature, using a useful modification of the saddle point method, we obtain the large asymptotic behaviour of these densities (and their derivatives) for a specific region of space

Long-Gang Huang, Xuanchen Zhang, Yanzhen Wang, Zhenxing Hua

Spin squeezing plays a crucial role in quantum metrology and quantum information science. Its generation is the prerequisite for further applications but still faces an enormous challenge since the existing physical systems rarely contain the required squeezing interactions. Here we propose a universal scheme to generate spin squeezing in coupled spin models

J. Miquel Martínez

We describe finite groups whose principal block contains only characters of prime power degree.

Jiaqi Qu, Lu Wei, Qiang Sun, Hamidreza Zareipour

Various faults can occur during the operation of PV arrays, and both the dust-affected operating conditions and various diode configurations make the faults more complicated. However, current methods for fault diagnosis based on I-V characteristic curves only utilize partial feature information and often rely on calibrating the field characteristic curves to

Petr Dvořáček, Petr Hurtik, Petra Števuliáková

We propose a new, simple framework for crafting adversarial examples for black box attacks. The idea is to simulate the substitution model with a non-trainable model compounded of just one layer of handcrafted convolutional kernels and then train the generator neural network to maximize the distance of the outputs for the original and generated adversarial i

N. O. Agasian, Z. V. Khaidukov, Yu. A. Simonov

The phenomenon of the almost linear growth of the square root of spatial string tension $\sqrt{\sigma_s(T)}= c_{\sigma} g^2 T$ was found both in lattice and in theory, based on the Field Correlator Method (FCM). In the latter the string tension (both spatial and colorelectric) is expressed as an integral of the two gluon Green's function calculated with the

Haojie Zhao, Junsong Chen, Lijun Wang, Huchuan Lu

Compared with traditional RGB-only visual tracking, few datasets have been constructed for RGB-D tracking. In this paper, we propose ARKitTrack, a new RGB-D tracking dataset for both static and dynamic scenes captured by consumer-grade LiDAR scanners equipped on Apple's iPhone and iPad. ARKitTrack contains 300 RGB-D sequences, 455 targets, and 229.7K video f

Nadia Flodgren, Bo Sundborg

We study the one loop renormalisation of 4d $SU(N)$ Yang-Mills theory with $M$ adjoint representation scalar multiplets related by $O(M)$ symmetry. General $M$ are of field theoretic interest, and the 4d one loop beta function of the gauge coupling $g^2$ vanishes for the case $M=22$, which is intriguing for string theory. This case is related to D3 branes of

S. Prokhorenko, Y. Nahas, Q. Zhang, V. Govinden

Polar bubble domains are complex topological defects akin to magnetic skyrmions that can spontaneously form in ferroelectric thin films and superlattices. They can be deterministically written and deleted and exhibit a set of properties, such as sub-10 nm radius and room-temperature stability, that are highly attractive for dense data storage and reconfigura

Simon Jantač, Holger Grosshans

Current models predict particles of the same material but different sizes to charge bipolar upon contacts; the resulting charge peaks endanger process safety. However, we found wall-bounded turbulence to suppress the powder's electrostatic charging. Aerodynamic forces skew the collision frequency and narrow the charge distribution's bandwidth. Bipolar chargi

Carlos Hernandez-Olivan, Sonia Rubio Llamas, Jose R. Beltran

Music Structure Analysis is an open research task in Music Information Retrieval (MIR). In the past, there have been several works that attempt to segment music into the audio and symbolic domains, however, the identification and segmentation of the music structure at different levels is still an open research problem in this area. In this work we propose th

Angel Sherletov, David Schaich

We present ongoing investigations of maximally supersymmetric Yang--Mills ($Q = 16$ SYM) theory in three space-time dimensions. At low temperatures and large $N$ this theory is related to black branes in higher-dimensional quantum gravity. Building on previous work that focused on the homogeneous `D2' phase of the theory, we are now exploring phase transitio

Y. Boujakhrout, E. H Saidi, R. Ahl Laamara, L. B Drissi

We investigate 4D Chern-Simons theory with ADE gauge symmetries in the presence of interacting Wilson and 't Hooft line defects. We analyse the intrinsic properties of these lines' coupling and explicate the building of oscillator-type Lax matrices verifying the RLL integrability equation. We propose gauge quiver diagrams Q$_{G}^{\mu }$ encoding the topologi

Margarethe Hauck, Lena M. Saure, Berit Zeller-Plumhoff, Sören Kaps

Hydrogel-based soft actuators can operate in sensitive environments, bridging the gap of rigid machines interacting with soft matter. However, while stimuli-responsive hydrogels can undergo extreme reversible volume changes of up to ~90%, water transport in hydrogel actuators is in general limited by their poroelastic behavior. For poly(N-isopropylacrylamide

Yuji Ohta, Tadayuki Watanabe

In our previous works, we constructed diffeomorphisms of compact 4-manifolds $X$ by surgeries on theta-graphs embedded in $X$. In this paper, we consider the case $X=M\times I$, where $M$ is a spherical 3-manifold. For some of such $X$, we compute lower bounds of the ranks of the abelian groups $\pi_0\mathrm{Diff}(X,\partial)$. We study the behavior of the e

BOREXINO Collaboration, D. Basilico, G. Bellini, J. Benziger

The search for neutrino events in correlation with gravitational wave (GW) events for three observing runs (O1, O2 and O3) from 09/2015 to 03/2020 has been performed using the Borexino data-set of the same period. We have searched for signals of neutrino-electron scattering with visible energies above 250 keV within a time window of 1000 s centered at the de

C. J. Díaz Baso, L. Rouppe van der Voort, J. de la Cruz Rodríguez, J. Leenaarts

Fabry-P\'erot interferometers (FPIs) have become very popular in solar observations because they offer a balance between cadence, spatial resolution, and spectral resolution through a careful design of the spectral sampling scheme according to the observational requirements of a given target. However, an efficient balance requires knowledge of the expected t

WonJun Moon, Sangeek Hyun, SangUk Park, Dongchan Park

Recently, video moment retrieval and highlight detection (MR/HD) are being spotlighted as the demand for video understanding is drastically increased. The key objective of MR/HD is to localize the moment and estimate clip-wise accordance level, i.e., saliency score, to the given text query. Although the recent transformer-based models brought some advances,

Rui Chen, Yongwei Chen, Ningxin Jiao, Kui Jia

Automatic 3D content creation has achieved rapid progress recently due to the availability of pre-trained, large language models and image diffusion models, forming the emerging topic of text-to-3D content creation. Existing text-to-3D methods commonly use implicit scene representations, which couple the geometry and appearance via volume rendering and are s

Ryo Ishizuka, Kazuma Shimomoto

Over a complete Noetherian local domain of mixed characteristic with perfect residue field, we construct a perfectoid ring which is similar to an explicit representation of a perfect closure in positive characteristic. Then we demonstrate that this perfectoid ring is almost Cohen-Macaulay in the sense of almost ring theory. The proof of this result uses Andr

David Bauch, Dustin Siebert, Klaus D. Jöns, Jens Förstner

The biexciton-exciton emission cascade commonly used in quantum-dot systems to generate polarization entanglement yields photons with intrinsically limited indistinguishability. In the present work we focus on the generation of pairs of photons with high degrees of polarization entanglement and simultaneously high indistinguishability. We achieve this goal b

Matteo Bernabè, David López Pérez, Nicola Piovesan, Giovanni Geraci

In this article, we introduce a new metric for driving the serving cell selection process of a swarm of cellular connected unmanned aerial vehicles (CCUAVs) located on aerial highways when served by a massive multiple input multiple output (mMIMO) terrestrial network. Selecting the optimal serving cell from several suitable candidates is not straightforward.

Yudong Huang, Minrui Xu, Xinyuan Zhang, Dusit Niyato

The future networks pose intense demands for intelligent and customized designs to cope with the surging network scale, dynamically time-varying environments, diverse user requirements, and complicated manual configuration. However, traditional rule-based solutions heavily rely on human efforts and expertise, while data-driven intelligent algorithms still la

Wei Xingxing, Yu Jie, Huang Yao

Owing to the extensive application of infrared object detectors in the safety-critical tasks, it is necessary to evaluate their robustness against adversarial examples in the real world. However, current few physical infrared attacks are complicated to implement in practical application because of their complex transformation from digital world to physical w

Yi Lin, Yufan Chen, Kwang-Ting Cheng, Hao Chen

Medical image segmentation has made significant progress in recent years. Deep learning-based methods are recognized as data-hungry techniques, requiring large amounts of data with manual annotations. However, manual annotation is expensive in the field of medical image analysis, which requires domain-specific expertise. To address this challenge, few-shot l

Si Shen, Chenzhi Yuan, Zichang Zhang, Hao Yu

Quantum teleportation can transfer an unknown quantum state between distant quantum nodes, which holds great promise in enabling large-scale quantum networks. To advance the full potential of quantum teleportation, quantum states must be faithfully transferred at a high rate over long distance. Despite recent impressive advances, a high-rate quantum teleport

Moritz Schauer, Frank van der Meulen, Andi Q. Wang

Backward Filtering Forward Guiding (BFFG) is a bidirectional algorithm proposed in Mider et al. [2021] and studied more in depth in a general setting in Van der Meulen and Schauer [2022]. In category theory, optics have been proposed for modelling systems with bidirectional data flow. We connect BFFG with optics by demonstrating that the forward and backward

Leyou Xu, Bo Zhou

For $S\subseteq V(G)$ with $|S|\ge 2$, let $\kappa_G (S)$ denote the maximum number of internally disjoint trees connecting $S$ in $G$. For $2\le k\le n$, the generalized $k$-connectivity $\kappa_k(G)$ of an $n$-vertex connected graph $G$ is defined to be $\kappa_k(G)=\min \{\kappa_G(S): S\in V(G) \mbox{ and } |S|=k\}$. The generalized $k$-connectivity can s

Sibi C. Sethuraman, Gaurav R. Tadkapally, Saraju P. Mohanty, Gautam Galada

Individuals with visual impairments often face a multitude of challenging obstacles in their daily lives. Vision impairment can severely impair a person's ability to work, navigate, and retain independence. This can result in educational limits, a higher risk of accidents, and a plethora of other issues. To address these challenges, we present MagicEye, a st

Hao Chen, Linyan Li, Fan Lyu, Fuyuan Hu

Few-shot class-incremental learning (FSCIL) aims to design machine learning algorithms that can continually learn new concepts from a few data points, without forgetting knowledge of old classes. The difficulty lies in that limited data from new classes not only lead to significant overfitting issues but also exacerbates the notorious catastrophic forgetting

Thiem Hoang, Abraham Loeb

The first interstellar object observed in our solar system, 1I/`Oumuamua, exhibited several peculiar properties, including extreme elongation and non-gravitational acceleration. Bergner and Seligman (hereafter BS23) proposed that evaporation of trapped H$_2$ created by cosmic rays (CRs) can explain the non-gravitational acceleration. However, their modeling

Stéphane Crépey, Noufel Frikha, Azar Louzi

We propose a multilevel stochastic approximation (MLSA) scheme for the computation of the value-at-risk (VaR) and expected shortfall (ES) of a financial loss, which can only be computed via simulations conditionally on the realisation of future risk factors. Thus the problem of estimating its VaR and ES is nested in nature and can be viewed as an instance of

Madhusudan Kumar Sinha, Arun Pachai Kannu

Sparse regression codes (SPARC) connect the sparse signal recovery framework of compressive sensing with error control coding techniques. SPARC encoding produces codewords which are \emph{sparse} linear combinations of columns of a dictionary matrix. SPARC decoding is accomplished using sparse signal recovery algorithms. We construct dictionary matrices usin

Xinhui Huang, Chunyi Li, Abdelhak Bentaleb, Roger Zimmermann

With the rapid growth of Internet video data amounts and types, a unified Video Quality Assessment (VQA) is needed to inspire video communication with perceptual quality. To meet the real-time and universal requirements in providing such inspiration, this study proposes a VQA model from a classification of User Generated Content (UGC), Professionally Generat

Johannes Puschnig, Matthew Hayes, Oscar Agertz, Eric Emsellem

Using new high-resolution data of CO (2-1), H-alpha and H-beta obtained with the Northern Extended Millimeter Array (NOEMA) and the Multi-Unit Spectroscopic Explorer (MUSE) at the Very Large Telescope, we have performed a Toomre-Q disc stability analysis and studied star formation, gas depletion times and other environmental parameters on sub-kpc scales with

Emmanuel P. Smyrnelis, Panayotis Smyrnelis

Our starting point is the measure $\epsilon_x-\alpha_x\rho_x^{\omega_1}+\beta_x\rho_x^{\omega_2}$, where $\rho_x^{\omega_i}$ is the harmonic measure relative to $x \in \omega_1 \subset \overline{\omega}_1 \subset \omega_2$ and $\omega_i$ are concentric balls of $\R^n$; $\alpha_x$, $\beta_x$ are functions depending on $x$ and on the radii of $\omega_i$, $(i=1

Pengyuan Zhou

Incorporating artificial intelligence (AI) technology, particularly large language models (LLMs), is becoming increasingly vital for developing immersive and interactive metaverse experiences. GPT, a representative LLM developed by OpenAI, is leading LLM development and gaining attention for its potential in building the metaverse. The article delves into th

Baixin Xu, Jiarui Zhang, Kwan-Yee Lin, Chen Qian

Reconstructing 3D human heads in low-view settings presents technical challenges, mainly due to the pronounced risk of overfitting with limited views and high-frequency signals. To address this, we propose geometry decomposition and adopt a two-stage, coarse-to-fine training strategy, allowing for progressively capturing high-frequency geometric details. We

Shyamal Kumar Hui, Abimbola Abolarinwa, Sujit Bhattacharyya

This article is devoted to the study of several estimations for a positive solution to a nonlinear weighted parabolic equation on a weighted Riemannian manifold. We therefore derive new Li-Yau type and Hamilton type gradient estimates yielding several consequences. We also derive Hessian estimate and some corollaries for the same equation. Among the applicat

Mikhail Kennerley, Jian-Gang Wang, Bharadwaj Veeravalli, Robby T. Tan

Object detection at night is a challenging problem due to the absence of night image annotations. Despite several domain adaptation methods, achieving high-precision results remains an issue. False-positive error propagation is still observed in methods using the well-established student-teacher framework, particularly for small-scale and low-light objects.

Renjiao Yi, Chenyang Zhu, Kai Xu

We present a learning-based approach to relight a single image of Lambertian and low-frequency specular objects. Our method enables inserting objects from photographs into new scenes and relighting them under the new environment lighting, which is essential for AR applications. To relight the object, we solve both inverse rendering and re-rendering. To resol

Renxi Liu, Mohan Chen

The hydrogen-bond (H-bond) network of high-pressure water is investigated by neural-network-based molecular dynamics (MD) simulations with the first-principles accuracy. The static structure factors (SSFs) of water at three densities, i.e., 1, 1.115 and 1.24 g/cm3 are directly evaluated from 512-water MD trajectories, which are in quantitative agreement with

Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin L Godfrey

Recently, there has been a growing interest in learning and explaining causal effects within Neural Network (NN) models. By virtue of NN architectures, previous approaches consider only direct and total causal effects assuming independence among input variables. We view an NN as a structural causal model (SCM) and extend our focus to include indirect causal

J. X. Teng, K. Y. Ma

The experimental results of 252 magnetic rotational bands reported in 123 nuclei and 38 antimagnetic rotational bands reported in 27 nuclei are collected and listed in the present work, including energy, spin, parity, magnetic dipole reduced transition probability B(M1), electric quadrupole reduced transition probability B(E2), B(M1)/B(E2) ratio, and the rat

Qiantong Liang, Johnny Yang, Wai-Tong Louis Fan, Wing-Cheong Lo

Defective interfering particles (DIPs) are virus-like particles that occur naturally during virus infections. These particles are defective, lacking essential genetic materials for replication, but they can interact with the wild-type virus and potentially be used as therapeutic agents. However, the effect of DIPs on infection spread is still unclear due to

Victor Volfson

The paper considers estimates for the asymptotics of summation functions of bounded multiplicative arithmetic functions. Several assertions on this subject are proved and examples are considered.

Lei Wang, Xiurui Geng, Lei Zhang

The concept of tensor eigenpairs has received more researches in past decades. Recent works have paid attentions to a special class of symmetric tensors termed regular simplex tensors, which is constructed by equiangular tight frame of n + 1 vectors in n-dimensional space, and the robustness of eigenpairs was investigated. In the end of the literature, a con

Woo Jae Kim, Yoonki Cho, Junsik Jung, Sung-Eui Yoon

Deep neural networks are susceptible to adversarial attacks due to the accumulation of perturbations in the feature level, and numerous works have boosted model robustness by deactivating the non-robust feature activations that cause model mispredictions. However, we claim that these malicious activations still contain discriminative cues and that with recal

Tri Cao, Jiawen Zhu, Guansong Pang

Anomaly detection (AD) is a crucial machine learning task that aims to learn patterns from a set of normal training samples to identify abnormal samples in test data. Most existing AD studies assume that the training and test data are drawn from the same data distribution, but the test data can have large distribution shifts arising in many real-world applic

Lei Zou, Yue Pang, M. Tamer Özsu, Jiaqi Chen

The proliferation of RDF datasets has resulted in studies focusing on optimizing SPARQL query processing. Most existing work focuses on basic graph patterns (BGPs) and ignores other vital operators in SPARQL, such as UNION and OPTIONAL. SPARQL queries with these operators, which we abbreviate as SPARQL-UO, pose serious query plan generation challenges. In th

Haotian Bai, Yuanhuiyi Lyu, Lutao Jiang, Sijia Li

Text-to-3D form plays a crucial role in creating editable 3D scenes for AR/VR. Recent advances have shown promise in merging neural radiance fields (NeRFs) with pre-trained diffusion models for text-to-3D object generation. However, one enduring challenge is their inadequate capability to accurately parse and regenerate consistent multi-object environments.

Hao Shi, Yu Li, Kailun Yang, Jiaming Zhang

This paper raises the new task of Fisheye Semantic Completion (FSC), where dense texture, structure, and semantics of a fisheye image are inferred even beyond the sensor field-of-view (FoV). Fisheye cameras have larger FoV than ordinary pinhole cameras, yet its unique special imaging model naturally leads to a blind area at the edge of the image plane. This

Cong Wang, Po-Nan Li, Jana Thayer, Chun Hong Yoon

Serial crystallography at X-ray free electron laser (XFEL) and synchrotron facilities has experienced tremendous progress in recent times enabling novel scientific investigations into macromolecular structures and molecular processes. However, these experiments generate a significant amount of data posing computational challenges in data reduction and real-t

Sang-In Shim, Kazuki Yoshida, Kazuyuki Ogata

Recent studies on nucleon and alpha knockout reactions have shown that the distorted-wave impulse approximation (DWIA) is a simple and accurate method to describe these reactions. As it has been argued for decades, the nuclear absorption is one of the most important ingredients of the DWIA calculation. In this work, we systematically investigate the absorpti

Rebecca Briffa, Celia Escamilla-Rivera, Jackson Levi Said, Jurgen Mifsud

$f(T)$ cosmology has shown promise in explaining aspects of cosmic evolution. In this work, we analyze constraints on leading models of $f(T)$ gravity in the context of the recently released Pantheon+ data set, together with comparisons with previous releases. We also consider other late-time data sets including cosmic chronometers and baryonic acoustic osci

Jiefeng Ma, Jun Du, Pengfei Hu, Zhenrong Zhang

The problem of document structure reconstruction refers to converting digital or scanned documents into corresponding semantic structures. Most existing works mainly focus on splitting the boundary of each element in a single document page, neglecting the reconstruction of semantic structure in multi-page documents. This paper introduces hierarchical reconst

Niklas Paulig, Ostap Okhrin

This paper develops a Deep Reinforcement Learning (DRL)-agent for navigation and control of autonomous surface vessels (ASV) on inland waterways. Spatial restrictions due to waterway geometry and the resulting challenges, such as high flow velocities or shallow banks, require controlled and precise movement of the ASV. A state-of-the-art bootstrapped Q-learn

H. Nguyen-Xuan, Kim Q. Tran, Chien H. Thai, Jaehong Lee

Functionally graded porous plates have been validated as remarkable lightweight structures with excellent mechanical characteristics and numerous applications. With inspiration from the high strength-to-volume ratio of triply periodic minimal surface (TPMS) structures, a new model of porous plates, which is called a functionally graded TPMS (FG-TPMS) plate,

M. K. Panda

Light gradient can allow many motile photosynthetic microorganisms to bias their motion towards moderate light (positive phototaxis) or away from intense light (negative phototaxis). The proposed work presents the penetrative phototactic bioconvection in a non-scattering algal suspension. The suspension is confined by a stress-free top boundary, and rigid bo

K. P. Skokov, A. Y. Karpenkov, D. Y. Karpenkov, I. A. Radulov

Alloys with a first-order magnetic transition are central to solid-state refrigeration technology, sensors and actuators, or spintronic devices. The discontinuous nature of the transition in these materials is a consequence of the coupling between the magnetic, electronic and structural subsystems, but in a real experiment, it is difficult to observe and ana

Pep Español, Mark Thachuk, J. A. de la Torre

The motion of a rigid body is described in Classical Mechanics with the venerable Euler's equations which are based on the assumption that the relative distances among the constituent particles are fixed in time. Real bodies, however, cannot satisfy this property, as a consequence of thermal fluctuations. We generalize Euler's equations for a free body in or

Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li

Recommendation models that utilize unique identities (IDs) to represent distinct users and items have been state-of-the-art (SOTA) and dominated the recommender systems (RS) literature for over a decade. Meanwhile, the pre-trained modality encoders, such as BERT and ViT, have become increasingly powerful in modeling the raw modality features of an item, such

Ping Chen, Jianliang Zhai

In this paper, we consider a class of reflected stochastic differential equations for which the constraint is not on the paths of the solution but on its law. We establish a small noise large deviation principle, a large deviation for short time and the Malliavin derivative. To prove large deviation principles, a sufficient condition for the weak convergence

Jörg Schürmann, Connor Simpson, Botong Wang

In this paper we prove a new generic vanishing theorem for $X$ a complete homogeneous variety with respect to an action of a connected algebraic group. Let $A, B_0\subset X$ be locally closed affine subvarieties, and assume that $B_0$ is smooth and pure dimensional. Let $\mathcal{P}$ be a perverse sheaf on $A$ and let $B=g B_0$ be a generic translate of $B_0

Valiollah Khalili

In this paper we introduce the class of graded Poisson color algebras as the natural generalization of graded Poisson algebras and graded Poisson superalgebras. For $\Lambda$ an arbitrary abelian group, we show that any of such $\Lambda$-graed Poisson color algebra $\mathcal{P}$, with a symmetric $\Lambda$-support is of the form $\mathcal{P} = \mathcal{U}\op

Giulia Barbareschi, Midori Kawaguchi, Hiroki Kato, Masato Nagahiro

Robotic avatars can help disabled people extend their reach in interacting with the world. Technological advances make it possible for individuals to embody multiple avatars simultaneously. However, existing studies have been limited to laboratory conditions and did not involve disabled participants. In this paper, we present a real-world implementation of a

Wei-Jer Chang, Chen Tang, Chenran Li, Yeping Hu

Traffic simulation plays a crucial role in evaluating and improving autonomous driving planning systems. After being deployed on public roads, autonomous vehicles need to interact with human road participants with different social preferences (e.g., selfish or courteous human drivers). To ensure that autonomous vehicles take safe and efficient maneuvers in d

Benjamin Laplace, Jérémy Vessaire, David Oks, Oliver Tolfts

We present experimental observations of the spatial distribution of large inertial particles suspended in a turbulent swirling flow at high Reynolds number. The plastic particles, which are tracked using several high speed cameras, are heavier than the working fluid so that their dynamics results from a competition between gravitational effects and turbulent

Shujun Wang, Yongqiang Tian, Dengcheng He

Optimizing and maintaining up-to-date API documentation is a challenging problem for evolving OpenAPIs. In this poster, we propose a data-driven continuous optimization solution and multilingual SDK generation scheme to improve the comprehensibility of API documentation. We compute the correlation between API integrity and API trial success rate. Based on th

Nitish Shukla

Manufacturing wafers is an intricate task involving thousands of steps. Defect Pattern Recognition (DPR) of wafer maps is crucial to find the root cause of the issue and further improving the yield in the wafer foundry. Mixed-type DPR is much more complicated compared to single-type DPR due to varied spatial features, the uncertainty of defects, and the numb