April 2023 arXiv papers — page 37

Ruichen Zheng, Peng Li, Haoqian Wang, Tao Yu

Detailed 3D reconstruction and photo-realistic relighting of digital humans are essential for various applications. To this end, we propose a novel sparse-view 3d human reconstruction framework that closely incorporates the occupancy field and albedo field with an additional visibility field--it not only resolves occlusion ambiguity in multiview feature aggr

Anirban Paul, Dipayan Biswas, Dhananjay Nandi

Complete dissociation dynamics of low energy electron attachment to nitrogen dioxide around 8.5 eV resonance has been studied using a velocity map imaging (VMI) spectrometer. Besides the three prominent resonant peaks at around 1.4 eV, 3.1 eV, and 8.5 eV, we have found an additional small resonance at the higher energy tail of the 8.5 eV resonance. We have c

Sarwan Ali, Babatunde Bello, Prakash Chourasia, Ria Thazhe Punathil

Understanding the host-specificity of different families of viruses sheds light on the origin of, e.g., SARS-CoV-2, rabies, and other such zoonotic pathogens in humans. It enables epidemiologists, medical professionals, and policymakers to curb existing epidemics and prevent future ones promptly. In the family Coronaviridae (of which SARS-CoV-2 is a member),

Christina M. Pontin, Adrian J. Barker, Rainer Hollerbach

We study how stably stratified or semi-convective layers alter the tidal dissipation rates associated with the generation of internal waves in planetary interiors. We consider if these layers could contribute to the high rates of tidal dissipation observed for Jupiter and Saturn in our solar system. We use an idealised global spherical Boussinesq model to st

Takumu Ooi, Toshihiro Uemura

We consider Dynkin games for Markov processes associated with semi-Dirichlet forms. Dynkin games are the optimal stopping games introduced as the models of zero-sum games by two players. We prove that the solution to the certain variational inequality with two obstacles is the equilibrium price of the Dynkin game. Moreover, we obtain the saddle point of the

Łucja Kipczak, Zhaolong Chen, Pengru Huang, Kristina Vaklinova

Quantum phenomena at interfaces create functionalities at the level of materials. Ferromagnetism in van der Waals systems with diverse arrangements of spins opened a pathway for utilizing proximity magnetic fields to activate properties of materials which would otherwise require external stimuli. Herewith, we realize this notion via creating heterostructures

Chuan-Peng Zhang, Peng Jiang, Ming Zhu, Jun Pan

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) has been running for several years. A new Ultra-Wide Bandwidth (UWB) receiver, simultaneously covering 500-3300 MHz, has been mounted in the FAST feed cabin and passed a series of observational tests. The whole UWB band is separated into four independent bands. Each band has 1048576 channels in

Mujing Li, Yani Feng, Guanjie Wang

Evaluating failure probability for complex engineering systems is a computationally intensive task. While the Monte Carlo method is easy to implement, it converges slowly and, hence, requires numerous repeated simulations of a complex system to generate sufficient samples. To improve the efficiency, methods based on surrogate models are proposed to approxima

Roberto Reale, Elisabetta Biasin, Alessandro Scardovi, Stefano Toro

The Italian National Health Service is adopting Artificial Intelligence through its technical agencies, with the twofold objective of supporting and facilitating the diagnosis and treatment. Such a vast programme requires special care in formalising the knowledge domain, leveraging domain-specific data spaces and addressing data governance issues from an int

Gilles Dowek, Ying Jiang

We present a calculus, called the scheme-calculus, that permits to express natural deduction proofs in various theories. Unlike $\lambda$-calculus, the syntax of this calculus sticks closely to the syntax of proofs, in particular, no names are introduced for the hypotheses. We show that despite its non-determinism, some typed scheme-calculi have the same exp

Andreas Bally, Yi Chung, Florian Goertz

In this talk, an alternative to top partner solutions and its consequences on phenomenology are discussed. The hierarchy problem from the top loop contribution is solved by mitigating the top Yukawa coupling at high scales. In this scenario, the new degrees of freedom appearing at the cut-off scale of the top loop should then be some new top-philic particles

Hideki Matsuoka, Shun Kajihara, Yue Wang, Yoshihiro Iwasa

Magnetic semimetals form an attractive class of materials because of the non-trivial contributions of itinerant electrons to magnetism. Due to their relatively low-carrier-density nature, a doping level of those materials could be largely tuned by a gating technique. Here we demonstrate gate-tunable ferromagnetism in an emergent van der Waals magnetic semime

Hajrudin Bešić, Alper Demir, Johannes Steurer, Niklas Luhmann

Nanomechanical resonators can serve as high performance detectors and have potential to be widely used in the industry for a variety of applications. Most nanomechanical sensing applications rely on detecting changes of resonance frequency. In commonly used frequency tracking schemes, the resonator is driven at or close to its resonance frequency. Closed-loo

Hannes Wallimann, Silvio Sticher

In railway infrastructure, construction and maintenance is typically procured using competitive procedures such as auctions. However, these procedures only fulfill their purpose - using (taxpayers') money efficiently - if bidders do not collude. Employing a unique dataset of the Swiss Federal Railways, we present two methods in order to detect potential coll

Stathis Filippas, Alkis Tersenov

We obtain estimates of all components of the velocity of a 3D rigid body moving in a viscous incompressible fluid without any symmetry restriction on the shape of the rigid body or the container. The estimates are in terms of suitable norms of the velocity field in a small domain of the fluid only, provided the distance $h$ between the rigid body and the con

Bo Feng, Gang Wu

Quadratic minimization problems with orthogonality constraints (QMPO) play an important role in many applications of science and engineering. However, some existing methods may suffer from low accuracy or heavy workload for large-scale QMPO. Krylov subspace methods are popular for large-scale optimization problems. In this work, we propose a block Lanczos me

Navid Zehtabiyan-Rezaie, Mahdi Abkar

The Reynolds-averaged Navier-Stokes approach coupled with the standard $k-\varepsilon$ model is widely utilized for wind-energy applications. However, it has been shown that the standard $k-\varepsilon$ model overestimates the turbulence intensity in the wake region and, consequently, overpredicts the power output of the waked turbines. This study focuses on

Boyu Teng, Xiaojun Yuan, Rui Wang

Reconfigurable intelligent surface (RIS) has attracted enormous interest for its potential advantages in assisting both wireless communication and environmental sensing. In this paper, we study a challenging multiuser tracking problem in the multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system aided by multiple RISs.

Kyungsub Lee

This study examines the use of a recurrent neural network for estimating the parameters of a Hawkes model based on high-frequency financial data, and subsequently, for computing volatility. Neural networks have shown promising results in various fields, and interest in finance is also growing. Our approach demonstrates significantly faster computational perf

Guillaume Burel, Gilles Dowek

We introduce a method to prove that a proof search method is not an instance of another. As an example of application, we show that Polarized resolution modulo, a method that mixes clause selection restrictions and literal selection restrictions, is not an instance of Ordered resolution with selection.

Clara Stegehuis, Lotte Weedage

With more and more demand from devices to use wireless communication networks, there has been an increased interest in resource sharing among operators, to give a better link quality. However, in the analysis of the benefits of resource sharing among these operators, the important factor of co-location is often overlooked. Indeed, often in wireless communica

Yuyan Li

Transformer fault diagnosis (TFD) is a critical aspect of power system maintenance and management. This review paper provides a comprehensive overview of the current state of the art in TFD using artificial intelligence (AI) and dissolved gas analysis (DGA). The paper presents an analysis of recent advancements in this field, including the use of deep learni

Yingtao Tian

Computational creativity has contributed heavily to abstract art in modern era, allowing artists to create high quality, abstract two dimension (2D) arts with a high level of controllability and expressibility. However, even with computational approaches that have promising result in making concrete 3D art, computationally addressing abstract 3D art with hig

Beom-Seok Han, Jaeyun Yi

We study the existence, uniqueness, and regularity of the solution to the stochastic reaction-diffusion equation (SRDE) with colored noise $\dot{F}$: $$ \partial_t u = a^{ij}u_{x^ix^j} + b^i u_{x^i} + cu - \bar{b} u^{1+\beta} + \xi u^{1+\gamma}\dot F,\quad (t,x)\in \mathbb{R}_+\times\mathbb{R}^d; \quad u(0,\cdot) = u_0, $$ where $a^{ij},b^i,c, \bar{b}$ and $

Stanley Burris

An examination of George Boole's mysterious use of the Algebra of Numbers to create an Algebra of Logic, and subsequent research connected to this.

Deepanway Ghosal, Navonil Majumder, Ambuj Mehrish, Soujanya Poria

The immense scale of the recent large language models (LLM) allows many interesting properties, such as, instruction- and chain-of-thought-based fine-tuning, that has significantly improved zero- and few-shot performance in many natural language processing (NLP) tasks. Inspired by such successes, we adopt such an instruction-tuned LLM Flan-T5 as the text enc

Karin Erdmann

We give a characterisation of representation-finite symmetric algebras of period four, and describe their basic algebras. In particular, if such an algebra is indecomposable, it has at most two simple modules.

Fatemeh Zarrabi, Isabel Wagner, Eerke Boiten

Based on Article 35 of the EU (European Union) General Data Protection Regulation, a Data Protection Impact Assessment (DPIA) is necessary whenever there is a possibility of a high privacy and data protection risk to individuals caused by a new project under development. A similar process to DPIA had been previously known as Privacy Impact Assessment (PIA).

Avi Abu, Roee Diamant

Combining synthetic aperture sonar (SAS) imagery with optical images for underwater object classification has the potential to overcome challenges such as water clarity, the stability of the optical image analysis platform, and strong reflections from the seabed for sonar-based classification. In this work, we propose this type of multi-modal combination to

Julien Toulouse

We develop semiclassical approximations for calculating photoabsorption cross sections beyond the continuum threshold in quantum many-body systems. These approximations use the fully quantum-mechanical Wigner function of the ground state and semiclassical expansions only for the part of the cross section depending on the continuum states, thus avoiding the d

Grégory Faye, Jean-Michel Roquejoffre, Mingmin Zhang

In this paper, we revisit the famous Kermack-McKendrick model with nonlocal spatial interactions by shedding new lights on associated spreading properties and we also prove the existence and uniqueness of traveling fronts. Unlike previous studies that have focused on integrated versions of the model for susceptible population, we analyze the long time dynami

Ruohong Zhang, Yau-Shian Wang, Yiming Yang

The remarkable performance of large language models (LLMs) in zero-shot language understanding has garnered significant attention. However, employing LLMs for large-scale inference or domain-specific fine-tuning requires immense computational resources due to their substantial model size. To overcome these limitations, we introduce a novel method, namely Gen

Chun-Khiang Chua

We study $\bar B_q\to {{\rm\bf B}\bar{\rm\bf B}}' l \bar\nu$ and $\bar B_q\to {{\rm\bf B}\bar{\rm\bf B}}' \nu \bar\nu$ decays with all low lying octet and decuplet baryons using a topological amplitude approach. In tree induced $\bar B_q\to {{\rm\bf B}\bar{\rm\bf B}}' l \bar\nu$ decay modes, we need 2 tree and 1 annihilation amplitudes in octet-anti-octet de

Hogun Park, Aly Megahed, Peifeng Yin, Yuya Ong

Machine learning (ML) models have been quite successful in predicting outcomes in many applications. However, in some cases, domain experts might have a judgment about the expected outcome that might conflict with the prediction of ML models. One main reason for this is that the training data might not be totally representative of the population. In this pap

Vinay Shukla, A. Swaminathan

When the co-recursion and co-dilation in the recurrence relation of certain sequences of orthogonal polynomials are not at the same level, the behaviour of the modified orthogonal polynomials is expected to have different properties compared to the situation of the same level of perturbation. This manuscript attempts to derive structural relations between th

Mingjie Li, Ben Beck, Tharindu Rathnayake, Lingheng Meng

Cycling is a healthy and sustainable mode of transport. However, interactions with motor vehicles remain a key barrier to increased cycling participation. The ability to detect potentially dangerous interactions from on-bike sensing could provide important information to riders and policymakers. A key influence on rider comfort and safety is close passes, i.

Aradhana Kumari, Md Samsuzzaman, Arnab Saha, Sourabh Lahiri

The area of stochastic heat engines using active particles has attracted a lot of attention recently. They have been shown to exhibit advantages over engines using passive particles. In this work, we use multiple self-propelling particles undergoing Vicsek-like aligning interaction as our working system. The particles are confined in a two-dimensional circul

Vishal Agrawal, Ajay Prajapati, Abhilash Sahu, Tanmoy Som

In this article, we show that $\alpha$-fractal functions defined on Sierpi\'nski gasket (denoted by $\triangle$) depend continuously on the parameters involved in the construction. In the latter part of this article, the continuous dependence of parameters on $\alpha$-fractal functions defined on $\triangle$ is shown graphically.

Ludvig af Klinteberg

This paper presents a quadrature method for evaluating layer potentials in two dimensions close to periodic boundaries, discretized using the trapezoidal rule. It is an extension of the method of singularity swap quadrature, which recently was introduced for boundaries discretized using composite Gauss-Legendre quadrature. The original method builds on swapp

Chong Wang, Xiao-Wei Zhang, Xiaoyu Liu, Yuchi He

A recent experiment has reported the first observation of a zero-field fractional Chern insulator (FCI) phase in twisted bilayer MoTe$_2$ moir\'e superlattices [Nature 622, 63-68 (2023)]. The experimental observation is at an unexpected large twist angle 3.7$^\circ$ and calls for a better understanding of the FCI in real materials. In this work, we perform l

Long MA, Piet Van Mieghem, Maksim Kitsak

Epidemic forecasts are only as good as the accuracy of epidemic measurements. Is epidemic data, particularly COVID-19 epidemic data, clean and devoid of noise? Common sense implies the negative answer. While we cannot evaluate the cleanliness of the COVID-19 epidemic data in a holistic fashion, we can assess the data for the presence of reporting delays. In

Didi Zhu, Yincuan Li, Junkun Yuan, Zexi Li

Universal domain adaptation (UniDA) aims to transfer knowledge from the source domain to the target domain without any prior knowledge about the label set. The challenge lies in how to determine whether the target samples belong to common categories. The mainstream methods make judgments based on the sample features, which overemphasizes global information w

Chinasa T. Okolo

Explainable AI (XAI) is often promoted with the idea of helping users understand how machine learning models function and produce predictions. Still, most of these benefits are reserved for those with specialized domain knowledge, such as machine learning developers. Recent research has argued that making AI explainable can be a viable way of making AI more

Shaowu Pan, Karthik Duraisamy

The Koopman operator provides a linear perspective on non-linear dynamics by focusing on the evolution of observables in an invariant subspace. Observables of interest are typically linearly reconstructed from the Koopman eigenfunctions. Despite the broad use of Koopman operators over the past few years, there exist some misconceptions about the applicabilit

Matthieu Malléjac, Romain Fleury

Scattering wave systems that are periodically modulated in time offer many new degrees of freedom to control waves both in spatial and frequency domains. Such systems, albeit linear, do not conserve frequency and require the adaptation of the usual theories and methods. In this paper, we provide a general extension of transmission line or telegraph equations

Pamela C. Zurita, Daniel P. Benalcazar, Juan E. Tapia

Fitness for Duty (FFD) techniques detects whether a subject is Fit to perform their work safely, which means no reduced alertness condition and security, or if they are Unfit, which means alertness condition reduced by sleepiness or consumption of alcohol and drugs. Human iris behaviour provides valuable information to predict FFD since pupil and iris moveme

Rui Zhang, Luziwei Leng, Kaiwei Che, Hu Zhang

Spiking neural networks (SNNs), known for their low-power, event-driven computation and intrinsic temporal dynamics, are emerging as promising solutions for processing dynamic, asynchronous signals from event-based sensors. Despite their potential, SNNs face challenges in training and architectural design, resulting in limited performance in challenging even

Jiwook Kim, Minhyeok Lee

In financial engineering, portfolio optimization has been of consistent interest. Portfolio optimization is a process of modulating asset distributions to maximize expected returns and minimize risks. To obtain the expected returns, deep learning models have been explored in recent years. However, due to the deterministic nature of the models, it is difficul

Haoyu Wang, Guansong Pang, Peng Wang, Lei Zhang

Few-shot open-set recognition (FSOR) is a challenging task of great practical value. It aims to categorize a sample to one of the pre-defined, closed-set classes illustrated by few examples while being able to reject the sample from unknown classes. In this work, we approach the FSOR task by proposing a novel energy-based hybrid model. The model is composed

Hoang Huy Nguyen, Siva Theja Maguluri

We consider a nonlinear discrete stochastic control system, and our goal is to design a feedback control policy in order to lead the system to a prespecified state. We adopt a stochastic approximation viewpoint of this problem. It is known that by solving the corresponding continuous-time deterministic system, and using the resulting feedback control policy,

Marcin Waniek, Navya Suri, Abdullah Zameek, Bedoor AlShebli

Attribute inference - the process of analyzing publicly available data in order to uncover hidden information - has become a major threat to privacy, given the recent technological leap in machine learning. One way to tackle this threat is to strategically modify one's publicly available data in order to keep one's private information hidden from attribute i

Didier El Baz

Large Language Models (LLM) are studied. Applications to chatbots and education are considered. A case study on Leonardo's contribution to astronomy is presented. Major problems with accuracy, reproducibility and traceability of answers are reported for ChatGPT, GPT-4, BLOOM and Google Bard. Possible reasons for problems are discussed and some solutions are

Fredrik Lohne Aanes, Geir Storvik

In this paper we study the type IV Knorr Held space time models. Such models typically apply intrinsic Markov random fields and constraints are imposed for identifiability. INLA is an efficient inference tool for such models where constraints are dealt with through a conditioning by kriging approach. When the number of spatial and/or temporal time points bec

Reinhard M. Grassmann, Chengnan Shentu, Taqi Hamoda, Puspita Triana Dewi

Experiments on physical continuum robot are the gold standard for evaluations. Currently, as no commercial continuum robot platform is available, a large variety of early-stage prototypes exists. These prototypes are developed by individual research groups and are often used for a single publication. Thus, a significant amount of time is devoted to creating

Yi Qin, Xinyue Gao, Lele Chen, Liangliang Jiang

This paper develops a new 2D/3D stochastic closed-loop geothermal system with a random hydraulic conductivity tensor. We use the finite element method (FEM) and the Monte Carlo method (MCM) to discrete physical and probability spaces, respectively. This FEM-MCM method is effective. The stability for velocity and temperature is rigorously proved. Compared wit

S. M. Udhaya Sankar, D. Selvaraj, G. K. Monica, Jeevaa Katiravan

With the help of a shared pool of reconfigurable computing resources, clients of the cloud-based model can keep sensitive data remotely and access the apps and services it offers on-demand without having to worry about maintaining and storing it locally. To protect the privacy of the public auditing system that supports the cloud data exchange system. The da

Zhenning Cai, Bo Lin, Meixia Lin

This paper presents a novel Fourier spectral method that utilizes optimization techniques to ensure the positivity and conservation of moments in the space of trigonometric polynomials. We rigorously analyze the accuracy of the new method and prove that it maintains spectral accuracy. To solve the optimization problem, we propose an efficient Newton solver t

Yun He, Danhang Tang, Yinda Zhang, Xiangyang Xue

Most existing point cloud upsampling methods have roughly three steps: feature extraction, feature expansion and 3D coordinate prediction. However,they usually suffer from two critical issues: (1)fixed upsampling rate after one-time training, since the feature expansion unit is customized for each upsampling rate; (2)outliers or shrinkage artifact caused by

Milutin Obradović, Nikola Tuneski

Let $\mathcal{U(\alpha, \lambda)}$, $0<\alpha <1$, $0 < \lambda <1$ be the class of functions $f(z)=z+a_{2}z^{2}+a_{3}z^{3}+\cdots$ satisfying $$\left|\left(\frac{z}{f(z)}\right)^{1+\alpha}f'(z)-1\right|<\lambda$$ in the unit disc ${\mathbb D}$. For $f\in \mathcal{U(\alpha, \lambda)}$ we give sharp bounds of its initial logarithmic coefficients $\gamma_{1},\

Cesar Gomez

Gauge invariant local observables describing primordial scalar quantum fluctuations in Inflationary Cosmology are identified as elements of a type $II$ de Sitter crossed product algebra. This algebra is defined, after adding a reference frame clock, as the algebra of clock dressed local operators. Clock dressing sets, in the weak gravity limit, the Schroding

Debasish Borah, Suruj Jyoti Das, Rishav Roshan, Rome Samanta

We study the effect of an ultra-light primordial black hole (PBH) dominated phase on the gravitational wave (GW) spectrum generated by a cosmic string (CS) network formed as a result of a high-scale $U(1)$ symmetry breaking. A PBH-dominated phase leads to tilts in the spectrum via entropy dilution and generates a new GW spectrum from PBH density fluctuations

Bhera Ram, Bibhas Ranjan Majhi

Using recently developed consistent and robust first order relativistic hydrodynamics of a dissipative fluid we propose a generalization but weak version of Tolman-Ehrenfest relation and Klein's law on a general background spacetime. These relations are appeared to be a consequence of thermal equilibrium state of the fluid, defined by the absence of heat flu

Yonggan Fu, Zhifan Ye, Jiayi Yuan, Shunyao Zhang

Novel view synthesis is an essential functionality for enabling immersive experiences in various Augmented- and Virtual-Reality (AR/VR) applications, for which generalizable Neural Radiance Fields (NeRFs) have gained increasing popularity thanks to their cross-scene generalization capability. Despite their promise, the real-device deployment of generalizable

Pei Liu, Ruixia Wang, Jing-Ning Zhang, Yingshan Zhang

Quantum computation architecture based on $d$-level systems, or qudits, has attracted considerable attention recently due to their enlarged Hilbert space. Extensive theoretical and experimental studies have addressed aspects of algorithms and benchmarking techniques for qudit-based quantum computation and quantum information processing. Here, we report a phy

Yadang Chen, Dingwei Zhang, Zhi-xin Yang, Enhua Wu

This paper proposes a Robust and Efficient Memory Network, referred to as REMN, for studying semi-supervised video object segmentation (VOS). Memory-based methods have recently achieved outstanding VOS performance by performing non-local pixel-wise matching between the query and memory. However, these methods have two limitations. 1) Non-local matching could

Naoya Onizawa, Kyo Kuroki, Duckgyu Shin, Takahiro Hanyu

This paper presents a local energy distribution based hyperparameter determination for stochastic simulated annealing (SSA). SSA is capable of solving combinatorial optimization problems faster than typical simulated annealing (SA), but requires a time-consuming hyperparameter search. The proposed method determines hyperparameters based on the local energy d

Zhen Qin

Sparse structures are widely recognized and utilized in channel estimation. Two typical mechanisms, namely proportionate updating (PU) and zero-attracting (ZA) techniques, achieve better performance, but their computational complexity are higher than non-sparse counterparts. In this paper, we propose a DCS technique based on the recursive least squares (RLS)

Yao Su, Pengkang Yu, Matthew J. Gerber, Lecheng Ruan

Propeller failure is a major cause of multirotor Unmanned Aerial Vehicles (UAVs) crashes. While conventional multirotor systems struggle to address this issue due to underactuation, over-actuated platforms can continue flying with appropriate fault-tolerant control (FTC). This paper presents a robust FTC controller for an over-actuated UAV platform composed

Sizheng Ma, Vijay Varma, Leo C. Stein, Francois Foucart

We present a numerical-relativity simulation of a black hole - neutron star merger in scalar-tensor (ST) gravity with binary parameters consistent with the gravitational wave event GW200115. In this exploratory simulation, we consider the Damour-Esposito-Farese extension to Brans-Dicke theory, and maximize the effect of spontaneous scalarization by choosing

Yonggan Fu, Yuecheng Li, Chenghui Li, Jason Saragih

Real-time and robust photorealistic avatars for telepresence in AR/VR have been highly desired for enabling immersive photorealistic telepresence. However, there still exists one key bottleneck: the considerable computational expense needed to accurately infer facial expressions captured from headset-mounted cameras with a quality level that can match the re

Yonggan Fu, Ye Yuan, Shang Wu, Jiayi Yuan

Transfer learning leverages feature representations of deep neural networks (DNNs) pretrained on source tasks with rich data to empower effective finetuning on downstream tasks. However, the pretrained models are often prohibitively large for delivering generalizable representations, which limits their deployment on edge devices with constrained resources. T

Pravin Kumar Dahal, Fil Simovic

The Vaidya metric serves as a useful model-building tool that captures many essential features of dynamical and/or evaporating black hole spacetimes. Working in a semiclassical setting, we show that in the limit of slow evaporation, a general spherically symmetric metric subject to certain regularity conditions is uniquely described by a linear ingoing Vaidy

Dongyang Liu, Meina Kan, Shiguang Shan, Xilin Chen

Feature distillation makes the student mimic the intermediate features of the teacher. Nearly all existing feature-distillation methods use L2 distance or its slight variants as the distance metric between teacher and student features. However, while L2 distance is isotropic w.r.t. all dimensions, the neural network's operation on different dimensions is usu

Janhavi Baghel, P. Kharb, Silpa S., Luis C. Ho

With high-sensitivity kiloparsec-scale radio polarimetry, we can examine the jet-medium interactions and get a better understanding of the blazar divide in radio-loud (RL) AGN. We are analyzing the radio polarimetric observations with the EVLA and GMRT of 24 quasars and BL Lacs belonging to the Palomar-Green (PG) sample. The RL quasars show extensive polaris

Chao Ju

The Hilbert space of level $q$ Chern-Simons theory of gauge group $G$ of the ADE type quantized on $T^2$ can be represented by points that lie on the weight lattice of the Lie algebra $\mathfrak{g}$ up to some discrete identifications. Of special significance are the points that also lie on the root lattice. The generating functions that count the number of

Zeyu Lu, Chengyue Wu, Xinyuan Chen, Yaohui Wang

Diffusion models have attained impressive visual quality for image synthesis. However, how to interpret and manipulate the latent space of diffusion models has not been extensively explored. Prior work diffusion autoencoders encode the semantic representations into a semantic latent code, which fails to reflect the rich information of details and the intrins

Min Yi, Ming Xue, Peihong Cong, Yang Song

Fatigue properties of additively manufactured (AM) materials depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities, post-treatments, etc. Their evaluation inevitably requires these factors combined as many as possible, thus resulting in low efficiency and high cost. In recent years, their asses

Shivansh Walia, Tejas Iyer, Shubham Tripathi, Akshith Vanaparthy

This project presents an implementation and designing of safe, secure and smart home with enhanced levels of security features which uses IoT-based technology. We got our motivation for this project after learning about movement of west towards smart homes and designs. This galvanized us to engage in this work as we wanted for homeowners to have a greater co

Marc Hellmuth, Peter F. Stadler

Most genes are part of larger families of evolutionary related genes. The history of gene families typically involves duplications and losses of genes as well as horizontal transfers into other organisms. The reconstruction of detailed gene family histories, i.e., the precise dating of evolutionary events relative to phylogenetic tree of the underlying speci

Zakary Georgis-Yap, Milos R. Popovic, Shehroz S. Khan

Epilepsy affects more than 50 million people worldwide, making it one of the world's most prevalent neurological diseases. The main symptom of epilepsy is seizures, which occur abruptly and can cause serious injury or death. The ability to predict the occurrence of an epileptic seizure could alleviate many risks and stresses people with epilepsy face. We for

Carlos Cancino-Chacón, Silvan Peter, Patricia Hu, Emmanouil Karystinaios

This paper introduces the ACCompanion, an expressive accompaniment system. Similarly to a musician who accompanies a soloist playing a given musical piece, our system can produce a human-like rendition of the accompaniment part that follows the soloist's choices in terms of tempo, dynamics, and articulation. The ACCompanion works in the symbolic domain, i.e.

Woundjiagué Apollinaire, Rodwell Kufakunesu, Julius Esunge

In this research, we present an analysis of the optimal investment, consumption, and life insurance acquisition problem for a wage earner with partial information. Our study considers the non-linear filter case where risky asset prices are correlated to the factor processes under constant relative risk aversion (CRRA) preferences. We introduce a more general

Arkadeep Narayan Chaudhury, Leonid Keselman, Christopher G. Atkeson

Controlling illumination can generate high quality information about object surface normals and depth discontinuities at a low computational cost. In this work we demonstrate a robot workspace-scaled controlled illumination approach that generates high quality information for table top scale objects for robotic manipulation. With our low angle of incidence d

Mingli Zhu, Shaokui Wei, Li Shen, Yanbo Fan

Backdoor defense, which aims to detect or mitigate the effect of malicious triggers introduced by attackers, is becoming increasingly critical for machine learning security and integrity. Fine-tuning based on benign data is a natural defense to erase the backdoor effect in a backdoored model. However, recent studies show that, given limited benign data, vani

Rakesh Mohan Das, Masahiko Iwasaki

We study the enhancement of the magnetic dipole induced excitation probability of the hyperfine ground state of Doppler-broadened muonic hydrogen ($p \mu^{-}$) by a nanosecond laser pulse in the mid-infrared range with Gaussian temporal shape such that the pulse bandwidth is broader than the Doppler width at 10~K. The enhancement is achieved by shrinking the

Shunli Ren, Zixing Lei, Zi Wang, Mehrdad Dianati

Cooperative perception can significantly improve the perception performance of autonomous vehicles beyond the limited perception ability of individual vehicles by exchanging information with neighbor agents through V2X communication. However, most existing work assume ideal communication among agents, ignoring the significant and common \textit{interruption

Seongyong Lee, Choongjae Won, Jimin Kim, Jonggyu Yoo

Kagome lattice materials offer a fertile ground to discover novel quantum phases of matter, ranging from unconventional superconductivity and quantum spin liquids to charge orders of various profiles. However, understanding the genuine origin of the quantum phases in kagome materials is often challenging, owing to the intertwined atomic, electronic, and stru

Takuto Narita, Hiroyuki Uchida, Takashi Yoshida, Takaaki Tanaka

Stellar winds blown out from massive stars ($\gtrsim 10M_{\odot}$) contain precious information on the progenitor itself, and in this context, the most important elements are carbon (C), nitrogen (N), and oxygen (O), which are produced by the CNO cycle in the H-burning layer. Although their X-ray fluorescence lines are expected to be detected in swept-up sho

Hao Tang, Songhua Liu, Tianwei Lin, Shaoli Huang

Transformer-based models achieve favorable performance in artistic style transfer recently thanks to its global receptive field and powerful multi-head/layer attention operations. Nevertheless, the over-paramerized multi-layer structure increases parameters significantly and thus presents a heavy burden for training. Moreover, for the task of style transfer,

Shuangge Wang, Yiwei Lyu, John M. Dolan

Autonomous agents (robots) face tremendous challenges while interacting with heterogeneous human agents in close proximity. One of these challenges is that the autonomous agent does not have an accurate model tailored to the specific human that the autonomous agent is interacting with, which could sometimes result in inefficient human-robot interaction and s

Abhishek Ramdas Nair, Pallab Kumar Nath, Shantanu Chakrabartty, Chetan Singh Thakur

Wildlife conservation using continuous monitoring of environmental factors and biomedical classification, which generate a vast amount of sensor data, is a challenge due to limited bandwidth in the case of remote monitoring. It becomes critical to have classification where data is generated, and only classified data is used for monitoring. We present a novel

Suvra Pal, Wisdom Aselisewine

The promotion time cure rate model (PCM) is an extensively studied model for the analysis of time-to-event data in the presence of a cured subgroup. There are several strategies proposed in the literature to model the latency part of PCM. However, there aren't many strategies proposed to investigate the effects of covariates on the incidence part of PCM. In

Giovanni Picotti, Michael E. Cholette, Cody B. Anderson, Theodore A. Steinberg

Reflectance losses on solar mirrors due to soiling are a significant challenge for Concentrating Solar Power (CSP) plants. Soiling losses can vary significantly from site to site -- with (absolute) reflectance losses varying from fractions of a percentage point up to several percentage points per day (pp/day), a fact that has motivated several studies in soi

Motokazu Abe, Okuto Morikawa, Soma Onoda

Topology and generalized symmetries in the $SU(N)/\mathbb{Z}_N$ gauge theory are considered in the continuum and the lattice. Starting from the $SU(N)$ gauge theory with the 't~Hooft twisted boundary condition, we give a simpler explanation of the van~Baal's proof on the fractionality of the topological charge. This description is applicable to both continuu

Guangzhe Hou, Guihe Qin, Minghui Sun, Yanhua Liang

Point clouds obtained from capture devices or 3D reconstruction techniques are often noisy and interfere with downstream tasks. The paper aims to recover the underlying surface of noisy point clouds. We design a novel model, NoiseTrans, which uses transformer encoder architecture for point cloud denoising. Specifically, we obtain structural similarity of poi

Shan-Zhong Li, Zhi Li

We study $p$-wave superconducting quasiperiodic chains with staggered potential. The result shows a counter-intuitive phase transition phenomenon, i.e., recurrent extension phase transition (REPT). By analyzing the participation ration and scaling behavior, we prove the existence of REPT phenomenon, which, in concrete terms, means that the system will repeat

Shu Wei, Nuo Xu

Document layout analysis has a wide range of requirements across various domains, languages, and business scenarios. However, most current state-of-the-art algorithms are language-dependent, with architectures that rely on transformer encoders or language-specific text encoders, such as BERT, for feature extraction. These approaches are limited in their abil

Malte Kampschulte, Boris Muha, Srđan Trifunović

In this paper, we study an interaction problem between a $3D$ compressible viscous fluid and a $3D$ nonlinear viscoelastic solid fully immersed in the fluid, coupled together on the interface surface. The solid is allowed to have self-contact or contact with the rigid boundary of the fluid container. For this problem, a global weak solution with defect measu

Halim Lee, Jiwon Seo

The maximum likelihood (ML) estimator can be applied to localize a target mobile device using the RSS and TOA. However, the ML estimator for the RSS-TOA-based target localization problem is nonconvex and nonlinear, having no analytical solution. Therefore, the ML estimator should be solved numerically, unless it is relaxed into a convex or linear form. This

Jorge Alfaro

Mandelstam-Leibbrandt(ML) regularization of Very Special Relativity (VSR) amplitudes in momentum space depends on two fixed null vectors $n_\mu,\bar{n}_\mu$ besides external momenta. ML is known to preserve gauge invariance and naive power counting. The second null vector $\bar{n}_\mu$ destroys the $Sim(2)$ symmetry of the VSR model. We devise a systematic p