August 2024 arXiv papers — page 3

Jia-Jing He, Yan Xu, Yi-Bo Wang, Xiu-Lin Huang

The research of the properties of neutron stars with dark energy is a particularly interesting yet unresolved problem in astrophysics. We analyze the influence of dark energy on the equation of state, the maximum mass, the surface gravitational redshift, and the Keplerian frequency for the traditional neutron star and the hyperon star matter within the relat

Ángel D. Martínez

In this paper we use the convex integration technique enhanced by an extra iteration originally due to Källén and revisited by Kröner to provide a local $h$-principle for isometric embeddings in the class $C^{1,1-ε}$ for $n$-dimensional manifolds in codimension $\frac{1}{2}n(n+1)$.

Ángel D. Martínez

We devote this paper to provide an abstract generalization of an iteration originally due to Källén, and revisited later by Kröner, that might be of independent interest.

Anoushka Harit, Zhongtian Sun, Jongmin Yu, Noura Al Moubayed

In the fast-paced and volatile financial markets, accurately predicting stock movements based on financial news is critical for investors and analysts. Traditional models often struggle to capture the intricate and dynamic relationships between news events and market reactions, limiting their ability to provide actionable insights. This paper introduces a no

Nicolás A. Loubet, Alejandro R. Verde, Gustavo A. Appignanesi

The peculiar structuring of liquid water stems from a fine-tuned molecular principle embodying the two different interaction demands of the water molecule: The formation of hydrogen bonds or the compensation for coordination defects. Here we shall show that the same underlying molecular mechanism is also at play in order to establish favorable interactions w

Paolo Muratore-Ginanneschi, Gen Kimura, Dariusz Chruściński

Relaxation rates provide important characteristics both for classical and quantum processes. Essentially they control how fast the system thermalizes, equilibrates, {decoheres, and/or dissipates}. Moreover, very often they are directly accessible to be measured in the laboratory and hence they define key physical properties of the system. Experimentally meas

Tianyang Chu, Hailong Guo, Zhimin Zhang

Monge-Ampère equation is a prototype second-order fully nonlinear partial differential equation. In this paper, we propose a new idea to design and analyze the $C^0$ interior penalty method to approximation the viscosity solution of the Monge-Ampère equation. The new methods is inspired from the discrete Miranda-Talenti estimate. Based on the vanishing momen

Ogun Yurdakul, Erik Ela, Farhad Billimoria

Flexible ramping products (FRPs) emerge as a promising instrument for addressing steep and uncertain ramping needs through market mechanisms. Initial implementations of FRPs in North American electricity markets, however, revealed several shortcomings in existing FRP designs. In many instances, FRP prices failed to signal the true value of ramping capacity,

Tomos Parry

Nguyen has shown that on averaging over $a=1,...,q$ the 3-fold divisor function has exponent of distribution 2/3, following \cite {banks}. We follow [2] which leads to stronger bounds.

Wilhiam de Carvalho, Ahmad Attarha, Hemanshu R. Pota

We propose a combined global-local control approach to regulate voltage and minimize power losses in distribution networks with high integration of distributed energy resources (DERs). Local controllers embed the fast acting proportional volt-var-watt control law and have their gain (slope) coefficients updated regularly by a global optimization problem at a

Maximilian Fels, Lisa Hartung, Oren Louidor

This is the second in a series of two works which study the discrete Gaussian free field on the binary tree when all leaves are conditioned to be positive. In the first work ("Gaussian free field on the tree subject to a hard wall I: Bounds") we identified the repulsion profile followed by the field in order to fulfill this "hard-wall constraint&

Thijmen Nijdam, Juell Sprott, Taiki Papandreou-Lazos, Jurgen de Heus

In this study, we undertake a reproducibility analysis of 'Learning Fair Graph Representations Via Automated Data Augmentations' by Ling et al. (2022). We assess the validity of the original claims focused on node classification tasks and explore the performance of the Graphair framework in link prediction tasks. Our investigation reveals that we can

Giovanni Gentili, Luigi Vezzoni

We consider a general class of elliptic equations on hypercomplex manifolds which includes the quaternionic Monge-Ampère equation, the quaternionic Hessian equation and the Monge-Ampère equation for quaternionic $(n-1)$-plurisubharmonic functions. We prove that under suitable assumptions the solutions to these equations on hyperkähler manifolds satisfy a $C^

Kosuke Nakanishi, Akihiro Kubo, Yuji Yasui, Shin Ishii

Recently, robust reinforcement learning (RL) methods against input observation have garnered significant attention and undergone rapid evolution due to RL's potential vulnerability. Although these advanced methods have achieved reasonable success, there have been two limitations when considering adversary in terms of long-term horizons. First, the mutual

Ming Cai, Penggang Gao, Hisayuki Hara

This paper discusses algorithms for learning causal DAGs. The PC algorithm makes no assumptions other than the faithfulness to the causal model and can identify only up to the Markov equivalence class. LiNGAM assumes linearity and continuous non-Gaussian disturbances for the causal model, and the causal DAG defining LiNGAM is shown to be fully identifiable.

Miguel C. Herculano

Frazzini and Pedersen (2014) Betting Against Beta (BAB) factor is based on the idea that high beta assets trade at a premium and low beta assets trade at a discount due to investor funding constraints. However, as argued by Campbell and Vuolteenaho (2004), beta comes in "good" and "bad" varieties. While gaining exposure to low-beta, BAB facto

Ching-Hsiu Chen, Wei-Hao Hsu, Ryoko Oishi-Tomiyasu, Chi-Cheng Lee

Water hydrogen bonding is extremely versatile; approximately 20 ice structures and several types of clathrate hydrate structures have been identified. These crystalline water structures form at temperatures below room temperature and/or at high pressure. We used transmission electron microscopy to study a new crystalline water structure in a clathrate state

Daniel Varab, Christian Hardmeier

Recent work has suggested that end-to-end system designs for cross-lingual summarization are competitive solutions that perform on par or even better than traditional pipelined designs. A closer look at the evidence reveals that this intuition is based on the results of only a handful of languages or using underpowered pipeline baselines. In this work, we co

Alan Boyle, Isha Gupta, Sebastian Hönig, Lukas Mautner

As language models have become increasingly successful at a wide array of tasks, different prompt engineering methods have been developed alongside them in order to adapt these models to new tasks. One of them is Tree-of-Thoughts (ToT), a prompting strategy and framework for language model inference and problem-solving. It allows the model to explore multipl

Leenoy Meshulam, William Bialek

Perceptions and actions, thoughts and memories result from coordinated activity in hundreds or even thousands of neurons in the brain. It is an old dream of the physics community to provide a statistical mechanics description for these and other emergent phenomena of life. These aspirations appear in a new light because of developments in our ability to meas

Shangquan Sun, Wenqi Ren, Juxiang Zhou, Jianhou Gan

Existing deraining Transformers employ self-attention mechanisms with fixed-range windows or along channel dimensions, limiting the exploitation of non-local receptive fields. In response to this issue, we introduce a novel dual-branch hybrid Transformer-Mamba network, denoted as TransMamba, aimed at effectively capturing long-range rain-related dependencies

Dinh-Thi Nguyen

In two-dimensional space, we consider a system of $N$ anyons interacts via a short range attractive two-body interaction. In the stable regime, we derive the average-field Pauli functional as the mean-field limit of many-body quantum mechanics. Furthermore, we investigate the collapse phenomenon in the collapse regime where the strength of attractions tends

Duygu Dogan, Huang Xie, Toni Heittola, Tuomas Virtanen

Zero-shot learning models are capable of classifying new classes by transferring knowledge from the seen classes using auxiliary information. While most of the existing zero-shot learning methods focused on single-label classification tasks, the present study introduces a method to perform multi-label zero-shot audio classification. To address the challenge

Chao Dang, Marcos A. Valdebenito, Nataly A. Manque, Jun Xu

Estimation of the response probability distributions of computer simulators in the presence of randomness is a crucial task in many fields. However, achieving this task with guaranteed accuracy remains an open computational challenge, especially for expensive-to-evaluate computer simulators. In this work, a Bayesian active learning perspective is presented t

J. W. E. Harrow, A. N. W. Hone

Motivated by the search for an appropriate notion of a cluster superalgebra, incorporating Grassmann variables, Ovsienko and Tabachnikov considered the extension of various recurrence relations with the Laurent phenomenon to the ring of dual numbers. Furthermore, by iterating recurrences with specific numerical values, some particular well-known integer sequ

Wenhao Zhuang, Xinyu He, Yuyi Mao, Juan Liu

Future wireless networks are envisioned to support both sensing and artificial intelligence (AI) services. However, conventional integrated sensing and communication (ISAC) networks may not be suitable due to the ignorance of diverse task-specific data utilities in different AI applications. In this letter, a full-duplex unmanned aerial vehicle (UAV)-enabled

Minjia Shi, Sihui Tao, Jihoon Hong, Jon-Lark Kim

Self-dual codes have been studied actively because they are connected with mathematical structures including block designs and lattices and have practical applications in quantum error-correcting codes and secret sharing schemes. Nevertheless, there has been less attention to construct self-dual codes from self-orthogonal codes with smaller dimensions. Hence

Yun Liu, Hao Zhao, Huazhen Yao, Zeng Hu

In recent years, orthogonal chirp division modulation (OCDM) has gained attention as a robust communication waveform due to its strong resistance to both time-domain and frequency-domain interference. However, similar to orthogonal frequency division multiplexing (OFDM), OCDM suffers from a high peak-to-average power ratio (PAPR), resulting in increased hard

Miki Hirano, Taku Ishii, Tadashi Miyazaki

We give explicit formulas of Whittaker functions on GL(4,R) for all irreducible generic representations. As an application, we determine test vectors which attain the associated L-factors for Bump-Friedberg integrals on GL(4,R).

Qiang Zhang, Zhipeng Teng, Disheng Wu, Jiayin Wang

In industrial recommendation systems on websites and apps, it is essential to recall and predict top-n results relevant to user interests from a content pool of billions within milliseconds. To cope with continuous data growth and improve real-time recommendation performance, we have designed and implemented a high-performance batch query architecture for re

Fatna Abdedou, Bassam Fayad, Jean-Paul Thouvenot

We show that every ergodic dynamical system induces a system with pure Lebesgue spectrum of infinite multiplicity.

Yu-Fan Lin, Ching-Heng Cheng, Bo-Cheng Qiu, Cheng-Jun Kang

Fusarium Head Blight (FHB) is a serious fungal disease affecting wheat (including durum), barley, oats, other small cereal grains, and corn. Effective monitoring and accurate detection of FHB are crucial to ensuring stable and reliable food security. Traditionally, trained agronomists and surveyors perform manual identification, a method that is labor-intens

Michael Th. Rassias

We investigate the behaviour of a certain additive function depending on prime divisors of specific integers lying in large gaps between consecutive primes. The result is obtained by a combination of results and ideas related to large gaps between primes and the Erdös-Kac theorem, especially the Kubilius model from Probabilistic Number Theory.

Jaime E. Pineda, Juan D. Soler, Stella Offner, Eric W. Koch

Context. Turbulence is a key component of molecular cloud structure. It is usually described by a cascade of energy down to the dissipation scale. The power spectrum for subsonic incompressible turbulence is $k^{-5/3}$, while for supersonic turbulence it is $k^{-2}$. Aims. We aim to determine the power spectrum in an actively star-forming molecular cloud, fr

Georgios Ioannides, Adrian Kieback, Aman Chadha, Aaron Elkins

Speech-based depression detection poses significant challenges for automated detection due to its unique manifestation across individuals and data scarcity. Addressing these challenges, we introduce DAAMAudioCNNLSTM and DAAMAudioTransformer, two parameter efficient and explainable models for audio feature extraction and depression detection. DAAMAudioCNNLSTM

Qingbin Tian, Yukang Huo, Mingyuan Yao, Haihua Wang

Dead fish frequently appear on the water surface due to various factors. If not promptly detected and removed, these dead fish can cause significant issues such as water quality deterioration, ecosystem damage, and disease transmission. Consequently, it is imperative to develop rapid and effective detection methods to mitigate these challenges. Conventional

Tianrui Wang, Jin Li, Ziyang Ma, Rui Cao

Self-supervised learning (SSL) has garnered significant attention in speech processing, excelling in linguistic tasks such as speech recognition. However, jointly improving the performance of pre-trained models on various downstream tasks, each requiring different speech information, poses significant challenges. To this purpose, we propose a progressive res

Xiangdi Huang, Weili Meng, Anchun Ni

This paper is devoted to the study of free-boundary-value problem of the compressible Naiver-Stokes system with density-dependent viscosities $μ=const>0,λ=ρ^β$ which was first introduced by Vaigant-Kazhikhov \cite{1995 Vaigant-Kazhikhov-SMJ} in 1995. By assuming the endpoint case $β=1$ in the radially spherical symmetric setting, we prove the (a priori) expa

Rodolphe Grivet, Axel Huerre, Thomas Séon, Laurent Duchemin

We investigate experimentally the receding of a contact line when a Peltier module is pulled out of a water bath at constant speed, while a ice layer is also growing at constant speed on the Peltier module. A steady regime is therefore reached for all the parameters used in this studied, corresponding to a dynamical stationnary meniscus. We show that the hei

Wadim Zudilin

Given a newform with the Fourier expansion $\sum_{n=1}^\infty b(n)q^n\in\mathbb Z[[q]]$, a prime $p$ is said to be non-ordinary if $p\mid b(p)$. We exemplify several newforms of weight 4 for which the latter divisibility implies a stronger divisibility - a property that may be thought unlikely to happen too often.

Anish Kundu, Giulia Barbareschi, Midori Kawaguchi, Yuichiro Yano

In this paper we explore the potential of utilizing Virtual Reality (VR) as a therapeutic tool for supporting individuals in the LGBTQ+ community, who often face elevated risks of mental health issues. Specifically, we investigated the effectiveness of using pre-existing avatars compared to allowing individuals to create their own avatars through a website,

Kenta Kumagai

We consider the bifurcation diagram of radial solutions for the Gelfand problem with a positive radially symmetric weight in the unit ball. We deal with the exponential nonlinearity and a power-type nonlinearity. When the weight is constant, it is well-known that the bifurcation curve exhibits three different types depending on the dimension and the exponent

Toru Kitagawa, Jeff Rowley

Static supervised learning-in which experimental data serves as a training sample for the estimation of an optimal treatment assignment policy-is a commonly assumed framework of policy learning. An arguably more realistic but challenging scenario is a dynamic setting in which the planner performs experimentation and exploitation simultaneously with subjects

Stavros Akras, Isabel Aleman, Denise R. Gonçalves, Gerardo Ramos-Larios

Low-ionisation structures (LISs) are commonly found in planetary nebulae (PNe) but they are still poorly understood. The recent discovery of unforeseen molecular hydrogen gas (H2) has changed what we think we know about these microstructures and PNe. For an overall understanding of LISs, an [Fe II] 1.644$μ$m imagery survey in PNe with LISs was carried out wi

Shahabedin Nabavi, Kian Anvari Hamedani, Mohsen Ebrahimi Moghaddam, Ahmad Ali Abin

This study proposes an attention-based statistical distance-guided unsupervised domain adaptation model for multi-class cardiovascular magnetic resonance (CMR) image quality assessment. The proposed model consists of a feature extractor, a label predictor and a statistical distance estimator. An annotated dataset as the source set and an unlabeled dataset as

Solveig Klepper

Diffusion models have emerged from various theoretical and methodological perspectives, each offering unique insights into their underlying principles. In this work, we provide an overview of the most prominent approaches, drawing attention to their striking analogies -- namely, how seemingly diverse methodologies converge to a similar mathematical formulati

Zongzheng Cao, Menghan Liao, Hongyi Yan, Yuying Zhu

A conventional superconducting state may be replaced by another dissipationless state hosting Cooper pairs with a finite momentum, leaving thermodynamic footprints for such a phase transition. Recently, a novel type of finite momentum pairing, so-called orbital Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state, has been proposed to occur in spin-orbit coupled su

Juan E. Tapia, Naser Damer, Christoph Busch, Juan M. Espin

This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB2024). The competition attracted a total of ten registered teams, both from academia and industry. In the end, the participating teams submitted five valid submissions, with eight models to be eval

Stavros Akras, Hektor Monteiro, Jeremy R. Walsh, Lydia Konstantinou

We report the first spatially resolved detection of the near-infrared [C I] $λ$8727 emission from the outer pair of low-ionization structures in the planetary nebula NGC 7009 from data obtained by the Multi Unit Spectroscopic Explorer integral field unit. This atomic carbon emission marks the transition zone between ionized and neutral gas, and for the first

Takeshi Fukao, Masahiro Ikeda, Shun Uchida

In this paper, we consider an optimal control problem of an ordinary differential inclusion governed by the hypergraph Laplacian, which is defined as a subdifferential of a convex function and then is a set-valued operator. We can assure the existence of optimal control for a suitable cost function by using methods of a priori estimates established in the pr

Costas Mylonas, Titos Georgoulakis, Magda Foti

In this paper, we introduce a synergistic approach between artificial intelligence and system operators through an innovative digital twin architecture, integrated with an active learning framework, to enhance short-term load forecasting. Central to this architecture is the incorporation of sophisticated data pipelines, facilitating the real-time ingestion,

P. Achenbach, K. Aoki, S. Aoki, C. Curceanu

The mini proceedings of the "Fourth International Workshop on the Extension Project for the J-PARC Hadron Experimental Facility (HEF-ex 2024) [https://kds.kek.jp/event/46965]" held at J-PARC, February 19-21, 2024, are presented. The workshop was devoted to discussing the physics case that connects both the present and the future Hadron Experimental F

Phuong Le

We prove the monotonicity of positive solutions to the problem $-Δu = f(u)$ in $\mathbb{R}^N_+ := \{(x',x_N)\in\mathbb{R}^N \mid x_N>0 \}$ under zero Dirichlet boundary condition with a possible singular nonlinearity $f$. In some situations, we can derive a precise estimate on the blow-up rate of $\frac{\partial u}{\partialη}$ as $x_N \to 0^+$, where $(η

Wanming Hao, Xue Wu, Xingwang Li, Gangcan Sun

In this paper, we investigate an intelligent reflecting surface (IRS) assisted full-duplex (FD) integrated sensing, communication and computing system. Specifically, an FD base station (BS) provides service for uplink and downlink transmission, and a local cache is connected to the BS through a backhaul link to store data. Meanwhile, active sensing elements

Yagyank Srivastava, Ankit Jain

The calculation of material phonon thermal conductivity from density functional theory calculations requires computationally expensive evaluation of anharmonic interatomic force constants and has remained a computational bottleneck in the high-throughput discovery of materials. In this work, we present a machine learning-assisted approach for the extraction

Carlos Medel-Ramírez, Hilario Medel-López

The article focuses on the urgent issue of femicide in Veracruz, Mexico, and the development of the MFM_FEM_VER_CP_2024 model, a mathematical framework designed to predict femicide risk using fuzzy logic. This model addresses the complexity and uncertainty inherent in gender based violence by formalizing risk factors such as coercive control, dehumanization,

Weinan Dai, Yifeng Jiang, Yuanjing Liu, Jinkun Chen

This paper addresses the persistent challenge in Keyword Spotting (KWS), a fundamental component in speech technology, regarding the acquisition of substantial labeled data for training. Given the difficulty in obtaining large quantities of positive samples and the laborious process of collecting new target samples when the keyword changes, we introduce a no

Dongil Yang, Suyeon Lee, Minjin Kim, Jungsoo Won

Engagement between instructors and students plays a crucial role in enhancing students'academic performance. However, instructors often struggle to provide timely and personalized support in large classes. To address this challenge, we propose a novel Virtual Teaching Assistant (VTA) named YA-TA, designed to offer responses to students that are grounded

Nirmali Roy, Anuradha Jha

In this article, we address singularly perturbed two-parameter parabolic problem of the reaction-convection-diffusion type in two dimensions. These problems exhibit discontinuities in the source term and convection coefficient at particular domain points, which result in the formation of interior layers. The presence of two perturbation parameters leads to t

Vijay Higgins

We construct a quantum Frobenius map for the $SL_3$ skein module of any oriented 3-manifold specialized at a root of unity, and describe the map by way of threading certain polynomials along links. The homomorphism is a higher rank version of the Chebyshev-Frobenius homomorphism of Bonahon-Wong. The strategy builds on a previous construction of the Frobenius

Hsiang-Wei Huang, Jiacheng Sun, Cheng-Yen Yang, Zhongyu Jiang

Assessing gross motor development in toddlers is crucial for understanding their physical development and identifying potential developmental delays or disorders. However, existing datasets for action recognition primarily focus on adults, lacking the diversity and specificity required for accurate assessment in toddlers. In this paper, we present ToddlerAct

Paulo Soares, Sean McCurdy, Andrew J. Gerber, Peter Fonagy

Obtaining data in the medical field is challenging, making the adoption of AI technology within the space slow and high-risk. We evaluate whether we can overcome this obstacle with synthetic data generated by large language models (LLMs). In particular, we use GPT-4 and Claude 3 Opus to create agents that simulate adults with varying profiles, childhood memo

Kushal Kumar Jain, Ankith Varun J, Anoop Namboodiri

Portrait sketching involves capturing identity specific attributes of a real face with abstract lines and shades. Unlike photo-realistic images, a good portrait sketch generation method needs selective attention to detail, making the problem challenging. This paper introduces \textbf{Portrait Sketching StyleGAN (PS-StyleGAN)}, a style transfer approach tailo

Advait Gilankar, Abishek Katta, Nabasindhu Das, Nidhin Kurian Kalarickal

This work demonstrates high-performance vertical NiO/Ga2O3 heterojunction diodes (HJDs) with a 2-step space-modulated junction termination extension. Distinct from the current state-of-the-art Ga2O3 HJDs, we achieve breakdown voltage exceeding 3 kV with a low turn on voltage (VON) of 0.8V, estimated at a forward current density (IF) of 1 A-cm-2. The measured

Xiao Fang, Yi Lin, Dong Zhang, Kwang-Ting Cheng

Pre-trained large vision-language models (VLMs) like CLIP have revolutionized visual representation learning using natural language as supervisions, and demonstrated promising generalization ability. In this work, we propose ViP, a novel visual symptom-guided prompt learning framework for medical image analysis, which facilitates general knowledge transfer f

Hossein Khalili, Seongbin Park, Vincent Li, Brandan Bright

Autonomous mobile systems increasingly rely on deep neural networks for perception and decision-making. While effective, these systems are vulnerable to adversarial machine learning attacks where minor input perturbations can significantly impact outcomes. Common countermeasures involve adversarial training and/or data or network transformation. These method

Makoto M. Itoh, Qingrui Hu, Takayuki Niizato, Hiroaki Kawashima

The study of collective animal behavior, especially in aquatic environments, presents unique challenges and opportunities for understanding movement and interaction patterns in the field of ethology, ecology, and bio-navigation. The Fish Tracking Challenge 2024 (https://ftc-2024.github.io/) introduces a multi-object tracking competition focused on the intric

Xiaoyu Zhang, Wenchuan Yang, Jiawei Feng, Bitao Dai

Identifying structures in common forms the basis for networked systems design and optimization. However, real structures represented by graphs are often of varying sizes, leading to the low accuracy of traditional graph classification methods. These graphs are called cross-scale graphs. To overcome this limitation, in this study, we propose GSpect, an advanc

Dandan Jiang, Rui Wang, Jiang Xue

In wireless communication systems, the accurate and reliable evaluation of channel capacity is believed to be a fundamental and critical issue for terminals. However, with the rapid development of wireless technology, large-scale communication networks with significant random interference have emerged, resulting in extremely high computational costs for capa

Yuhan Ji, Song Gao

This research focuses on assessing the ability of AI foundation models in representing the trajectories of movements. We utilize one of the large language models (LLMs) (i.e., GPT-J) to encode the string format of trajectories and then evaluate the effectiveness of the LLM-based representation for trajectory data analysis. The experiments demonstrate that wh

Yibin Du, Ming Yu, Chongwen Jiang, Xianxu Yuan

In the present study, we conduct numerical simulations of compressible flows around spheroid particles, for the purpose of refining empirical formulas for drag force, lift force, and pitching torque acting on them. Through an analysis of approximately a thousand numerical simulation cases spanning a wide range of Mach numbers, Reynolds numbers and particle a

Reshma Kumawat, Shubham Farswan, Simranjeet Kaur, Smriti Bhatia

Raman scattering is an excellent method for simultaneously determining the dynamics of lattice, spin, and charge degrees of freedom. Furthermore, polarization selection rules in Raman scattering enable momentum-resolved quasiparticle dynamics. In this review, we highlight the potential of Raman scattering in probing magnetic quasiparticles or excitations in

Oktie Hassanzadeh

Recently, there has been an increasing interest in the construction of general-domain and domain-specific causal knowledge graphs. Such knowledge graphs enable reasoning for causal analysis and event prediction, and so have a range of applications across different domains. While great progress has been made toward automated construction of causal knowledge g

Jun Li, Jinying Wu, Qiming Li, Feifei Guo

With the continuous development of deep learning, the field of repetitive action counting is gradually gaining notice from many researchers. Extraction of pose keypoints using human pose estimation networks is proven to be an effective pose-level method. However, existing pose-level methods suffer from the shortcomings that the single coordinate is not stabl

Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland

In reinforcement learning (RL), the consideration of multivariate reward signals has led to fundamental advancements in multi-objective decision-making, transfer learning, and representation learning. This work introduces the first oracle-free and computationally-tractable algorithms for provably convergent multivariate distributional dynamic programming and

Jiaxiang Geng, Beilong Tang, Boyan Zhang, Jiaqi Shao

In this demo, we introduce FedCampus, a privacy-preserving mobile application for smart \underline{campus} with \underline{fed}erated learning (FL) and federated analytics (FA). FedCampus enables cross-platform on-device FL/FA for both iOS and Android, supporting continuously models and algorithms deployment (MLOps). Our app integrates privacy-preserving pro

Ergon Cugler de Moraes Silva

Resistance to progressive policies and hate speech have been consolidating on Brazilian Telegram, with anti-woke communities rejecting diversity and promoting a worldview that sees these social changes as a threat. Therefore, this study aims to address the research question: how are Brazilian conspiracy theory communities on anti-woke agenda, gender issues,

Conghao Zhou, Jie Gao, Yixiang Liu, Shisheng Hu

Future 6G networks are envisioned to support mobile augmented reality (MAR) applications and provide customized immersive experiences for users via advanced service provision. In this paper, we investigate user-centric service provision for edge-assisted MAR to support the timely camera frame uploading of an MAR device by optimizing the spectrum resource res

Unggi Lee, Jiyeong Bae, Yeonji Jung, Minji Kang

Knowledge Tracing (KT) is a critical component in online learning, but traditional approaches face limitations in interpretability and cross-domain adaptability. This paper introduces Language Model-based Code Knowledge Tracing (CodeLKT), an innovative application of Language model-based Knowledge Tracing (LKT) to programming education. CodeLKT leverages pre

Girish Kumar, Thomas Strohmer, Roman Vershynin

While differentially private synthetic data generation has been explored extensively in the literature, how to update this data in the future if the underlying private data changes is much less understood. We propose an algorithmic framework for streaming data that generates multiple synthetic datasets over time, tracking changes in the underlying private da

Aashirwad N. Ballal, Vamsi P. Pingali

We study MA-positivity, a notion of positivity relevant to a vector bundle version of the complex Monge--Ampère equation introduced in an earlier work, and show that for rank-two holomorphic bundles over complex surfaces, MA-semi-positive solutions of the vector bundle Monge--Ampère (vbMA) equation are also MA-positive. For vector bundles of rank-three and h

Hang Liu, Hong Guo

It was reported that the optical field fluctuations in self-defocusing media can be described by sound waves propagating in a two-dimensional photon-fluid which is controlled by the driving laser beam. The photon-fluid can be regarded as the background where the sound waves propagate in the way like a scalar field propagating in curved spacetime, thus provid

Manuel de J. Luevano, Alejandro Puga

In this work, several random Boolean networks (RBN) are generated and analyzed from two characteristics: their time evolution diagram and their transition diagram. For this purpose, its randomness is estimated using three measures, of which Algorithmic Complexity is capable of both a) revealing transitions towards the chaotic regime in a more marked way, and

Zi-Wei Sun, Ze-Xi Hua, Heng-Chao Li, Zhi-Peng Qi

A Flying Bird Dataset for Surveillance Videos (FBD-SV-2024) is introduced and tailored for the development and performance evaluation of flying bird detection algorithms in surveillance videos. This dataset comprises 483 video clips, amounting to 28,694 frames in total. Among them, 23,833 frames contain 28,366 instances of flying birds. The proposed dataset

Guang Yang, Muru Zhang, Lin Qiu, Yanming Wan

Optical music recognition (OMR) aims to convert music notation into digital formats. One approach to tackle OMR is through a multi-stage pipeline, where the system first detects visual music notation elements in the image (object detection) and then assembles them into a music notation (notation assembly). Most previous work on notation assembly unrealistica

Xinyi Shen, Zuoquan Lin

Transformer-based open-domain dialog models have become increasingly popular in recent years. These models typically represent context as a concatenation of a dialog history. However, there is no criterion to decide how many utterances should be kept adequate in a context. We try to figure out how the choice of context length affects the model. We experiment

Christopher A. Curwen, Mathieu Fradet, Ryan M. Briggs

We present a modified approach to laser optical-feedback cavity-enhanced absorption spectroscopy. The technique involves continuously scanning the length of a high-finesse cavity to periodically lock a diode laser to the cavity resonance, resulting in a discrete set of transmission measurements that are evenly spaced in frequency. For a fixed laser bias, dat

Dongfen Bian, Emmanuel Grenier, Nader Masmoudi, Weiren Zhao

In this article, we prove that the threshold of instability of the classical Couette flow in $H^s$ for large $s$ is $ν^{1/2}$. The instability is completely driven by the boundary. The dynamic of the flow creates a Prandtl type boundary layer of width $ν^{1/2}$ which is itself linearly unstable. This leads to a secondary instability which in turn creates a s

Yangyang Song, Ning Zhang, Yibo Lei, Yang Guo

Given a number of datasets for evaluating the performance of single reference methods for the low-lying excited states of closed-shell molecules, a comprehensive dataset for assessing the performance of multireference methods for the low-lying excited states of open-shell systems is still desired. For this reason, we propose an extension (QUEST\#4X) of the r

Ana Djurdjevac, Ann Almgren, John Bell

Our focus is on simulating the dynamics of non-interacting particles including the effects of an external potential, which, under certain assumptions, can be formally described by the Dean-Kawasaki equation. The Dean-Kawasaki equation can be solved numerically using standard finite volume methods. However, the numerical approximation implicitly requires a su

Yeachan Park, Sejun Park, Geonho Hwang

Existing works on the expressive power of neural networks typically assume real parameters and exact operations. In this work, we study the expressive power of quantized networks under discrete fixed-point parameters and inexact fixed-point operations with round-off errors. We first provide a necessary condition and a sufficient condition on fixed-point arit

Songyan Zhao, Bingxuan Li, Yufei Tian, Nanyun Peng

Automatic melody-to-lyric (M2L) generation aims to create lyrics that align with a given melody. While most previous approaches generate lyrics from scratch, revision, editing plain text draft to fit it into the melody, offers a much more flexible and practical alternative. This enables broad applications, such as generating lyrics from flexible inputs (keyw

Zuoning Zhang, Dhruv Parikh, Youning Zhang, Viktor Prasanna

Transformer based Large Language Models (LLMs) have recently reached state of the art performance in Natural Language Processing (NLP) and Computer Vision (CV) domains. LLMs use the Multi-Headed Self-Attention (MHSA) mechanism to capture long-range global attention relationships among input words or image patches, drastically improving its performance over p

Yuriko Baba, Vanessa Junk, Wolfgang Hogger, Francisco Domínguez-Adame

Recent experiments, combing ultrafast strong-field irradiation of surfaces with time- and angle-resolved photoemission spectroscopy, allow for monitoring the time-dependent charge carrier dynamics and the build-up of transient sidebands due to the radiation pulses. While these structures are reminiscent of Floquet-Bloch bands, standard Floquet theory is not

Mohamad Rida Rammal, Ruida Zhou, Suhas Diggavi

Data valuation seeks to answer the important question, "How much is this data worth?" Existing data valuation methods have largely focused on discriminative models, primarily examining data value through the lens of its utility in training. However, with the push for ever-larger language models, relying on valuation methods that require training beco

Sebastiaan van den Eijnden, Thomas Chaffey

Systems that show different characteristics, such as finite-gain and passivity, depending on the nature of the inputs, are said to possess mixed input-output properties. In this paper, we provide a constructive method for characterizing mixed input-output properties of nonlinear systems using a dissipativity framework. Our results take inspiration from the g

Yingjie Ma, Jing Guo, Andrew Maloney, Richard Braatz

Glycosylation is a critical quality attribute for monoclonal antibody (mAb) production, influenced by both process conditions and cellular mechanisms. Multiscale mechanistic models, spanning from the bioreactor to the Golgi apparatus, have been proposed for analyzing the glycosylation process. However, these models are computationally intensive to solve when

Nan Xue, Lawrence A. Wilen, Robert W. Style, Eric R. Dufresne

The surface tension of partially wetting droplets deforms soft substrates. These deformations are usually localized to a narrow region near the contact line, forming a so-called `elastocapillary ridge.' When a droplet slides along a substrate, the movement of the elastocapillary ridge dissipates energy in the substrate and slows the droplet down. Previou

Mahesh Kumar Mulimani, Sebastian Echeverria-Alar, Michael Reiss, Wouter-Jan Rappel

Excitable systems can exhibit a variety of dynamics with different complexity, ranging from a single, stable spiral to spiral defect chaos (SDC), during which spiral waves are continuously formed and destroyed. The corresponding reaction-diffusion models, including ones for cardiac tissue, can involve a large number of variables and can be time-consuming to

Haixiang Zhang, Baturalp Yalcin, Javad Lavaei, Eduardo D. Sontag

In this work, we study the problem of learning a nonlinear dynamical system by parameterizing its dynamics using basis functions. We assume that disturbances occur at each time step with an arbitrary probability $p$, which models the sparsity level of the disturbance vectors over time. These disturbances are drawn from an arbitrary, unknown probability distr