December 2023 arXiv papers — page 67

Zeinab Zakani, Hadi Moradi, Sogand Ghasemzadeh, Maryam Riazi

Objective: Early identification of ADHD is necessary to provide the opportunity for timely treatment. However, screening the symptoms of ADHD on a large scale is not easy. This study aimed to validate a video game (FishFinder) for the screening of ADHD using objective measurement of the core symptoms of this disorder. Method: The FishFinder measures attentio

Yacine Izza, Kuldeep S. Meel, Joao Marques-Silva

Explainable Artificial Intelligence (XAI) is widely regarding as a cornerstone of trustworthy AI. Unfortunately, most work on XAI offers no guarantees of rigor. In high-stakes domains, e.g. uses of AI that impact humans, the lack of rigor of explanations can have disastrous consequences. Formal abductive explanations offer crucial guarantees of rigor and so

Umberto Hryniewicz, Michael Hutchings, Vinicius G. B. Ramos

We consider dynamically convex star-shaped domains in a symplectic vector space of dimension $4$. For such a domain, a ``Hopf orbit'' is a closed characteristic in the boundary which is unknotted and has self-linking number $-1$. We show that the minimum action among Hopf orbits exists and defines a symplectic capacity for dynamically convex star-shaped doma

Haiming Zhang, Xu Yan, Dongfeng Bai, Jiantao Gao

3D occupancy prediction is an emerging task that aims to estimate the occupancy states and semantics of 3D scenes using multi-view images. However, image-based scene perception encounters significant challenges in achieving accurate prediction due to the absence of geometric priors. In this paper, we address this issue by exploring cross-modal knowledge dist

Burak Aksar, Yara Rizk, Tathagata Chakraborti

Chatbots have become one of the main pathways for the delivery of business automation tools. Multi-agent systems offer a framework for designing chatbots at scale, making it easier to support complex conversations that span across multiple domains as well as enabling developers to maintain and expand their capabilities incrementally over time. However, multi

Osamu Hatori, Shiho Oi

We prove that if open subgroups of the groups of invertible elements in two Fourier-Stieltjes algebras are isometric as metric spaces, then the underlying locally compact groups are topologically isomorphic. We describe the structure of isometric real algebra isomorphisms between Fourier-Stieltjes algebras and apply it to prove the above result.

Yufei Cai, Yuxiang Wei, Zhilong Ji, Jinfeng Bai

Customized text-to-image generation, which aims to learn user-specified concepts with a few images, has drawn significant attention recently. However, existing methods usually suffer from overfitting issues and entangle the subject-unrelated information (e.g., background and pose) with the learned concept, limiting the potential to compose concept into new s

Shengkui Zhao, Yukun Ma, Chongjia Ni, Chong Zhang

Our previously proposed MossFormer has achieved promising performance in monaural speech separation. However, it predominantly adopts a self-attention-based MossFormer module, which tends to emphasize longer-range, coarser-scale dependencies, with a deficiency in effectively modelling finer-scale recurrent patterns. In this paper, we introduce a novel hybrid

Anilatmaja Aryasomayajula, Dyuti Roy, Debasish Sadhukhan

Let $\Gamma\subset \mathrm{SU}((2,1),\mathbb{C})$ be a torsion-free cocompact subgroup. Let $\mathbb{B}^{2}$ denote the $2$-dimensional complex ball endowed with the hyperbolic metric $\mu_{\mathrm{hyp}}$, and let $X_{\Gamma}:=\Gamma\backslash \mathbb{B}^{2}$ denote the quotient space, which is a compact complex manifold of dimension $2$. Let $\Lambda:= \Ome

Baris Ata, J. Michael Harrison, Nian Si

Motivated by applications in queueing theory, we consider a class of singular stochastic control problems whose state space is the d-dimensional positive orthant. The original problem is approximated by a drift control problem, to which we apply a recently developed computational method that is feasible for dimensions up to d=30 or more. To show that nearly

Shih-Kuang, Lee, Sun-Ting Tsai, Sharon Glotzer

Detecting and analyzing the local environment is crucial for investigating the dynamical processes of crystal nucleation and shape colloidal particle self-assembly. Recent developments in machine learning provide a promising avenue for better order parameters in complex systems that are challenging to study using traditional approaches. However, the applicat

M. Ukai, Y. Ishikawa, T. Takahashi, K. Tanida

We performed a $\overline{d}$ beam study at the K1.8 beam line of J-PARC Hadron Experimental Facility. 1.8 GeV/$c$ $\overline{d}$ beam yield was measured to be 0.30 $\pm$ 0.04 counts/spill for 30 GeV 70 $\times 10^{12}$ protons/spill irradiated on a 66 mm thick of gold target with the vertical slit opening widths of 2.2 mm, 5 mm and 5 mm for intermediate foc

Shixin Chen, Su Zheng, Chen Bai, Wenqian Zhao

Designing a system-on-chip (SoC) for deep neural network (DNN) acceleration requires balancing multiple metrics such as latency, power, and area. However, most existing methods ignore the interactions among different SoC components and rely on inaccurate and error-prone evaluation tools, leading to inferior SoC design. In this paper, we present SoC-Tuner, a

Youshao Xiao, Zhenglei Zhou, Fagui Mao, Weichang Wu

Recently, ChatGPT or InstructGPT like large language models (LLM) has made a significant impact in the AI world. Many works have attempted to reproduce the complex InstructGPT's training pipeline, namely Reinforcement Learning with Human Feedback (RLHF). However, the mainstream distributed RLHF training methods typically adopt a fixed model placement strateg

Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen

Identifying root causes of anomalies in causal processes is vital across disciplines. Once identified, one can isolate the root causes and implement necessary measures to restore the normal operation. Causal processes are often modelled as graphs with entities being nodes and their paths/interconnections as edge. Existing work only consider the contribution

Santhosh Pogaku

Smart home technology is part of our everyday lives, and this technology is fast-evolving compared to other technologies. The user's feedback is gathered in this paper by conducting expert interviews on how collecting the feedback from the smart home devices will be helpful to improve the devices. We are yet to know about the feedback system of the smart hom

Santhosh Pogaku

Smart Home technology has accomplished extraordinary interest in making individuals' lives more straightforward and more relaxing as of late. Technology as of late brought about delivering numerous savvy and refined frameworks which advanced clever living innovation. In this paper, we will be investigating the behavioural intention of user's approach on prov

Shezheng Song, Shan Zhao, Chengyu Wang, Tianwei Yan

Multimodal Entity Linking (MEL) aims at linking ambiguous mentions with multimodal information to entity in Knowledge Graph (KG) such as Wikipedia, which plays a key role in many applications. However, existing methods suffer from shortcomings, including modality impurity such as noise in raw image and ambiguous textual entity representation, which puts obst

Yugo Kawai, Norio Narita, Akihiko Fukui, Noriharu Watanabe

Dozens of planets are now discovered with large orbital obliquity, and have become the proof for the dynamical evolution of planetary orbits. In the current samples, there is an apparent clustering of planets around $90^\circ$, and also an absence of planets around $180^\circ$ although the latter is expected by some theories. Statistical extrapolation using

Santhosh Pogaku

Different types of warfare have evolved between nations and states in the modern era, each with its technological breakthroughs and use of cutting-edge technologies. With the help of the latest innovations, technologies and ideas emerging and contributing more to the It sector, making it more advanced and resulting in different technologies used for cyber wa

Di Ke, Xie Meng, Xia Hua Rong, Cheng An Yu

In this paper, we present a metamaterial structure of Dirac and vanadium dioxide and investigate its optical properties using the finite-difference time-domain (FDTD) technique. Using the phase transition feature of vanadium dioxide, the design can realize active tuning of the PIT effect at terahertz frequency, thereby converting from a single PIT to a doubl

Fengli Xu, Jun Zhang, Chen Gao, Jie Feng

Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, face significant challenges in the face of rapid urbanization. These challenges, ranging from traffic congestion and pollution to social inequality, call for advanced technological interventions. Recent development

Mahmoud SalahEldin Kasem, Mohamed Mahmoud, Hyun-Soo Kang

Optical character recognition (OCR) is a vital process that involves the extraction of handwritten or printed text from scanned or printed images, converting it into a format that can be understood and processed by machines. This enables further data processing activities such as searching and editing. The automatic extraction of text through OCR plays a cru

K. P. Khemchandani, Luciano M. Abreu, A. Martinez Torres, F. S. Navarra

We present a coupled channel treatment of meson-meson dynamics, for systems with spin-parity $1^+$, and determine the corresponding amplitudes by solving the Bethe-Salpeter equations, which lead to the generation of two axial resonances when mesons are considered as the degrees of freedom in the model. One of them is narrow and has properties in good agreeme

Wen Xu, Berger Lukas, Cai Liming, Parente Alessandro

Thermodiffusive instabilities can have a leading order effect on flame propagation for lean premixed hydrogen flames. Many simulation studies have been performed to study this effect, but almost exclusively in two-dimensional (2D) or domain sizes too small to support the characteristic large-scale features of the instability. The main purpose of this study i

Shota Kikuchi, Tatsuo Kobayashi, Kaito Nasu

We study the large mass hierarchy and CP violation in the modular symmetric quark flavor models without fine-tuning. Mass matrices are written in terms of modular forms. Modular forms near the modular fixed points are approximately given by $\varepsilon^p$, where $\varepsilon$ and $p$ denote the small deviation from the fixed points and their residual charge

Shilei Ji, Chuye Quan, Ruijia Yao, Jianping Yang

Recent findings indicate that orbital angular momentum (OAM) has the capability to induce the intrinsic orbital Hall effect (OHE), which is characterized by orbital Chern number in the orbital Hall insulator. Unlike the spin-polarized channel in Quantum anomalous Hall insulator, the OAM is valley-locked, posing challenges in manipulating the corresponding ed

Toral Gupta, Neil Cornish

The analysis of gravitational wave interferometer data requires estimates for the noise covariance matrix. For stationary noise, this amounts to estimating the power spectrum. Classical methods such as Welch averaging are used in many analyses, but this method require large stretches of ``off-source'' data, where the assumption of stationarity may break down

Yi-Huang Shen, Guangjun Zhu

This paper analyzes the cohomological dimension of the generalized binomial edge ideal $\calJ_{K_m,G}$ for a complete $r$-partite graph $G$. Additionally, the Krull dimension, the depth, the Castelnuovo--Mumford regularity, the Hilbert series, and the multiplicity of its quotient ring are explicitly determined.

Yuxin Hu

This article presents an analysis of China's economic evolution amidst demographic changes from 1990 to 2050, offering valuable insights for academia and policymakers. It uniquely intertwines various economic theories with empirical data, examining the impact of an aging population, urbanization, and family dynamics on labor, demand, and productivity. The st

Gemini Team, Rohan Anil, Sebastian Borgeaud, Jean-Baptiste Alayrac

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks

Tianyi Ko, Takuya Ikeda, Thomas Stewart, Robert Lee

Learning-based grasp detectors typically assume a precision grasp, where each finger only has one contact point, and estimate the grasp probability. In this work, we propose a data generation and learning pipeline that can leverage power grasping, which has more contact points with an enveloping configuration and is robust against both positioning error and

Maria Antoniak, Aakanksha Naik, Carla S. Alvarado, Lucy Lu Wang

Ethical frameworks for the use of natural language processing (NLP) are urgently needed to shape how large language models (LLMs) and similar tools are used for healthcare applications. Healthcare faces existing challenges including the balance of power in clinician-patient relationships, systemic health disparities, historical injustices, and economic const

Sanjay Oruganti, Ramviyas Parasuraman, Ramana Pidaparti

Multi-agent and multi-robot systems (MRS) often rely on direct communication for information sharing. This work explores an alternative approach inspired by eavesdropping mechanisms in nature that involves casual observation of agent interactions to enhance decentralized knowledge dissemination. We achieve this through a novel IKT-BT framework tailored for a

Rico Angell, Andrew McCallum

While semidefinite programming (SDP) has traditionally been limited to moderate-sized problems, recent algorithms augmented with matrix sketching techniques have enabled solving larger SDPs. However, these methods achieve scalability at the cost of an increase in the number of necessary iterations, resulting in slower convergence as the problem size grows. F

Yixuan Even Xu, Hanrui Zhang, Vincent Conitzer

Bilateral trade is one of the most natural and important forms of economic interaction: A seller has a single, indivisible item for sale, and a buyer is potentially interested. The two parties typically have different, privately known valuations for the item, and ideally, they would like to trade if the buyer values the item more than the seller. The celebra

Zahra Moslemi, Yang Meng, Shiwei Lan, Babak Shahbaba

Bayesian Neural Networks (BNNs) offer a principled and natural framework for proper uncertainty quantification in the context of deep learning. They address the typical challenges associated with conventional deep learning methods, such as data insatiability, ad-hoc nature, and susceptibility to overfitting. However, their implementation typically either rel

Haruka Noguchi, Satoshi Yukawa

We analyze a two-dimensional spring network model comprising breakable and unbreakable springs. Computer simulations showed this system to exhibit intermittent stress drops in a larger strain regime, and these stress drops resulted in ductile-like behavior. The scaling analysis reveals that the avalanche size distribution demonstrates a cut-off, depending on

Min Dai, Yuchao Dong, Yanwei Jia, Xun Yu Zhou

We study Merton's expected utility maximization problem in an incomplete market, characterized by a factor process in addition to the stock price process, where all the model primitives are unknown. The agent under consideration is a price taker who has access only to the stock and factor value processes and the instantaneous volatility. We propose an auxili

Shujie Cui, Haohua Li, Yuanhong Li, Zhi Zhang

Trusted Execution Environments (TEEs) allow user processes to create enclaves that protect security-sensitive computation against access from the OS kernel and the hypervisor. Recent work has shown that TEEs are vulnerable to side-channel attacks that allow an adversary to learn secrets shielded in enclaves. The majority of such attacks trigger exceptions or

Lang Yu, Qin Chen, Jie Zhou, Liang He

Large language models (LLMs) have shown great success in various Natural Language Processing (NLP) tasks, whist they still need updates after deployment to fix errors or keep pace with the changing knowledge in the world. Researchers formulate such problem as Model Editing and have developed various editors focusing on different axes of editing properties. H

Yueh-Ting Yao, Xiaoting Zhou, Yi-Chun Hung, Hsin Lin

Gapless topological boundary states characterize nontrivial topological phases arising from the bulk-boundary correspondence in symmetry-protected topological materials, such as the emergence of helical edge states in a two-dimensional $\mathbb{Z}_2$ topological insulator. However, the incorporation of symmetry-breaking perturbation terms in the Hamiltonian

Li Jiang, Zhaowei Lu

Image forensics has become increasingly crucial in our daily lives. Among various types of forgeries, copy-move forgery detection has received considerable attention within the academic community. Keypoint-based algorithms, particularly those based on Scale Invariant Feature Transform, have achieved promising outcomes. However, most of keypoint detection alg

Yi Cheng, Wenge Liu, Jian Wang, Chak Tou Leong

In recent years, there has been a growing interest in exploring dialogues with more complex goals, such as negotiation, persuasion, and emotional support, which go beyond traditional service-focused dialogue systems. Apart from the requirement for much more sophisticated strategic reasoning and communication skills, a significant challenge of these tasks lie

Zijian An, Lifeng Zhou

We study the problem of game-theoretic robot allocation where two players strategically allocate robots to compete for multiple sites of interest. Robots possess offensive or defensive capabilities to interfere and weaken their opponents to take over a competing site. This problem belongs to the conventional Colonel Blotto Game. Considering the robots' heter

Vaishnavi Mhaske, Khushi Jain, Sai Karthik Thatikonda, Asif Kunwar

Google's BBR (Bottleneck Bandwidth and Round-trip Propagation Time) approach is used to enhance internet network transmission. It is particularly intended to efficiently handle enormous amounts of data. Traditional TCP (Transmission Control Protocol) algorithms confront the most difficulty in calculating the proper quantity of data to send in order to preven

Conghao Zhou, Hao-Yi Wu, Andrés N. Salcedo, Sebastian Grandis

Galaxy clusters identified with optical imaging tend to suffer from projection effects, which impact richness (the number of member galaxies in a cluster) and lensing coherently. Physically unassociated galaxies can be mistaken as cluster members due to the significant uncertainties in their line-of-sight distances, thereby changing the observed cluster rich

Aadirupa Saha, Vitaly Feldman, Tomer Koren, Yishay Mansour

We address the problem of convex optimization with preference feedback, where the goal is to minimize a convex function given a weaker form of comparison queries. Each query consists of two points and the dueling feedback returns a (noisy) single-bit binary comparison of the function values of the two queried points. Here we consider the sign-function-based

Lu Chen, Guozhen Lu, Hanli Tang

We establish the optimal asymptotic lower bound for the stability of fractional Sobolev inequality: \begin{equation}\label{Sob sta ine} \left\|(-\Delta)^{s/2} U \right\|_2^2 - \mathcal S_{s,n} \| U\|_{\frac{2n}{n-2s}}^2\geq C_{n,s} d^{2}(U, \mathcal{M}_s), \end{equation} where $\mathcal{M}_s$ is the set of maximizers of the fractional Sobolev inequality of o

Mitsuyasu Hashimoto, Anurag K. Singh

Let $V$ be a finite rank vector space over a perfect field of characteristic $p>0$, and let $G$ be a finite subgroup of $\operatorname{GL}(V)$. If $V$ is a permutation representation of $G$, or more generally a monomial representation, we prove that the ring of invariants $(\operatorname{Sym}V)^G$ has finite Frobenius representation type. We also construct a

Zhangdie Yuan, Andreas Vlachos

Despite progress in automated fact-checking, most systems require a significant amount of labeled training data, which is expensive. In this paper, we propose a novel zero-shot method, which instead of operating directly on the claim and evidence sentences, decomposes them into semantic triples augmented using external knowledge graphs, and uses large langua

Stefan Johann Hofmeister

A point-spread function describes the optics of an imaging system and can be used to correct collected images for instrumental effects. The state of the art for deconvolving images with the point-spread function is the Richardson-Lucy algorithm; however, despite its high fidelity, it is slow and cannot account for light scattered out of the field of view of

Wilkie Olin-Ammentorp

The increasing difficulty in continued development of digital electronic logic has led to a renewed interest in alternative approaches. Oscillatory computing is one such approach that leverages alternative physical systems and computation strategies, but it lacks high-level paradigms for system design and programming. We address this gap by describing a mode

Zihui Xue, Kumar Ashutosh, Kristen Grauman

Object State Changes (OSCs) are pivotal for video understanding. While humans can effortlessly generalize OSC understanding from familiar to unknown objects, current approaches are confined to a closed vocabulary. Addressing this gap, we introduce a novel open-world formulation for the video OSC problem. The goal is to temporally localize the three stages of

Takahiro Tsumura, Seiji Yamada

Cooperative relationships between humans and agents are becoming more important for the social coexistence of anthropomorphic agents, including virtual agents and robots. One way to improve the relationship between humans and agents is for humans to empathize with the agents. Empathy can help humans become more accepting of agents. In this study, we focus on

Mark J. Ablowitz, Ziad H. Musslimani, Nicholas J. Ossi

Nonlocal integrable partial differential equations possessing a spatial or temporal reflection have constituted an active research area for the past decade. Recently, more general classes of these nonlocal equations have been proposed, wherein the nonlocality appears as a combination of a shift (by a real or a complex parameter) and a reflection. This new sh

Anaelia Ovalle, Ninareh Mehrabi, Palash Goyal, Jwala Dhamala

Gender-inclusive NLP research has documented the harmful limitations of gender binary-centric large language models (LLM), such as the inability to correctly use gender-diverse English neopronouns (e.g., xe, zir, fae). While data scarcity is a known culprit, the precise mechanisms through which scarcity affects this behavior remain underexplored. We discover

Prajwal Mohanmurthy, Joseph Formaggio, Daniel J. Salvat, Jeff A. Winger

Neutron lifetime is a critical parameter in the Standard Model. Its measurements using, particularly, the beamline and ultracold neutron storage techniques reveals serious tension. The status of the tension between various measurements have been presented, in light of the insights provided by the $\beta$-decay correlation measurements. When ultracold neutron

Eugene A. Koval

The field-free alignment and orientation of the linear molecule by the two-color trapezoidal laser pulses were theoretically investigated. The trapezoidal shape of a laser pulse allows to enhance the maximum alignment degree for the same intensity and duration comparing to the conventional Gaussian laser pulse. The alignment and orientation persist after the

Tomohiro Inagaki, Masahiko Taniguchi

We investigate the quintessential inflation in the logarithmic Cartan $F(R)$ gravity. A small logarithmic modification of the general relativity has the potential to introduce both inflation and dark energy. We evaluate the time evolution of the Universe such as inflation, reheating, and dark energy. The parameters in the model are fixed to introduce the inf

Mohannad Barakat, Noha Magdy, Jjuuko George William, Ethel Phiri

Gliomas, the most prevalent primary brain tumors, require precise segmentation for diagnosis and treatment planning. However, this task poses significant challenges, particularly in the African population, were limited access to high-quality imaging data hampers algorithm performance. In this study, we propose an innovative approach combining the Segment Any

Yuze He, Yushi Bai, Matthieu Lin, Jenny Sheng

By lifting the pre-trained 2D diffusion models into Neural Radiance Fields (NeRFs), text-to-3D generation methods have made great progress. Many state-of-the-art approaches usually apply score distillation sampling (SDS) to optimize the NeRF representations, which supervises the NeRF optimization with pre-trained text-conditioned 2D diffusion models such as

Jacob Bradd

For a real reductive group $G$, we investigate the structure of the Casselman algebra $\mathcal{S}(G)$ and its similarities to the structure of the reduced group $C^*$-algebra $C_r^*(G)$. We demonstrate that the two algebras are assembled from very similar elementary components in a compatible way. In particular, we prove that the two algebras have the same

Emily Kaczmarek, Olivier X. Miguel, Alexa C. Bowie, Robin Ducharme

Deep neural networks have been widely adopted in numerous domains due to their high performance and accessibility to developers and application-specific end-users. Fundamental to image-based applications is the development of Convolutional Neural Networks (CNNs), which possess the ability to automatically extract features from data. However, comprehending th

Tong Fu, Ruo-Yang Zhang, Shiqi Jia, C. T. Chan

The Chern number has been widely used to describe the topological properties of periodic structures in the momentum space. Here, we introduce a real-space spin Chern number for the optical near fields of finite-sized structures. This new spin Chern number is intrinsically quantized and equal to the structure's Euler characteristic. The relationship is robust

Alyssa R. Amod, Alexandra Smith, Pearly Joubert, Confidence Raymond

A critical challenge for tumour segmentation models is the ability to adapt to diverse clinical settings, particularly when applied to poor-quality neuroimaging data. The uncertainty surrounding this adaptation stems from the lack of representative datasets, leaving top-performing models without exposure to common artifacts found in MRI data throughout Sub-S

Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas

We study the clustering problem for mixtures of bounded covariance distributions, under a fine-grained separation assumption. Specifically, given samples from a $k$-component mixture distribution $D = \sum_{i =1}^k w_i P_i$, where each $w_i \ge \alpha$ for some known parameter $\alpha$, and each $P_i$ has unknown covariance $\Sigma_i \preceq \sigma^2_i \cdot

Rupali Bhati, Sai Krishna Gottipati, Clodéric Mars, Matthew E. Taylor

While there has been significant progress in curriculum learning and continuous learning for training agents to generalize across a wide variety of environments in the context of single-agent reinforcement learning, it is unclear if these algorithms would still be valid in a multi-agent setting. In a competitive setting, a learning agent can be trained by ma

Jessica K. Wallingford, William A. Masters

The least-cost diet problem introduces students to optimization and linear programming, using the health consequences of food choice. We provide a graphical example, Excel workbook and Word template using actual data on item prices, food composition and nutrient requirements for a brief exercise in which students guess at and then solve for nutrient adequacy

Peter J. McNamara, Alistair Savage

We introduce a diagrammatic monoidal category, the spin Brauer category, that plays the same role for the spin and pin groups as the Brauer category does for the orthogonal groups. In particular, there is a full functor from the spin Brauer category to the category of finite-dimensional modules for the spin and pin groups. This functor becomes essentially su

James Edmond, Joachim Raeder, Banafsheh Ferdousi, Matthew Argall

The use of supervised methods in space science have demonstrated powerful capability in classification tasks, but unsupervised methods have been less utilized for the clustering of spacecraft observations. We use a combination of unsupervised methods, being principal component analysis, self-organizing maps, and hierarchical agglomerative clustering, to make

Varadharajan Muruganandam, Manas Sajjan, Sabre Kais

We discuss one-dimensional(1D) spin compass model or 1D Kitaev model in the presence of local bond defects. Three types of local disorders concerning both bond-nature and bond-strength that occur on kitaev materials have been investigated. Using exact diagonalization, two-point spin-spin structural correlations and four-point Out-of-Time-Order Correlators(OT

Gabriel Aguayo, Arnold J. T. M. Mathijssen, Hugo N. Ulloa, Rodrigo Soto

Communities of swimming microorganisms often thrive near liquid-air interfaces. We study how such `active carpets' shape their aquatic environment by driving biogenic transport in the water column beneath them. The hydrodynamic stirring that active carpets generate leads to diffusive upward fluxes of nutrients from deeper water layers, and downward fluxes of

Hanwen Ye, Tatiana Moreno, Adrianne Alpern, Louis Ehwerhemuepha

Mental health diseases affect children's lives and well-beings which have received increased attention since the COVID-19 pandemic. Analyzing psychiatric clinical notes with topic models is critical to evaluating children's mental status over time. However, few topic models are built for longitudinal settings, and most existing approaches fail to capture tem

Manabu Mukai, Hidekata Hontani, Tatsuya Yokota

In this paper, we propose a new unified optimization algorithm for general tensor decomposition which is formulated as an inverse problem for low-rank tensors in the general linear observation models. The proposed algorithm supports three basic loss functions ($\ell_2$-loss, $\ell_1$-loss and KL divergence) and various low-rank tensor decomposition models (C

Robert E. Butler, Samir Salim

The Milky Way extinction curve in the near-infrared (NIR) follows a power law form, but the value of the slope, $\beta_\text{NIR}$, is debated. Systematic variations in the slope of the Milky Way UV extinction curve are known to be correlated with variations in the optical slope (through $R_V$), but whether such a dependence extends to the NIR is unclear. Fi

Jay Mahajan, Samuel Hum, Jack Henhapl, Diya Yunus

MineObserver 2.0 is an AI framework that uses Computer Vision and Natural Language Processing for assessing the accuracy of learner-generated descriptions of Minecraft images that include some scientifically relevant content. The system automatically assesses the accuracy of participant observations, written in natural language, made during science learning

Amon Furuichi, Sung Hak Lim, Mihoko M. Nojiri

Recent advancements in deep learning models have significantly enhanced jet classification performance by analyzing low-level features (LLFs). However, this approach often leads to less interpretable models, emphasizing the need to understand the decision-making process and to identify the high-level features (HLFs) crucial for explaining jet classification.

Jacques L. Pienaar

Recent no-go theorems on interpretations of quantum theory featuring an assumption of `Absoluteness of Observed Events' (AOE) are shown to have an unexpectedly strong corollary: one cannot reject AOE and at the same time assume that the `observed events' in question can all be embedded within a single background space-time common to all observers. Consequent

Cesar A. Bernardes

A hot and dense matter exhibiting collective flow behavior with almost no viscous dissipation has been discovered in ultrarelativistic nuclear collisions. To constrain the fundamental degrees of freedom and equation of state of this matter, these proceedings present an extraction of its speed of sound using head-on lead-lead collision data collected by the C

Sergei Alexandrov, Soheyla Feyzbakhsh, Albrecht Klemm, Boris Pioline

In previous work, we used new mathematical relations between Gopakumar-Vafa (GV) invariants and rank 0 Donaldson-Thomas (DT) invariants to determine the first few terms in the generating series of Abelian D4-D2-D0 indices for a class of compact one-parameter Calabi-Yau threefolds. This allowed us to obtain striking checks of S-duality, namely the prediction

Renan Assimos, Balázs Márk Békési, Giuseppe Gentile

Inspired by the halfspace theorem for minimal surfaces in $\mathbb{R}^3$ of Hoffman-Meeks, the halfspace theorem of Rodriguez-Rosenberg, and the cone theorem of Omori, we derive new non-existence results for proper harmonic maps into perturbed cones in $\mathbb{R}^n$, horospheres in $\mathbb{H}^n$ and also into perturbed Riemannian cones. The technical tool

Masoud Dorvash, Ali Eslamian, Mohammad Reza Ahmadzadeh

This paper introduces an innovative approach to Simultaneous Localization and Mapping (SLAM) using the Unscented Kalman Filter (UKF) in a dynamic environment. The UKF is proven to be a robust estimator and demonstrates lower sensitivity to sensor data errors compared to alternative SLAM algorithms. However, conventional algorithms are primarily concerned wit

Fabrice Orgogozo, Joël Riou

Relying on the formalism developed by Alexander Beilinson and Takeshi Saito, we compute the characteristic cycle of an external symmetric power of a tame étale sheaf on a curve. This generalizes a result of Gérard Laumon in characteristic 0 and leads to a result of local acyclicity of the Abel-Jacobi morphism, due to Pierre Deligne and motivated by his geome

Xueqian Sun, Manuka Suriyage, Ahmed Khan, Mingyuan Gao

Twisted vdW quantum materials have emerged as a rapidly developing field of 2D semiconductors. These materials establish a new central research area and provide a promising platform for studying quantum phenomena and investigating the engineering of novel optoelectronic properties such as single-photon emission, non-linear optical response, magnon physics, a

Jan Rozman, Chaithanya K. V. S., Julia M. Yeomans, Rastko Sknepnek

Complex tissue flows in epithelia are driven by intra- and inter-cellular processes that generate, maintain, and coordinate mechanical forces. There has been growing evidence that cell shape anisotropy, manifested as nematic order, plays an important role in this process. Here we extend an active nematic vertex model by replacing substrate friction with inte

Janak Tiwari, Tianli Feng

Many complex crystals show a flattening or even increasing lattice thermal conductivity at high temperatures, which deviates from the traditional 1/T decay trend given by conventional phonon theory. In this work, we predict the thermal conductivity of Al2O3 that matches with experimental data from room temperature to near melting point (2200 K). The lattice

Gabriel Agostini, Emma Pierson, Nikhil Garg

Decision-makers often observe the occurrence of events through a reporting process. City governments, for example, rely on resident reports to find and then resolve urban infrastructural problems such as fallen street trees, flooded basements, or rat infestations. Without additional assumptions, there is no way to distinguish events that occur but are not re

Juho Kim

This paper introduces the Poker Hand History (PHH) file format, designed to standardize the recording of poker hands across different game variants. Despite poker's widespread popularity in the mainstream culture as a mind sport and its prominence in the field of artificial intelligence (AI) research as a benchmark for imperfect information AI agents, it lac

Inioluwa Deborah Raji, Roel Dobbe

As AI systems proliferate in society, the AI community is increasingly preoccupied with the concept of AI Safety, namely the prevention of failures due to accidents that arise from an unanticipated departure of a system's behavior from designer intent in AI deployment. We demonstrate through an analysis of real world cases of such incidents that although cur

Michael Psenka, Alejandro Escontrela, Pieter Abbeel, Yi Ma

Diffusion models have become a popular choice for representing actor policies in behavior cloning and offline reinforcement learning. This is due to their natural ability to optimize an expressive class of distributions over a continuous space. However, previous works fail to exploit the score-based structure of diffusion models, and instead utilize a simple

Fabian R. Pieroth, Nils Kohring, Martin Bichler

We compute equilibrium strategies in multi-stage games with continuous signal and action spaces as they are widely used in the management sciences and economics. Examples include sequential sales via auctions, multi-stage elimination contests, and Stackelberg competitions. In sequential auctions, analysts performing equilibrium analysis are required to deriv

Harsh Sharma, Pratyush Dhingra, Janardhan Rao Doppa, Umit Ogras

Transformers have revolutionized deep learning and generative modeling, enabling advancements in natural language processing tasks. However, the size of transformer models is increasing continuously, driven by enhanced capabilities across various deep learning tasks. This trend of ever-increasing model size has given rise to new challenges in terms of memory

Cheng-Wei Lee, Andriy Zakutayev, Vladan Stevanović

Novel wide-band-gap semiconductors are needed for next-generation power electronic but there is a gap between a promising material and a functional device. Finding stable contacts is one of the major challenges, which is currently dealt with mainly via trial and error. Herein, we computationally investigate the thermochemistry and phase co-existence at the j

Shreeram Athreya, Ashwath Radhachandran, Vedrana Ivezić, Vivek Sant

Purpose: The objective of this work is to introduce an advanced framework designed to enhance ultrasound images, especially those captured by portable hand-held devices, which often produce lower quality images due to hardware constraints. Additionally, this framework is uniquely capable of effectively handling non-registered input ultrasound image pairs, ad

Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo

Counterfactual Explanation (CE) techniques have garnered attention as a means to provide insights to the users engaging with AI systems. While extensively researched in domains such as medical imaging and autonomous vehicles, Graph Counterfactual Explanation (GCE) methods have been comparatively under-explored. GCEs generate a new graph similar to the origin

Tong Shen, Hatem Barghathi, Adrian Del Maestro, Brenda Rubenstein

The complicated ways in which electrons interact in many-body systems such as molecules and materials have long been viewed through the lens of local electron correlation and associated correlation functions. However, quantum information science has demonstrated that more global diagnostics of quantum states, like the entanglement entropy, can provide a comp

Babooshka Shavazipour, Theodor J. Stewart

Many real-world decision-making problems involve multiple decision-making stages and various objectives. Besides, most of the decisions need to be made before having complete knowledge about all aspects of the problem leaves some sort of uncertainty. Deep uncertainty happens when the degree of uncertainty is so high that the probability distributions are not

Samantha L. Dahlberg, Hemanshu Kaul, Jeffrey A. Mudrock

The notion of $S$-labeling of graphs, where $S$ is a subset of a symmetric group, was introduced in 2019 by Jin, Wong, and Zhu. This notion provides the framework for a common generalization of various well studied notions of graph coloring, including classical coloring, signed $k$-coloring, signed $\mathbb{Z}_k$-coloring, DP (or correspondence) coloring, gr

Gurdip Uppal, Dervis Can Vural

Many species of microbes cooperate by producing public goods from which they collectively benefit. However, these populations are under the risk of being taken over by cheating mutants that do not contribute to the pool of public goods. Here we present theoretical findings that address how the social evolution of microbes can be manipulated by external pertu