October 2022 arXiv papers — page 91

Anyi Rao, Xuekun Jiang, Sichen Wang, Yuwei Guo

The ability to choose an appropriate camera view among multiple cameras plays a vital role in TV shows delivery. But it is hard to figure out the statistical pattern and apply intelligent processing due to the lack of high-quality training data. To solve this issue, we first collect a novel benchmark on this setting with four diverse scenarios including conc

Daniel Seleznev, David Vanderbilt

The theory of bulk orbital magnetization has been formulated both in reciprocal space based on Berry curvature and related quantities, and in real space in terms of the spatial average of a quantum mechanical local marker. Here we consider a three-dimensional antiferromagnetic material having a vanishing bulk but a nonzero surface orbital magnetization. We a

Xiaolong Huang, Qiankun Li

Image representations are a critical building block of computer vision applications. This paper presents the 2nd place solution to the Google Universal Image Embedding Competition, which is part of the ECCV2022 instance-level recognition workshops. We use the instance-level fine-grained image classification method to complete this competition. We focus on da

Raniere Silva, Khizar Hayat, Christopher M Riggs, Michael Doube

Background: Object detection in radiograph computer vision has largely benefited from progress in deep convolutional neural networks and can, for example, annotate a radiograph with a box around a knee joint or intervertebral disc. Is deep learning capable of detect small (less than 1% of the image) in radiographs? And how many radiographs do we need use whe

Xiaoying Xu, Yufan Li, C. L. Chien

Phase-sensitive measurements on a composite ring made of a superconductor of interest connected by a known singlet $s$-wave superconductor can unambiguously determine its pairing symmetry. In composite rings with epitaxial $\beta-$Bi$_2$Pd and $s$-wave Nb, we have observed half-integer quantum flux when Nb is connected to the opposite crystalline ends of $\b

Mancheng Meng, Ziyan Wu, Terrence Chen, Xiran Cai

Predicting the future trajectory of a person remains a challenging problem, due to randomness and subjectivity of human movement. However, the moving patterns of human in a constrained scenario typically conform to a limited number of regularities to a certain extent, because of the scenario restrictions and person-person or person-object interactivity. Thus

Lin Ma, Longrui Chen, Yan Zhang, Mengdi Chu

Pedestrians' safety is a crucial factor in assessing autonomous driving scenarios. However, pedestrian safety evaluation is rarely considered by existing autonomous driving simulation platforms. This paper proposes a pedestrian safety evaluation method for autonomous driving, in which not only the collision events but also the conflict events together with t

Philippe Bisaillon, Brandon Robinson, Mohammad Khalil, Chris L. Pettit

We consider state and parameter estimation for a dynamical system having both time-varying and time-invariant parameters. It has been shown that the robustness of the Markov Chain Monte Carlo (MCMC) algorithm for estimating time-invariant parameters alongside nonlinear filters for state estimation provided more reliable estimates than the estimates obtained

Sankeerth Durvasula, Raymond Kiguru, Samarth Mathur, Jenny Xu

Real-time 3D mapping is a critical component in many important applications today including robotics, AR/VR, and 3D visualization. 3D mapping involves continuously fusing depth maps obtained from depth sensors in phones, robots, and autonomous vehicles into a single 3D representative model of the scene. Many important applications, e.g., global path planning

Hao Xu, Yuxi Hu, Bolong Tan, Xiaohai Shi

The reliability of operating system (OS) has always been a major concern in the academia and industry. This paper studies how to perform OS failure analysis by fault injection based on the fault mode library. Firstly, we use the fault mode generation method based on Linux abstract hierarchy structure analysis to systematically define the Linux-like fault mod

Luyao Wang, Qihe Chen, Yan Zhang, Ziang Li

Quadruped robots have the potential to guide blind and low vision (BLV) people due to their highly flexible locomotion and emotional value provided by their bionic forms. However, the development of quadruped guide robots rarely involves BLV users' participatory designs and evaluations. In this paper, we conducted two empirical experiments both in indoor con

Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen

Language models (LMs) now excel at many tasks such as few-shot learning, question answering, reasoning, and dialog. However, they sometimes generate unsupported or misleading content. A user cannot easily determine whether their outputs are trustworthy or not, because most LMs do not have any built-in mechanism for attribution to external evidence. To enable

Yu Zhang, Shu Chen

We study an imaginary stark ladder model and propose a realization of the model in a dissipative chain with linearly increasing site-dependent dissipation strength. Due to the existence of a $K$-symmetry and passive $\mathcal{PT}$ symmetry, the model exhibits quite different feature from its Hermitian counterpart. With the increase of dissipation strength, t

Xingyu Xing, Tong Jia, Junyi Chen, Lu Xiong

The autonomous vehicle (AV) is a safety-critical system relying on complex sensors and algorithms. The AV may confront risk conditions if these sensors and algorithms misunderstand the environment and situation, even though all components are fault-free. The ISO 21448 defined the safety of the intended functionality (SOTIF), aiming to enhance the AV's safety

Zhihua Tian, Jian Liu, Jingyu Li, Xinle Cao

Data valuation is an essential task in a data marketplace. It aims at fairly compensating data owners for their contribution. There is increasing recognition in the machine learning community that the Shapley value -- a foundational profit-sharing scheme in cooperative game theory -- has major potential to value data, because it uniquely satisfies basic prop

J. A. Detwiler, R. G. H. Robertson

We revisit the role of shake-up and shake-off effects in neutrinoless double-beta decay, following earlier work by Drukarev et al. We find in agreement with Drukarev et al. that the Q value of the decay is reduced by any atomic excitation in the final-state but not by the difference in atomic binding energy of the initial and final state atoms, as was recent

Ismael Lemhadri, Harrison H. Li, Trevor Hastie

We introduce region-based explanations (RbX), a novel, model-agnostic method to generate local explanations of scalar outputs from a black-box prediction model using only query access. RbX is based on a greedy algorithm for building a convex polytope that approximates a region of feature space where model predictions are close to the prediction at some targe

Stephen Drury, Minghua Lin

Sendov's conjecture, which was first introduced in the last 50s, asserts that if all the zeros of a polynomial $p$ lie in the closed unit disk then for each zero there must be a critical point of $p$ within unit distance. This paper confirms the conjecture.

Yafen Cai, Shuai Shi, Yijia Zhou, Jianhao Yu

Stabilizing important physical quantities to atom-based standards lies at the heart of modern atomic, molecular and optical physics, and is widely applied to the field of precision metrology. Of particular importance is the atom-based microwave field amplitude stabilizer, the so-called atomic candle. Previous atomic candles are realized with atoms in their g

Chao Wang, Bin Wu, Zhen Ming Xu, Wen Li Yang

In this paper, we show the relation between the thermodynamic geometry of a four-dimensional Reissner-Nordstrom-AdS (RN-AdS) black hole and non-local observables in boundary field theory. Instead of introducing the critical point associating with the black hole charge to nondimensionalize the thermodynamics parameters, we use the cosmological constant to res

Oliver Broadrick, Poorvi L. Vora, Filip Zagórski

A Risk-Limiting Audit (RLA) is a statistical election tabulation audit with a rigorous error guarantee. We present ballot polling RLA PROVIDENCE, an audit with the efficiency of MINERVA and flexibility of BRAVO. We prove that PROVIDENCE is risk-limiting in the presence of an adversary who can choose subsequent round sizes given knowledge of previous samples.

Chaofeng Guan, Ruihu Li, Liangdong Lu, Yang Liu

One of the main objectives of quantum error-correction theory is to construct quantum codes with optimal parameters and properties. In this paper, we propose a class of 2-generator quasi-cyclic codes and study their applications in the construction of quantum codes over small fields. Firstly, some sufficient conditions for these 2-generator quasi-cyclic code

Chongyu Sun, Yang Xu, Zebin Wu, Zhihui Wei

This paper proposes a Rotation-equivariant Attention Feature Fusion Pyramid Networks for Aerial Object Detection named ReAFFPN. ReAFFPN aims at improving the effect of rotation-equivariant features fusion between adjacent layers which suffers from the semantic and scale discontinuity. Due to the particularity of rotational equivariant convolution, general me

Sunjae Yoon, Ji Woo Hong, Eunseop Yoon, Dahyun Kim

Video moment retrieval (VMR) aims to localize target moments in untrimmed videos pertinent to a given textual query. Existing retrieval systems tend to rely on retrieval bias as a shortcut and thus, fail to sufficiently learn multi-modal interactions between query and video. This retrieval bias stems from learning frequent co-occurrence patterns between quer

Xiaohui Song, Longtao Huang, Hui Xue, Songlin Hu

Capturing emotions within a conversation plays an essential role in modern dialogue systems. However, the weak correlation between emotions and semantics brings many challenges to emotion recognition in conversation (ERC). Even semantically similar utterances, the emotion may vary drastically depending on contexts or speakers. In this paper, we propose a Sup

Zhiyuan Wang, Chenglang Yang

We derive an explicit formula for the connected $(n,m)$-point functions associated to an arbitrary diagonal tau-function $\tau_f(\boldsymbol{t}^+,\boldsymbol{t}^-)$ of the 2d Toda lattice hierarchy using fermionic computations and the boson-fermion correspondence. Then for fixed $\boldsymbol{t}^-$, we compute the KP-affine coordinates of $\tau_f(\boldsymbol{

Dan Berrebbi, Ronan Collobert, Samy Bengio, Navdeep Jaitly

Self-training (ST), or pseudo-labeling has sparked significant interest in the automatic speech recognition (ASR) community recently because of its success in harnessing unlabeled data. Unlike prior semi-supervised learning approaches that relied on iteratively regenerating pseudo-labels (PLs) from a trained model and using them to train a new model, recent

Bowen Wang, Xuefei Yan, Xiangyue Cui, Yongqing Cai

Germanium selenide (GeSe) is a unique two-dimensional (2D) material showing various polymorphs stable at ambient condition. Recently, a new phase with a layered hexagonal lattice ({\gamma}-GeSe) was synthesized with ambient stability and extraordinary electronic conductivity even higher than graphite while its monolayer is semiconducting. In this work, via u

Zexian Yang, Dayan Wu, Wanqian Zhang, Bo Li

Incremental learning for person re-identification (ReID) aims to develop models that can be trained with a continuous data stream, which is a more practical setting for real-world applications. However, the existing incremental ReID methods make two strong assumptions that the cameras are fixed and the new-emerging data is class-disjoint from previous classe

Ye Wang, Xinxin Liu, Wenxin Hu, Tao Zhang

Document-level relation extraction (RE) aims to identify relations between entities across multiple sentences. Most previous methods focused on document-level RE under full supervision. However, in real-world scenario, it is expensive and difficult to completely label all relations in a document because the number of entity pairs in document-level RE grows q

Yongchang Hao, Yuxin Liu, Lili Mou

Reinforcement learning (RL) has been widely used in text generation to alleviate the exposure bias issue or to utilize non-parallel datasets. The reward function plays an important role in making RL training successful. However, previous reward functions are typically task-specific and sparse, restricting the use of RL. In our work, we propose a task-agnosti

Qinglong Xiao, Cuihong Wen, Jiliang Jing, Jieci Wang

We study the dynamics of Gaussian quantum coherence under the background of a Garfinkle-Horowitz-Strominger dilaton black hole. It is shown that the dilaton field has evident effects on the degree of coherence for all the bipartite subsystems. The bipartite Gaussian coherence is not affected by the frequency of the scalar field for an uncharged or an extreme

Changmeng Huan, Pu Wang, Bingtao Liu, Binghan He

Recent discovery of a novel hexagonal phase of GeSe (Gamma-GeSe) has triggered great interests in nanoelectronics applications owing to its electrical conductivity of bulk phase even higher than graphite while its monolayer is a semiconductor. For potential applications, construction of functional two-dimensional (2D) contacts is indispensable. Herein, via f

Yiming Shan, Aiguo Xu, Lifeng Wang, Yudong Zhang

Nonequilibrium kinetic effects are widespread in fluid systems and might have a significant impact on the inertial confinement fusion ignition process, and the entropy production rate is a key factor in accessing the compression process. In this work, we study the Richtmyer-Meshkov instability (RMI) and the reshock process by a two-fluid discrete Boltzmann m

Guowen Li, Zhiyao Yang, Yangyang Fu, Lingyu Ren

As smart buildings move towards open communication technologies, providing access to the Building Automation System (BAS) through the intranet, or even remotely through the Internet, has become a common practice. However, BAS was historically developed as a closed environment and designed with limited cyber-security considerations. Thus, smart buildings are

Yun Liu, Jean-Philippe Banon, Kyle Frohna, Yu-Hsien Chiang

Bandgap tunability of lead mixed-halide perovskites makes them promising candidates for various applications in optoelectronics since they exhibit sharp optical absorption onsets despite the presence of disorder from halide alloying. Here we use localization landscape theory to reveal that the static disorder due to compositional alloying for iodide:bromide

Changmeng Huan, Pu Wang, Binghan He, Yongqing Cai

Layered hexagonal Gamma--GeSe, a new polymorph of GeSe synthesized recently, shows strikingly high electronic conductivity in its bulk form (even higher than graphite) while semiconducting in the case of monolayer (1L). In this work, by using first-principles calculations, we demonstrate that, different from its orthorhombic phases of GeSe, the Gamma--GeSe s

Motoyuki Suzuki, Shintaro Sodeya, Taichi Nakamura

In this study, we develop a dialogue system for a dialogue robot competition. In the system, the characteristics of sightseeing spots are expressed as "attribute vectors" in advance, and the user is questioned on the different attributes of the two candidate spots. Consequently, the system can make recommendations based on user intentions. A dialogue experim

Genival da Silva

Using convex integration, we construct continuous weak solutions to the ideal Hall equation with a given energy profile. This is a first step in the direction of proving the Onsager's conjecture for the more general Hall-MHD equations.

Chaofan Tao, Ngai Wong

Quantizing neural networks to low-bitwidth is important for model deployment on resource-limited edge hardware. Although a quantized network has a smaller model size and memory footprint, it is fragile to adversarial attacks. However, few methods study the robustness and training efficiency of quantized networks. To this end, we propose a new method by recas

Xuefei Yan, Bowen Wang, Yulong Hai, Devesh R. Kripalani

Two-dimensional (2D) van der Waals (vdW) materials have extraordinary thermal properties due to the effect of quantum confinement, making them promising for thermoelectric energy conversion and thermal management in microelectronic devices. In this review, the mechanism of phonon anharmonicity originating from three- and four-phonon interactions is derived.

Kana Morokuma-Matsui, Kenji Bekki, Jing Wang, Paolo Serra

We conduct a $^{12}$C$^{16}$O($J$=1-0) (hereafter CO) mapping survey of 64 galaxies in the Fornax cluster using the ALMA Morita array in cycle 5. CO emission is detected from 23 out of the 64 galaxies. Our sample includes dwarf, spiral and elliptical galaxies with stellar masses of $M_{\rm star}\sim10^{6.3-11.6}$~M$_\odot$. The achieved beam size and sensiti

Christopher Harshaw, Fredrik Sävje, Yitan Wang

We describe a design-based framework for drawing causal inference in general randomized experiments. Causal effects are defined as linear functionals evaluated at unit-level potential outcome functions. Assumptions about the potential outcome functions are encoded as function spaces. This makes the framework expressive, allowing experimenters to formulate an

Weiwen Xu, Yang Deng, Wenqiang Lei, Wenlong Zhao

We study automatic Contract Clause Extraction (CCE) by modeling implicit relations in legal contracts. Existing CCE methods mostly treat contracts as plain text, creating a substantial barrier to understanding contracts of high complexity. In this work, we first comprehensively analyze the complexity issues of contracts and distill out three implicit relatio

Hajime Otsuka, Takashi Shimomura, Koji Tsumura, Yoshiki Uchida

We propose a pseudo-Nambu-Goldstone boson (pNGB) dark matter (DM) model based on an additional non-Abelian gauge symmetry $SU(2)_D$. The gauge symmetry $SU(2)_D$ is spontaneously broken to a global custodial symmetry $U(1)_V$ via the nonvanishing vacuum expectation values of $SU(2)_D$ doublet and triplet scalar fields. Due to the exact global symmetry $U(1)_

Vishal Sharma, Nur Shahidee Bin Saharan, Shao-Hen Chiew, Ezequiel Ignacio Rodríguez Chiacchio

We introduce OpenQAOA, a Python open-source multi-backend Software Development Kit to create, customise, and execute the Quantum Approximate Optimisation Algorithm (QAOA) on Noisy Intermediate-Scale Quantum (NISQ) devices and simulators. OpenQAOA facilitates the creation of QAOA workflows, removing the more tedious and repetitive aspects of implementing vari

Haiwen Wang, Charles C. Wojcik, Shanhui Fan

Topological defects are found in a variety of systems, and their existence are robust under perturbations due to their topological nature. Here we introduce a new type of topological defects found in electromagnetic waves: topological spin defects. Such a defect is associated with a point where the electromagnetic spin density is zero, and generically have a

Xing-Kun Song, Huiqiu Lin

A mixed circulant graph is called integral if all eigenvalues of its Hermitian adjacency matrix are integers. The main purpose of this paper is to investigate the existence of perfect state transfer (PST for short) and multiple state transfer (MST for short) on integral mixed circulant graphs. Concretely, we provide sufficient and necessary conditions for th

Hong Liu, Yucheng Cai, Zhijian Ou, Yi Huang

Building user simulators (USs) for reinforcement learning (RL) of task-oriented dialog systems (DSs) has gained more and more attention, which, however, still faces several fundamental challenges. First, it is unclear whether we can leverage pretrained language models to design, for example, GPT-2 based USs, to catch up and interact with the recently advance

Xiao-Wu Chen, Srikanth B. Iyengar, René Marczinzik

This work presents results on the finiteness, and on the symmetry properties, of various homological dimensions associated to the Jacobson radical and its higher syzygies, of a semiperfect ring.

Yasuhito Sakaki, Shinichiro Michizono, Nobuhiro Terunuma, Toshiya Sanami

We evaluate the neutron and muon fluxes produced in the ILC beam dumps by Monte Carlo simulations and discuss their potential use in irradiation fields. We show that the beam dumps can provide high-intensity neutron and muon fluxes with spectra quite similar to secondary cosmic rays, which are suitable for soft error studies. The beam dumps deliver neutrons

Qiye Guan, Hejin Yan, Yongqing Cai

As emerging atomically ultrathin metal compounds, MXenes show great promise for catalysts and nanoelectronics applications due to the abundant surface terminations and high metallic conductivity. However, the tendency of the interlayer adhesion and suffering from environmental disturbances significantly limit their endurance and efficiency. Herein via conduc

J. L. J. Fuentes-Maguiña, A. H. Tomita

We prove that the existence of $\mathfrak{c}$ incomparable selective ultrafilters implies the existence of a Wallace semigroup whose cube is countably compact. In addition, assuming the existence of $2^{\mathfrak c}$ incomparable selective ultrafilters and $2^{< 2^{\mathfrak{c}}} = 2^{\mathfrak{c}}$, we obtain torsion-free topological groups with respect to

Charles Fefferman, Ary Shaviv

For a set $E\subset\mathbb{R}^n$ that contains the origin we consider $I^m(E)$ -- the set of all $m^{\text{th}}$ degree Taylor approximations (at the origin) of $C^m$ functions on $\mathbb{R}^n$ that vanish on $E$. This set is an ideal in $\mathcal{P}^m(\mathbb{R}^n)$ -- the ring of all $m^{\text{th}}$ degree Taylor approximations of $C^m$ functions on $\mat

Liam O'Connor, Rayhana Amjad

This paper presents Holbert: a work-in-progress pedagogical proof assistant and online textbook platform, aimed at the educational use-case, specifically for the teaching of programming language theory. Holbert allows proof exercises and rule definitions to be embedded directly in an online textbook, where proofs and rules can be manipulated using a graphica

Younghun Hong, Sangdon Jin

The Vlasov-Schr\"odinger-Poisson system is a kinetic-quantum hybrid model describing quasi-lower dimensional electron gases. For this system, we construct a large class of 2D kinetic/1D quantum steady states in a bounded domain as generalized free energy minimizers, and we show their finite subband structure, monotonicity, uniqueness and conditional dynamica

Maruti K. Mudunuru, Velimir V. Vesselinov, Bulbul Ahmmed

This paper presents a novel ML-based methodology for geothermal exploration towards PFA applications. Our methodology is provided through our open-source ML framework, GeoThermalCloud \url{https://github.com/SmartTensors/GeoThermalCloud.jl}. The GeoThermalCloud uses a series of unsupervised, supervised, and physics-informed ML methods available in SmartTenso

Kayue Daniel Wong

In this manuscript, we introduce the notion of fundamental cases to study the unitary dual of $U(p,q)$. As applications, we prove of a conjecture of Salamanca-Riba and Vogan stated in 1998, as well as the fundamental parallelepiped (FPP) conjecture of Vogan in 2023 for $U(p,q)$.

Daniel Alpay, Fabrizio Colombo, Kamal Diki, Irene Sabadini

In a recent paper we used a basic decomposition property of polyanalytic functions of order $2$ in one complex variable to characterize solutions of the classical $\overline{\partial}$-problem for given analytic and polyanalytic data. Our approach suggested the study of a special reproducing kernel Hilbert space that we call the H\"ormander-Fock space that w

Tingyuan Liang, Gengjie Chen, Jieru Zhao, Sharad Sinha

On modern field-programmable gate arrays (FPGAs), certain critical path portions of the designs might be prearranged into many multi-cell macros during synthesis. These movable macros with constraints of shape and resources lead to challenging mixed-size placement for FPGA designs which cannot be addressed by previous analytical placers. Moreover, general ti

Daniel Alpay, Kamal Diki, Mihaela Vajiac

The purpose of this paper is to develop a new theory of three non-commuting quaternionic variables and its related Schur analysis theory for a modified version of the quaternionic global operator.

Thiago Bergamaschi

The ground state energy and the free energy of Quantum Local Hamiltonians are fundamental quantities in quantum many-body physics, however, it is QMA-Hard to estimate them in general. In this paper, we develop new techniques to find classical, additive error product-state approximations for these quantities on certain families of Quantum $k$-Local Hamiltonia

Junhong Xu, Kai Yin, Jason M. Gregory, Lantao Liu

Robot data collected in complex real-world scenarios are often biased due to safety concerns, human preferences, and mission or platform constraints. Consequently, robot learning from such observational data poses great challenges for accurate parameter estimation. We propose a principled causal inference framework for robots to learn the parameters of a sto

Hamid Reza Moradi, Shigeru Furuichi, Mohammad Sababheh

To better understand the algebra $\mathcal{M}_n$ of all $n\times n$ complex matrices, we explore the class of accretive matrices. This class has received renowned attention in recent years due to its role in complementing those results known for positive definite matrices. More precisely, we have several results that allow a better understanding of accretive

Jacqueline R. M. A. Maasch, Hao Zhang, Qian Yang, Fei Wang

The cost of manual data labeling can be a significant obstacle in supervised learning. Data programming (DP) offers a weakly supervised solution for training dataset creation, wherein the outputs of user-defined programmatic labeling functions (LFs) are reconciled through unsupervised learning. However, DP can fail to outperform an unweighted majority vote i

Dave Van Veen, Rogier van der Sluijs, Batu Ozturkler, Arjun Desai

We propose using a coordinate network decoder for the task of super-resolution in MRI. The continuous signal representation of coordinate networks enables this approach to be scale-agnostic, i.e. one can train over a continuous range of scales and subsequently query at arbitrary resolutions. Due to the difficulty of performing super-resolution on inherently

Woo Suk Choi, Yu-Jung Heo, Byoung-Tak Zhang

Scene graph is structured semantic representation that can be modeled as a form of graph from images and texts. Image-based scene graph generation research has been actively conducted until recently, whereas text-based scene graph generation research has not. In this paper, we focus on the problem of scene graph parsing from textual description of a visual s

Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun

As ML models have increased in capabilities and accuracy, so has the complexity of their deployments. Increasingly, ML model consumers are turning to service providers to serve the ML models in the ML-as-a-service (MLaaS) paradigm. As MLaaS proliferates, a critical requirement emerges: how can model consumers verify that the correct predictions were served,

Liming Wang, Guangrui Xia

Low-defect-density Ge thin films are critical in Ge based optical devices (optical detectors, LEDs and Lasers) integrated with Si electronic devices for low-cost, highly integrated photonic circuits. In this work, Ge thin films prepared by wet etching with four different solutions were studied in terms of the surface morphology, defect density and achievable

Junhong Xu, Durgakant Pushp, Kai Yin, Lantao Liu

When robots share the same workspace with other intelligent agents (e.g., other robots or humans), they must be able to reason about the behaviors of their neighboring agents while accomplishing the designated tasks. In practice, frequently, agents do not exhibit absolutely rational behavior due to their limited computational resources. Thus, predicting the

Gregory Eyink, Amir Jafari

We discuss application of methods from the Kraichnan model of turbulent advection to the study of non-equilibrium concentration fluctuations arising during diffusion in liquid mixtures at high Schmidt numbers. This approach treats nonlinear advection of concentration fluctuations exactly, without linearization. Remarkably, we find that static and dynamic str

Omar Mohsen

We introduce the notion of a differential operator on C*-algebras. This is a noncommutative analogue of a differential operator on a smooth manifold. We show that the common closed domain of all differential operators is closed under smooth functional calculus. As a corollary, we show that Schwartz functions on Connes tangent groupoid are closed under smooth

Laurence G. Wilson, Martin A. Bees

Flagella allow eukaryotic cells to move and pump fluid. We present the first three-dimensional, time-resolved imaging of the flagellar waveform of Chlamydomonas reinhardtii, a model alga found in fresh water. During the power stroke, we find that the flagella show rotational symmetry about the cell's centreline, but during the recovery stroke they display mi

Hu Yang, Yi Huang, Haijun Wang, Yu Chen

Analyzing both temporal and spatial patterns for an accurate forecasting model for financial time series forecasting is a challenge due to the complex nature of temporal-spatial dynamics: time series from different locations often have distinct patterns; and for the same time series, patterns may vary as time goes by. Inspired by the successful applications

Hamid Jahanian

Failure Mode Reasoning (FMR) is a method for formal analysis of system-related faults. The method was originally developed for identifying failure modes of safety-critical systems based on an analysis of their programs. In this paper, we generalize the method and present a mathematical framework for its use in model-based system and safety analyses. We expla

Maxence Cassier, Patrick Joly, Luis Alejandro Rosas Martínez

It is well-known that electromagnetic dispersive structures such as metamaterials can be modelled by generalized Drude-Lorentz models. The present paper is the first of two articles dedicated to dissipative generalized Drude-Lorentz open structures. We wish to quantify the loss in such media in terms of the long time decay rate of the electromagnetic energy

Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert

Mixup is a data augmentation technique that creates new examples as convex combinations of training points and labels. This simple technique has empirically shown to improve the accuracy of many state-of-the-art models in different settings and applications, but the reasons behind this empirical success remain poorly understood. In this paper we take a subst

Noe Atzin, Ali Mozaffari, Xingzhou Tang, Soumik Das

Solitons in liquid crystals have generated considerable interest. Several hypotheses of varying complexity have been advanced to explain how they emerge, and a consensus has not emerged yet about the underlying forces responsible for their formation or their structure. In this work, we present a minimal model for soliton structures in achiral nematic liquid

Ruchao Fan, Guoli Ye, Yashesh Gaur, Jinyu Li

Masked language model (MLM) has been widely used for understanding tasks, e.g. BERT. Recently, MLM has also been used for generation tasks. The most popular one in speech is using Mask-CTC for non-autoregressive speech recognition. In this paper, we take one step further, and explore the possibility of using MLM as a non-autoregressive spell correction (SC)

Navid Feizi, S. Farokh Atashzar, Mehrdad R. Kermani, Rajni V. Patel

The increasing need for sharing workspace and interactive physical tasks between robots and humans has raised concerns regarding safety of such operations. In this regard, controllable clutches have shown great potential for addressing important safety concerns at the hardware level by separating the high-impedance actuator from the end effector by providing

Max S. New, Daniel R. Licata

We present a domain-specific type theory for constructions and proofs in category theory. The type theory axiomatizes notions of category, functor, profunctor and a generalized form of natural transformations. The type theory imposes an ordered linear restriction on standard predicate logic, which guarantees that all functions between categories are functori

Chris Nagele, Hideyuki Umeda, Koh Takahashi, Keiichi Maeda

The origin of high-redshift quasars and their supermassive black hole engines is unclear. One promising solution is the collapse of a primordial supermassive star. Observational confirmation of this scenario may be challenging, but a general relativistic instability supernova provides one avenue for such. Previous studies have found that a general relativist

Eduardo Valdes Santurio, Samuel Silverstein, Katherine Dunne, Christian Bohm

The new electronics of the ATLAS Tile Calorimeter for the HL-LHC interfaces the on-detector and off-detector electronics by means of a Daughterboard. The Daughterboard is positioned on-detector featuring commercial SFPs+, CERN GBTx ASICs, ProASIC FPGAs and Kintex Ultrascale FPGAs. The design minimizes single points of failure and mitigates radiation damage b

Takafumi Kita

On the basis of the Luttinger-Ward functional for interacting many-body systems given in terms of full Green's function $G$ and the bare interaction vertex $\Gamma^{(0)}$, we develop a novel Legendre transformation to express the grand thermodynamic potential $\Omega$ as a functional of $G$ and the renormalized interaction vertex $\Gamma$ so that (i) $G$ and

Monika Filipovska, Michael Hyland, Haimanti Bala

Shared-use autonomous mobility services (SAMS) present new opportunities for improving accessible and demand-responsive mobility. A fundamental challenge that SAMS face is appropriate positioning of idle fleet vehicles to meet future demand - a problem that strongly impacts service quality and efficiency. This paper formulates SAMS fleet repositioning as a M

Yuchen Guo, Shardha Jogee, Steven L. Finkelstein, Zilei Chen

Stellar bars are key drivers of secular evolution in galaxies and can be effectively studied using rest-frame near-infrared (NIR) images, which trace the underlying stellar mass and are less impacted by dust and star formation than rest-frame UV or optical images. We leverage the power of {\it{JWST}} CEERS NIRCam images to present the first quantitative iden

Hacène Belbachir, El-Mehdi Mehiri

In the Tower of Hanoi problem, there is six types of moves between the three pegs. The main purpose of the present paper is to find out the number of each of these six elementary moves in the optimal sequence of moves. We present a recursive function based on indicator functions, which counts the number of each elementary move, we investigate some of its pro

Marc Illa, Martin J. Savage

The time-evolution of multi-neutrino entanglement and correlations are studied in two-flavor collective neutrino oscillations, relevant for dense neutrino environments, building upon previous works. Specifically, simulations performed of systems with up to 12 neutrinos using Quantinuum's H1-1 20 qubit trapped-ion quantum computer are used to compute n-tangle

Emily Muller, Xu Zheng, Jer Hayes

Generative models have been found effective for data synthesis due to their ability to capture complex underlying data distributions. The quality of generated data from these models is commonly evaluated by visual inspection for image datasets or downstream analytical tasks for tabular datasets. These evaluation methods neither measure the implicit data dist

Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu

In this paper, we investigate a realistic but underexplored problem, called few-shot temporal knowledge graph reasoning, that aims to predict future facts for newly emerging entities based on extremely limited observations in evolving graphs. It offers practical value in applications that need to derive instant new knowledge about new entities in temporal kn

Jeff Kahn

We show that if ${\mathcal A},{\mathcal B},{\mathcal C}$ are increasing subsets of $\Omega:=\{0,1\}^n$ with ${\mathcal A}\neq\emptyset$, then with respect to any product probability measure on $\Omega$, \[ \mbox{if each of the pairs $\{{\mathcal A}\cap{\mathcal B},{\mathcal C}\}$, $\{{\mathcal A}\cap {\mathcal C},{\mathcal A}\}$ is independent, then ${\mathc

Ho Hin Lee, Yucheng Tang, Han Liu, Yubo Fan

Recent studies have demonstrated the superior performance of introducing ``scan-wise" contrast labels into contrastive learning for multi-organ segmentation on multi-phase computed tomography (CT). However, such scan-wise labels are limited: (1) a coarse classification, which could not capture the fine-grained ``organ-wise" contrast variations across all org

Brahim Abdenbi

We study inert and compressed subgroups of free groups and provide a generalization of echelon subgroups.

Diana Petrescu, Arsany Guirguis, Do Le Quoc, Javier Picorel

Storage disaggregation underlies today's cloud and is naturally complemented by pushing down some computation to storage, thus mitigating the potential network bottleneck between the storage and compute tiers. We show how ML training benefits from storage pushdowns by focusing on transfer learning (TL), the widespread technique that democratizes ML by reusin

Parikshit Gopalan, Lunjia Hu, Michael P. Kim, Omer Reingold

We present a new perspective on loss minimization and the recent notion of Omniprediction through the lens of Outcome Indistingusihability. For a collection of losses and hypothesis class, omniprediction requires that a predictor provide a loss-minimization guarantee simultaneously for every loss in the collection compared to the best (loss-specific) hypothe

Keivan Nalaie, Rong Zheng

Multi-object tracking (MOT) is a vital component of intelligent video analytics applications such as surveillance and autonomous driving. The time and storage complexity required to execute deep learning models for visual object tracking hinder their adoption on embedded devices with limited computing power. In this paper, we aim to accelerate MOT by transfe

Ayman Beghdadi, Malik Mallem, Lotfi Beji

Considering the scene's dynamics is the most effective solution to obtain an accurate perception of unknown environments for real vSLAM applications. Most existing methods attempt to address the non-rigid scene assumption by combining geometric and semantic approaches to determine dynamic elements that lack generalization and scene awareness. We propose a no

Huiling You, David Samuel, Samia Touileb, Lilja Øvrelid

Event extraction involves the detection and extraction of both the event triggers and corresponding event arguments. Existing systems often decompose event extraction into multiple subtasks, without considering their possible interactions. In this paper, we propose EventGraph, a joint framework for event extraction, which encodes events as graphs. We represe

Jungkyu Park, Jakub Chłędowski, Stanisław Jastrzębski, Jan Witowski

3D imaging enables accurate diagnosis by providing spatial information about organ anatomy. However, using 3D images to train AI models is computationally challenging because they consist of 10x or 100x more pixels than their 2D counterparts. To be trained with high-resolution 3D images, convolutional neural networks resort to downsampling them or projecting

Brian Bollen, Pasindu Tennakoon, Joshua A. Levine

Distances on merge trees facilitate visual comparison of collections of scalar fields. Two desirable properties for these distances to exhibit are 1) the ability to discern between scalar fields which other, less complex topological summaries cannot and 2) to still be robust to perturbations in the dataset. The combination of these two properties, known resp