April 2023 arXiv papers — page 118

Maria Charisi, Stephen R. Taylor, Caitlin A. Witt, Jessie Runnoe

Supermassive black hole binaries are promising sources of low-frequency gravitational waves (GWs) and bright electromagnetic emission. Pulsar timing array searches for resolved binaries are complex and computationally expensive and so far limited to only a few sources. We present an efficient approximation that empowers large-scale targeted multi-messenger s

Ziteng Gao, Zhan Tong, Limin Wang, Mike Zheng Shou

Human visual recognition is a sparse process, where only a few salient visual cues are attended to rather than traversing every detail uniformly. However, most current vision networks follow a dense paradigm, processing every single visual unit (e.g,, pixel or patch) in a uniform manner. In this paper, we challenge this dense paradigm and present a new metho

Mingyu Ding, Yan Xu, Zhenfang Chen, David Daniel Cox

Humans, even at a very early age, can learn visual concepts and understand geometry and layout through active interaction with the environment, and generalize their compositions to complete tasks described by natural languages in novel scenes. To mimic such capability, we propose Embodied Concept Learner (ECL) in an interactive 3D environment. Specifically,

Marcelin Tworski, Stéphane Lathuilière

In this paper, we address the well-known image quality assessment problem but in contrast from existing approaches that predict image quality independently for every images, we propose to jointly model different images depicting the same content to improve the precision of quality estimation. This proposal is motivated by the idea that multiple distorted ima

Seth Brown, Saumya Sinha, Andrew J Schaefer

We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates design and operational phases, which are represented by a mixed-integer program and discounted-cost infinite-horizon Markov decision processes, respectively. We seek to simultaneously minimize the design costs and the su

Andreia Mordido, Janek Spaderna, Peter Thiemann, Vasco T. Vasconcelos

We propose algebraic protocols that enable the definition of protocol templates and session types analogous to the definition of domain-specific types with algebraic datatypes. Parameterized algebraic protocols subsume all regular as well as most context-free and nested session types and, at the same time, replace the expensive superlinear algorithms for typ

Fangyin Wei, Thomas Funkhouser, Szymon Rusinkiewicz

Removing clutter from scenes is essential in many applications, ranging from privacy-concerned content filtering to data augmentation. In this work, we present an automatic system that removes clutter from 3D scenes and inpaints with coherent geometry and texture. We propose techniques for its two key components: 3D segmentation from shared properties and 3D

Arkaitz Rodas, Jozef J. Dudek, Robert G. Edwards

Lattice QCD spectra can be used to constrain partial-wave scattering amplitudes that, while satisfying unitarity, do not have to respect crossing symmetry and analyticity. This becomes a particular problem when extrapolated far from real energies, e.g. in the case of broad resonances like the $\sigma$, leading to large systematic uncertainties in the pole po

Justin Murray

Given a Legendrian knot in $(\mathbb{R}^3, \ker(dz-ydx))$ one can assign a combinatorial invariants called ruling polynomials. These invariants have been shown to recover not only a (normalized) count of augmentations but are also closely related to a categorical count of augmentations in the form of the homotopy cardinality of the augmentation category. In

Kaiwen Xu, Aravind R. Krishnan, Thomas Z. Li, Yuankai Huo

Anatomically consistent field-of-view (FOV) completion to recover truncated body sections has important applications in quantitative analyses of computed tomography (CT) with limited FOV. Existing solution based on conditional generative models relies on the fidelity of synthetic truncation patterns at training phase, which poses limitations for the generali

Darshana Wickramaratne, Igor I. Mazin

The recent discovery of Ising superconductivity has garnered a lot of interest due in part to the resilience of these superconductors to large in-plane magnetic fields. In this Perspective we explain the basic concepts that define the behavior of Ising superconductors, provide an overview of the electronic structure and magnetic properties with a focus on Nb

Shivani Yadav, Dipanjan Gope, Uma Maheswari K., Prasanta Kumar Ghosh

Breathing is an essential part of human survival, which carries information about a person's physiological and psychological state. Generally, breath boundaries are marked by experts before using for any task. An unsupervised algorithm for breath boundary detection has been proposed for breath sounds recorded at the mouth also referred as vocal breath sounds

Zachary Chase, Shay Moran, Amir Yehudayoff

Replicability is essential in science as it allows us to validate and verify research findings. Impagliazzo, Lei, Pitassi and Sorrell (`22) recently initiated the study of replicability in machine learning. A learning algorithm is replicable if it typically produces the same output when applied on two i.i.d. inputs using the same internal randomness. We stud

Kin Man Lee, Arjun Krishna, Zulfiqar Zaidi, Rohan Paleja

As high-speed, agile robots become more commonplace, these robots will have the potential to better aid and collaborate with humans. However, due to the increased agility and functionality of these robots, close collaboration with humans can create safety concerns that alter team dynamics and degrade task performance. In this work, we aim to enable the deplo

Hung-Ting Su, Yulei Niu, Xudong Lin, Winston H. Hsu

Causal Video Question Answering (CVidQA) queries not only association or temporal relations but also causal relations in a video. Existing question synthesis methods pre-trained question generation (QG) systems on reading comprehension datasets with text descriptions as inputs. However, QG models only learn to ask association questions (e.g., ``what is someo

Stefan K. Muller, Kyle Singer, Devyn Terra Keeney, Andrew Neth

Many concurrent programs assign priorities to threads to improve responsiveness. When used in conjunction with synchronization mechanisms such as mutexes and condition variables, however, priorities can lead to priority inversions, in which high-priority threads are delayed by low-priority ones. Priority inversions in the use of mutexes are easily handled us

Jiaqi Wang, Pan Zhang, Tao Chu, Yuhang Cao

Recent advances in detecting arbitrary objects in the real world are trained and evaluated on object detection datasets with a relatively restricted vocabulary. To facilitate the development of more general visual object detection, we propose V3Det, a vast vocabulary visual detection dataset with precisely annotated bounding boxes on massive images. V3Det ha

P G Romeo, Minnumol P K

In this paper we describe the categories $\mathbb{L}_R$ , [$\mathbb{R}_R$] whose objects are left [right] ideals of a Noetherian ring $R$ with unity and morphisms are appropriate $R$-linear transformations. Further it is shown that these are preadditive categories with zero object and are full subcategories of the $R$-modulue category with the property that

J. Colin Hill, Boris Bolliet

A key assumption of the standard cosmological model is that the temperature of the cosmic microwave background (CMB) radiation scales with cosmological redshift $z$ as $T_{\rm CMB}(z) \propto (1+z)$ at all times after recombination at $z_\star \simeq 1090$. However, this assumption has only been precisely tested at $z \lesssim 3$. Here, we consider cosmologi

Nikhil Ravi, Anna Scaglione, Julieta Giraldez, Parth Pradhan

Stakeholders in electricity delivery infrastructure are amassing data about their system demand, use, and operations. Still, they are reluctant to share them, as even sharing aggregated or anonymized electric grid data risks the disclosure of sensitive information. This paper highlights how applying differential privacy to distributed energy resource product

Maruti K. Mudunuru, James A. Ang, Mahantesh Halappanavar, Simon D. Hammond

Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to

Chen-Yu Liu

Grover search is a renowned quantum search algorithm that leverages quantum superposition to find a marked item with quadratic speedup. However, when implemented on Noisy Intermediate-scale Quantum (NISQ) hardware, the required repeated iterations of the oracle and diffusion operators increase exponentially with the number of qubits, resulting in significant

Fayçal Hammad, Parvaneh Sadeghi, Nicolas Fleury

We recently studied neutrinos flavor oscillations in vacuum within conformal coupling models. In this paper, we extend that analysis by investigating neutrino flavor oscillations inside matter within a general conformal coupling scenario. We first derive the general formula for the flavor transition probability inside matter in arbitrary static and spherical

Anoop Mishra, Deepak Khazanchi

Fairness in machine learning (ML) applications is an important practice for developers in research and industry. In ML applications, unfairness is triggered due to bias in the data, curation process, erroneous assumptions, and implicit bias rendered within the algorithmic development process. As ML applications come into broader use developing fair ML applic

Francesca Balestrieri

Let $k$ be any field. Let $X \subset \mathbb{P}_k^N$ be a degree $d \geq 2$ hypersurface. Under some conditions, we prove that if $X(K) \neq \emptyset$ for some extension $K/k$ with $n:=[K:k] \geq 2$ and $\gcd(n,d)=1$, then $X(L) \neq \emptyset$ for some extension $L/k$ with $\gcd([L:k], d)=1$, $n \nmid [L:k]$, and $[L:k] \leq nd-n-d$. Moreover, if a $K$-sol

Mohamad Alkateeb, Julio Rebelo

We provide examples of foliations on the complex projective plane $\CP^2$ carrying positive foliated harmonic currents whose supports coincide with singular Levi-flats which, in turn, can be chosen real-analytic (but non-algebraic) or merely continuous with fractal transverse nature. Furthermore, non-trivial examples as above can already be found among folia

Maria J. Rodriguez, Luca Santoni, Adam R. Solomon, Luis Fernando Temoche

We compute the tidal Love numbers and static response coefficients associated to several rotating black holes in higher dimensions, including Myers-Perry black holes, black rings, and black strings. These coefficients exhibit a rich and complex structure as a function of the black hole parameters and multipoles. Our results agree in limiting cases with known

Frank Schindler, Kaiyuan Gu, Biao Lian, Kohei Kawabata

Non-Hermitian band theory distinguishes between line gaps and point gaps. While point gaps can give rise to intrinsic non-Hermitian band topology without Hermitian counterparts, line-gapped systems can always be adiabatically deformed to a Hermitian limit. Here we show that line-gap topology and point-gap topology can be intricately connected: topological li

Luc Devroye, Jad Hamdan

We develop a simple algorithm to generate random variables described by densities equaling squared Hermite functions. As an application, we show how to generate a randomly chosen eigenvalue of a matrix from the Gaussian Unitary Ensemble ({\textsc{gue}}) in sub-linear expected time.

Xinyi Zhou, Paul Chao, Luke Sloan, Huai-Hsun Lien

Al-Si alloys processed by laser rapid solidification yield eutectic microstructures with ultrafine and interconnected fibers. Such fibrous structures have long been thought to bear resemblance to those formed in impurity-doped alloys upon conventional casting. Here, we show that any similarity is purely superficial. By harnessing high-throughput characteriza

Prithvi Akella, Aaron D. Ames

Efficient methods to provide sub-optimal solutions to non-convex optimization problems with knowledge of the solution's sub-optimality would facilitate the widespread application of nonlinear optimal control algorithms. To that end, leveraging recent work in risk-aware verification, we provide two algorithms to (1) probabilistically bound the optimality gaps

Lindsay Katz, Rohan Alexander

Public knowledge of what is said in parliament is a tenet of democracy, and a critical resource for political science research. In Australia, following the British tradition, the written record of what is said in parliament is known as Hansard. While the Australian Hansard has always been publicly available, it has been difficult to use for the purpose of la

Emilio Ferrara

As the capabilities of generative language models continue to advance, the implications of biases ingrained within these models have garnered increasing attention from researchers, practitioners, and the broader public. This article investigates the challenges and risks associated with biases in large-scale language models like ChatGPT. We discuss the origin

Birte Johansson

We verify the inductive McKay--Navarro condition for the groups $\mathsf{B}_2(2^f)$ and $\mathsf{G}_2(3^f)$ and all primes if $f$ is odd. Further, we show that the equivariance part of the inductive condition holds for all integers $f$.

N. V. Krylov

We prove existence and uniqueness of solutions in Morrey spaces of functions with mixed norms for second-oder parabolic equations in the whole space with VMO $a$ and Morrey $b,c$.

Wenzheng Dong, Gerardo A. Paz-Silva, Lorenza Viola

We show the usefulness of frame-based characterization and control [PRX Quantum 2, 030315 (2021)] for non-Markovian open quantum systems subject to classical non-Gaussian dephasing. By focusing on the paradigmatic case of random telegraph noise and working in a digital window frame, we demonstrate how to achieve higher-order control-adapted spectral estimati

Irene Ren

We present a proof of a conjecture proposed by V. Delecroix, E. Goujard, P. Zograf, and A. Zorich, which describes the large genus asymptotic behaviours of the ratio of frequencies of separating over nonseparating simple closed geodesics on a closed hyperbolic surface of genus $g$ with $n$ cusps. We explicitly give the function $f(\frac{n}{g})$ in the conjec

Brian Buckley, Adrian O'Hagan, Marie Galligan

We investigate the performance and characteristics of currently available VB and MCMC software to explore the practicability of available approaches and provide guidance for clinical practitioners. Two case studies are used to fully explore the methods covering a variety of real-world data. First, we use the publicly available Pima Indian diabetes data to co

Pooja Aggarwal, Michael Luby, Lorenz Minder

Immersive experiences, such as remote collaboration and augmented and virtual reality, require delivery of large volumes of data with consistent ultra-low latency across wireless networks in fluctuating network conditions. We describe the high-level design behind a data delivery solution that meets these requirements and provide synthetic simulations and tes

Stephen Fairhurst, Charlie Hoy, Rhys Green, Cameron Mills

Using simple, intuitive arguments, we discuss the expected accuracy with which astrophysical parameters can be extracted from an observed gravitational wave signal. The observation of a chirp like signal in the data allows for measurement of the component masses and aligned spins, while measurement in three or more detectors enables good localization. The ab

Ziming Huang, Zhuoxuan Jiang, Ke Wang, Juntao Li

Currently, human-bot symbiosis dialog systems, e.g., pre- and after-sales in E-commerce, are ubiquitous, and the dialog routing component is essential to improve the overall efficiency, reduce human resource cost, and enhance user experience. Although most existing methods can fulfil this requirement, they can only model single-source dialog data and cannot

Tejas Pagare, Vivek Borkar, Konstantin Avrachenkov

We extend the provably convergent Full Gradient DQN algorithm for discounted reward Markov decision processes from Avrachenkov et al. (2021) to average reward problems. We experimentally compare widely used RVI Q-Learning with recently proposed Differential Q-Learning in the neural function approximation setting with Full Gradient DQN and DQN. We also extend

Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, Wei Fang

Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-task language checkers based on their latent representations of natural and social knowledge. We present an interpretable, unified, language checking (UniLC) method for both human

Antonio Auffinger, Daniel Fletcher

We study the empirical measure of the output of the t-distributed stochastic neighbour embedding algorithm when the initial data is given by n independent, identically distributed inputs. We prove that under certain assumptions on the distribution of the inputs, this sequence of measures converges to an equilibrium distribution, which is described as a solut

Shun Hatano, Mitsuru Kokubo, Masami Ouchi, Kimihiko Nakajima

SBS~0335-052E is a young star-forming dwarf galaxy with a total stellar mass of $M_{*} \lesssim 10^{8}~M_{\odot}$ and an extremely low metallicity ($Z \sim 1/40~Z_{\odot}$), which has long been considered to be devoid of an active galactic nucleus (AGN). Here we report the detection of temporal flux variability of SBS~0335-052E in near-infrared (NIR) 3-4\ ${

Vihaan Dheer

Properties of morphisms represented by so-called 'string diagrams' of monoidal categories (and their braided and symmetric derivatives), mainly their resistance in value to isotopic deformation, have made the usage of graphical calculi commonplace in category theory ever since the correspondence between diagrams and tensor categories was rigorously establish

Lorenzo Guerrieri, K. Alan Loper

It is well-known that an integrally closed domain $D$ can be express as the intersection of its valuation overrings but, if $D$ is not a Pr\"{u}fer domain, the most of valuation overrings of $D$ cannot be seen as localizations of $D$. The Kronecker function ring of $D$ is a classical construction of a Pr\"{u}fer domain which is an overring of $D[t]$, and its

Boris van Breugel, Mihaela van der Schaar

Generating synthetic data through generative models is gaining interest in the ML community and beyond. In the past, synthetic data was often regarded as a means to private data release, but a surge of recent papers explore how its potential reaches much further than this -- from creating more fair data to data augmentation, and from simulation to text gener

T. Bédécarrats, B. Cardoso Paz, B. Martinez Diaz, H. Niebojewski

Operating Si quantum dot (QD) arrays requires homogeneous and ultra-dense structures with aggressive gate pitch. Such a density is necessary to separately control the QDs chemical potential (i.e. charge occupation of each QD) from the exchange interaction (i.e. tunnel barriers between each QD). We present here a novel Si quantum device integration that halve

Konstantinos Gaitanas

In this note, we provide some results concerning the structure of a set $A\subseteq \mathbb{Z}_n^{\times}$, which has non-empty subset sums equally distributed modulo $n$. Here, $\mathbb{Z}_n^{\times}$ denotes the set which contains all the invertible elements of the ring $\mathbb{Z}_n$. In particular, we prove that if $n=q$ is a power of an odd prime, then

Peyman Morteza

We develop a mathematical framework to address a broad class of metric and preference learning problems within a Hilbert space. We obtain a novel representer theorem for the simultaneous task of metric and preference learning. Our key observation is that the representer theorem for this task can be derived by regularizing the problem with respect to the norm

Victor Miguel Banda Guzmán, Adnan Bashir

We compute one-loop electron-photon vertex with fully off-shell external momenta in an arbitrary covariant gauge and space-time dimension. There exist numerous efforts in literature where one-loop off-shell vertex is calculated by employing the standard first order Feynman rules in different covariant gauges and space-time dimensions of interest. The tensor

Anoop Mishra, Gopinath Gangisetti, Deepak Khazanchi

Structural health monitoring (SHM) tasks like damage detection are crucial for decision-making regarding maintenance and deterioration. For example, crack detection in SHM is crucial for bridge maintenance as crack progression can lead to structural instability. However, most AI/ML models in the literature have low latency and late inference time issues whil

Yunwei Ren, Yuanzhi Li

Recently, contrastive learning approaches (e.g., CLIP (Radford et al., 2021)) have received huge success in multimodal learning, where the model tries to minimize the distance between the representations of different views (e.g., image and its caption) of the same data point while keeping the representations of different data points away from each other. How

Hudson A. Loughlin, Vivishek Sudhir

We study an abstract model of an oscillator realized by an amplifier embedded in a positive feedback loop. The power and frequency stability of the output of such an oscillator are limited by quantum noise added by two elements in the loop: the amplifier, and the out-coupler. The resulting frequency instability gives the Schawlow-Townes formula. Thus the app

Robert J. Ewart, Michael L. Nastac, Alexander A. Schekochihin

Collisionless and weakly collisional plasmas often exhibit non-thermal quasi-equilibria. Among these quasi-equilibria, distributions with power-law tails are ubiquitous. It is shown that the statistical-mechanical approach originally suggested by Lynden-Bell (1967) can easily recover such power-law tails. Moreover, we show that, despite the apparent diversit

Hünkar Can Tunç, Parosh Aziz Abdulla, Soham Chakraborty, Shankaranarayanan Krishna

Over the years, several memory models have been proposed to capture the subtle concurrency semantics of C/C++.One of the most fundamental problems associated with a memory model M is consistency checking: given an execution X, is X consistent with M? This problem lies at the heart of numerous applications, including specification testing and litmus tests, st

De-Ming Chian, Chao-Kai Wen, Chi-Hung Wu, Fu-Kang Wang

Future wireless networks require the ability to actively adjust the wireless environment to meet strict performance indicators. Reconfigurable Intelligent Surface (RIS) technology is gaining attention for its advantages of low power consumption, cost-effectiveness, and ease of deployment. However, existing channel models for RIS often ignore important proper

Mana Masuda, Yusuke Sekikawa, Hideo Saito

When a camera travels across a 3D world, only a fraction of pixel value changes; an event-based camera observes the change as sparse events. How can we utilize sparse events for efficient recovery of the camera pose? We show that we can recover the camera pose by minimizing the error between sparse events and the temporal gradient of the scene represented as

Ningquan Gu, Zhizhong Zhang, Ruhan He, Lianqing Yu

Bag manipulation through robots is complex and challenging due to the deformability of the bag. Based on dynamic manipulation strategy, we propose a new framework, ShakingBot, for the bagging tasks. ShakingBot utilizes a perception module to identify the key region of the plastic bag from arbitrary initial configurations. According to the segmentation, Shaki

João Barata, Xoán Mayo López, Andrey V. Sadofyev, Carlos A. Salgado

We calculate the spectrum of gluons sourced by the branching of an energetic quark in the presence of an inhomogeneous QCD medium, focusing on the soft radiation limit. We take into account multiple soft interactions between the partons and matter, treating the transverse variations of its parameters within a gradient expansion. Thus, we derive the general f

Giacomo Lamporesi

The high degree of control on ultracold gases allows us to precisely manipulate their internal state. When the gas is made of atoms in two different internal states, it can be considered as a two-component spin mixture. Below a critical temperature, the gas becomes a superfluid mixture, never realized before with any other platform, and therefore interesting

Yahav Alon, Michael Anastos

Let $\mu(G)$ denote the minimum number of edges whose addition to $G$ results in a Hamiltonian graph, and let $\hat{\mu}(G)$ denote the minimum number of edges whose addition to $G$ results in a pancyclic graph. We study the distributions of $\mu (G),\hat{\mu}(G)$ in the context of binomial random graphs. Letting $d=d(n) := n\cdot p$, we prove that there exi

Jin Chen, Zhi Gao, Xinxiao Wu, Jiebo Luo

Single domain generalization aims to learn a model from a single training domain (source domain) and apply it to multiple unseen test domains (target domains). Existing methods focus on expanding the distribution of the training domain to cover the target domains, but without estimating the domain shift between the source and target domains. In this paper, w

Gongning Luo, Kuanquan Wang, Jun Liu, Shuo Li

Efficient automatic segmentation of multi-level (i.e. main and branch) pulmonary arteries (PA) in CTPA images plays a significant role in clinical applications. However, most existing methods concentrate only on main PA or branch PA segmentation separately and ignore segmentation efficiency. Besides, there is no public large-scale dataset focused on PA segme

Veronica R. Policht, Henry Mittenzwey, Oleg Dogadov, Manuel Katzer

Vertical heterostructures (HS) of transition metal dichalcogenides (TMDs) host interlayer excitons (ILX), with electrons and holes residing in different layers. With respect to their intralayer counterparts, ILX feature much longer lifetimes and diffusion lengths, paving the way to excitonic optoelectronic devices operating at room temperature. While the rec

Michal Feldman, Simon Mauras, Vishnu V. Narayan, Tomasz Ponitka

We study best-of-both-worlds guarantees for the fair division of indivisible items among agents with subadditive valuations. Our main result establishes the existence of a random allocation that is simultaneously ex-ante $\frac{1}{2}$-envy-free, ex-post $\frac{1}{2}$-EFX and ex-post EF1, for every instance with subadditive valuations. We achieve this result

H. Jacquinot, R. Maurand, G. Troncoso Fernandez Bada, B. Bertrand

In this paper, we report on simulations of an Electron Spin Resonance (ESR) RF control line for semiconductor electron spin qubits. The simulation includes both the ESR line characteristics (geometry and configuration, stack and material properties) and the electromagnetic (EM) environment at the vicinity of the qubits such as gates and interconnect network.

K. Deja, V. Martinez-Fernandez, B. Pire, P. Sznajder

Double deeply virtual Compton scattering (DDVCS) is the process where an electron scatters off a nucleon and produces a lepton pair. The main advantage of this process in contrast with deeply virtual and timelike Compton scatterings (DVCS and TCS) is the possibility of directly measuring GPDs for $x\neq\pm\xi$ at leading order in $\alpha_s$ (LO). We present

Michael Gatchell, Henning Zettergren, Klavs Hansen

Fullerenes are lowest energy structures for gas phase all-carbon particles for a range of sizes, but graphite remains the lowest energy allotrope of bulk carbon. This implies that the lowest energy structure changes nature from fullerenes to graphite or graphene at some size and therefore, in turn, implies a limit on the size of free fullerenes as ground sta

D. N. Sob'yanin

The recent discovery of a radio-emitting neutron star with an ultralong spin period of 76 s, PSR J0901-4046, raises a fundamental question on how such a slowly rotating magnetized object can be active in the radio band. A canonical magnetic field of $1.3\times10^{14}$ G estimated from the pulsar period and its time derivative is wholly insufficient for PSR J

Junjie Dong

Nominally anhydrous minerals (NAMs) are the primary carriers of water in rocky planet mantles. Therefore, studying water solubilities of major NAMs in the mantle can help us estimate the water storage capacities of rocky planet mantles and indirectly constrain the actual water contents of their interiors. By using data science methods such as statistics and

Muhammad Nadeem, Ahmad F. Taha

This paper presents a new approach to approximate the AC optimal power flow (ACOPF). By eliminating the need to solve the ACOPF every few minutes, the paper showcases how a realtime feedback controller can be utilized in lieu of ACOPF and its variants. By (i) forming the grid dynamics as a system of differential-algebraic equations (DAE) that naturally encod

Vrizlynn L. L. Thing

The rapid evolvement of deepfake creation technologies is seriously threating media information trustworthiness. The consequences impacting targeted individuals and institutions can be dire. In this work, we study the evolutions of deep learning architectures, particularly CNNs and Transformers. We identified eight promising deep learning architectures, desi

Sonia Raychaudhuri, Tommaso Campari, Unnat Jain, Manolis Savva

We propose a simple but effective modular approach MOPA (Modular ObjectNav with PointGoal agents) to systematically investigate the inherent modularity of the object navigation task in Embodied AI. MOPA consists of four modules: (a) an object detection module trained to identify objects from RGB images, (b) a map building module to build a semantic map of th

Yusuke Hirota, Yuta Nakashima, Noa Garcia

Image captioning models are known to perpetuate and amplify harmful societal bias in the training set. In this work, we aim to mitigate such gender bias in image captioning models. While prior work has addressed this problem by forcing models to focus on people to reduce gender misclassification, it conversely generates gender-stereotypical words at the expe

Hünkar Can Tunç, Umang Mathur, Andreas Pavlogiannis, Mahesh Viswanathan

Deadlocks are one of the most notorious concurrency bugs, and significant research has focused on detecting them efficiently. Dynamic predictive analyses work by observing concurrent executions, and reason about alternative interleavings that can witness concurrency bugs. Such techniques offer scalability and sound bug reports, and have emerged as an effecti

Zihao Wang, Vrizlynn L. L. Thing

The popularity of encryption mechanisms poses a great challenge to malicious traffic detection. The reason is traditional detection techniques cannot work without the decryption of encrypted traffic. Currently, research on encrypted malicious traffic detection without decryption has focused on feature extraction and the choice of machine learning or deep lea

Jau-Uei Chen, Shinhoo Kang, Tan Bui-Thanh, John N. Shadid

This work proposes a unified $hp$-adaptivity framework for hybridized discontinuous Galerkin (HDG) method for a large class of partial differential equations (PDEs) of Friedrichs' type. In particular, we present unified $hp$-HDG formulations for abstract one-field and two-field structures and prove their well-posedness. In order to handle non-conforming inte

Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang

Generative modelling over continuous-time geometric constructs, a.k.a such as handwriting, sketches, drawings etc., have been accomplished through autoregressive distributions. Such strictly-ordered discrete factorization however falls short of capturing key properties of chirographic data -- it fails to build holistic understanding of the temporal concept d

Ayoub Farkane, Mounir Ghogho, Mustapha Oudani, Mohamed Boutayeb

Fluid mechanics is a fundamental field in engineering and science. Solving the Navier-Stokes equation (NSE) is critical for understanding the behavior of fluids. However, the NSE is a complex partial differential equation that is difficult to solve, and classical numerical methods can be computationally expensive. In this paper, we present an innovative appr

Christophe Paul, Evangelos Protopapas, Dimitrios M. Thilikos

We establish a parametric framework for obtaining obstruction characterizations of graph parameters with respect to a quasi-ordering $\leqslant$ on graphs. At the center of this framework lies the concept of a $\leqslant$-parametric graph: a non $\leqslant$-decreasing sequence $\mathscr{G} = \langle \mathscr{G}_{t} \rangle_{t \in \mathbb{N}}$ of graphs index

Muhammad Umar B. Niazi, Karl H. Johansson

Traditional observer design methods rely on certain properties of the system's nonlinearity, such as Lipschitz continuity, one-sided Lipschitzness, a bounded Jacobian, or quadratic boundedness. These properties are described by parameterized inequalities. However, enforcing these inequalities globally can lead to very large parameters, resulting in overly co

Robert P. Laudone, Andrew Snowden

A symmetric chain of ideals is a rule that assigns to each finite set $S$ an ideal $I_S$ in the polynomial ring $\mathbb{C}[x_i]_{i \in S}$ such that if $\phi \colon S \to T$ is an embedding of finite sets then the induced homomorphism $\phi_*$ maps $I_S$ into $I_T$. Cohen proved a fundamental noetherian result for such chains, which has seen intense interes

Jeroen S. W. Lamb, Giuseppe Tenaglia, Dmitry Turaev

We propose a notion of random horseshoe for one-dimensional random dynamical systems. We prove the abundance of random horseshoes for a class of circle endomorphisms subject to additive noise, large enough to make the Lyapunov exponent positive. In particular, we provide conditions which guarantee that given any pair of disjoint intervals, for almost every n

Vijay A. Singh

We discuss the work of a brilliant line of Mathematicians who lived in central Kerala and starting with its founder Madhava (1350 CE) developed what can best be described as Calculus and applied it to a class of trigonometric functions. We explain, with the example of the expansion of the inverse tan function, how they handled integration. Further, they took

Johannes Pseiner, Manuel Erhard, Mario Krenn

The search for macroscopic quantum phenomena is a fundamental pursuit in quantum mechanics. It allows us to test the limits quantum physics and provides new avenues for exploring the interplay between quantum mechanics and relativity. In this work, we introduce a novel approach to generate macroscopic quantum systems by demonstrating that the creation proces

Shadman Rohan, Mojammel Hossain, Mohammad Mamun Or Rashid, Nabeel Mohammed

Coreference Resolution is a well studied problem in NLP. While widely studied for English and other resource-rich languages, research on coreference resolution in Bengali largely remains unexplored due to the absence of relevant datasets. Bengali, being a low-resource language, exhibits greater morphological richness compared to English. In this article, we

Vasco Cavina, Sadeq S. Kadijani, Massimiliano Esposito, Thomas Schmidt

The work fluctuation theorem (FT) is a symmetry connecting the moment generating functions (MGFs) of the work extracted in a given process and in its time-reversed counterpart. We show that, equivalently, the FT for work in isolated quantum systems can be expressed as an invariance property of a modified Keldysh contour. Modified contours can be used as star

Bjarne Kosmeijer, Hessel Posthuma

Given a smooth action of a Lie group on a manifold, we give two constructions of the Chern character of an equivariant vector bundle in the cyclic cohomology of the crossed product algebra. The first construction associates a cycle to the vector bundle whose structure maps are closely related to Getzler's model for equivariant cohomology. The second construc

Xiaohui Xie, Qian Dong, Bingning Wang, Feiyang Lv

Passage ranking involves two stages: passage retrieval and passage re-ranking, which are important and challenging topics for both academics and industries in the area of Information Retrieval (IR). However, the commonly-used datasets for passage ranking usually focus on the English language. For non-English scenarios, such as Chinese, the existing datasets

Yutong Li, Nan Li, Anouck Girard, Ilya Kolmanovsky

Dosage schedule of the Proton Pump Inhibitors (PPIs) is critical for gastric acid disorder treatment. In this paper, we develop a constrained optimization based approach for scheduling the PPIs dosage. In particular, we exploit a mathematical prediction model describing the gastric acid secretion, and use it within the optimization algorithm to predict the a

Rama K. Malladi, Phillip Thompson

As the United States is witnessing elevated racial differences pertaining to economic disparities, we have found a unique example contrary to the traditional narrative. Idaho is the only US state where Blacks earn more than Whites and all other races. In this paper, we examine how Idaho Blacks might have achieved economic success and, more importantly, what

Christian Rosendal

Under the weak assumption on a Banach space $E$ that $E\oplus E$ embeds isomorphically into $E$, we provide a characterisation of when a Banach space $X$ coarsely embeds into $E$ via a single numerical invariant.

Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz

In the recent years, machine learning has made great advancements that have been at the root of many breakthroughs in different application domains. However, it is still an open issue how make them applicable to high-stakes or safety-critical application domains, as they can often be brittle and unreliable. In this paper, we argue that requirements definitio

Lucas Gautheron, Elisa Omodei

According to Peter Galison, the coordination of different ``subcultures'' within a scientific field happens through local exchanges within ``trading zones''. In his view, the workability of such trading zones is not guaranteed, and science is not necessarily driven towards further integration. In this paper, we develop and apply quantitative methods (using s

Luca Grillotti, Manon Flageat, Bryan Lim, Antoine Cully

Quality-Diversity (QD) algorithms are designed to generate collections of high-performing solutions while maximizing their diversity in a given descriptor space. However, in the presence of unpredictable noise, the fitness and descriptor of the same solution can differ significantly from one evaluation to another, leading to uncertainty in the estimation of

Akash Harapanahalli, Saber Jafarpour, Samuel Coogan

In this paper, we present a contraction-guided adaptive partitioning algorithm for improving interval-valued robust reachable set estimates in a nonlinear feedback loop with a neural network controller and disturbances. Based on an estimate of the contraction rate of over-approximated intervals, the algorithm chooses when and where to partition. Then, by lev

Hiromichi Tagawa, Zoltán Haiman

The origin of the recently discovered new class of transients, X-ray quasi-periodic eruptions (QPEs), remains a puzzle. Due to their periodicity and association with active galactic nuclei (AGN), it is natural to relate these eruptions to stars or compact objects in tight orbits around supermassive black holes (SMBHs). In this paper, we predict the propertie

Haoyuan Li, Hao Jiang, Tao Jin, Mengyan Li

Product Retrieval (PR) and Grounding (PG), aiming to seek image and object-level products respectively according to a textual query, have attracted great interest recently for better shopping experience. Owing to the lack of relevant datasets, we collect two large-scale benchmark datasets from Taobao Mall and Live domains with about 474k and 101k image-query