November 2022 arXiv papers — page 103

Eunjin Choi, Yoonjin Chung, Seolhee Lee, JongIk Jeon

Existing multi-instrumental datasets tend to be biased toward pop and classical music. In addition, they generally lack high-level annotations such as emotion tags. In this paper, we propose YM2413-MDB, an 80s FM video game music dataset with multi-label emotion annotations. It includes 669 audio and MIDI files of music from Sega and MSX PC games in the 80s

SM Zobaed, Ali Mokhtari, Jaya Prakash Champati, Mathieu Kourouma

Smart IoT-based systems often desire continuous execution of multiple latency-sensitive Deep Learning (DL) applications. The edge servers serve as the cornerstone of such IoT-based systems, however, their resource limitations hamper the continuous execution of multiple (multi-tenant) DL applications. The challenge is that, DL applications function based on b

Brandon Alberts

In arithmetic statistics and analytic number theory, the asymptotic growth rate of counting functions giving the number of objects with order below $X$ is studied as $X\to \infty$. We define general counting functions which count epimorphisms out of an object on a category under some ordering. Given a probability measure $\mu$ on the isomorphism classes of t

P. D. Aleo, K. Malanchev, S. Sharief, D. O. Jones

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multi-color Pan-STARRS1 (PS1) griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host-galaxy associations, redshifts, spectroscopic/photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1

Daniel Richter, Mathias Wegner, Felix Ahrens, Christian Enss

Magnetic microcalorimeters (MMCs) are cryogenic, energy-dispersive single-particle detectors providing excellent energy resolution, intrinsically fast signal rise time, quantum efficiency close to 100\%, large dynamic range as well as almost ideal linear response. One of the remaining challenges to be overcome to ultimately allow for the utilization of large

Thomas Searle, Zina Ibrahim, James Teo, Richard Dobson

Brief Hospital Course (BHC) summaries are succinct summaries of an entire hospital encounter, embedded within discharge summaries, written by senior clinicians responsible for the overall care of a patient. Methods to automatically produce summaries from inpatient documentation would be invaluable in reducing clinician manual burden of summarising documents

Samuel Chevalier, Spyros Chatzivasileiadis

Machine learning, which can generate extremely fast and highly accurate black-box surrogate models, is increasingly being applied to a variety of AC power flow problems. Rigorously verifying the accuracy of the resulting black-box models, however, is computationally challenging. This paper develops a tractable neural network verification procedure which inco

Jen-Tsung Hsiang, Onat Arısoy, Bei-Lok Hu

This work strives to better understand how the entanglement in an open quantum system, here represented by two coupled Brownian oscillators, is affected by a nonMarkovian environment (with memories), here represented by two independent baths each oscillator separately interacts with. We consider two settings, a `symmetric' configuration wherein the parameter

Hugh L. Kennedy

The low-pass filter is a fundamental building block from which digital signal-processing systems (e.g. radio and radar) are built. Signals in the electromagnetic spectrum extend over all timescales/frequencies and are used to transmit and receive very long or very short pulses of very narrow or very wide bandwidth. Time/Frequency agility is the key for optim

Chanda Grover, Indra Deep Mastan, Debayan Gupta

State-of-the-art empirical work has shown that visual representations learned by deep neural networks are robust in nature and capable of performing classification tasks on diverse datasets. For example, CLIP demonstrated zero-shot transfer performance on multiple datasets for classification tasks in a joint embedding space of image and text pairs. However,

Yelnury Suleimen, Artem Podlesnyy, Lianna A. Akopyan, Nikita Sterligov

We describe the design and operation of a surface-electrode Paul trap for parallel entangling gate implementation. In particular, we demonstrate the possibility of separating or coupling ion motion by adjusting the DC-voltages on a set of electrodes and show the possibility of parallel MS-gate operations for specific voltage configurations. We verify the sca

Yongsoon Eun, Jaeho Lee, Hyungbo Shim

This work develops a data-based construction of inverse dynamics for LTI systems. Specifically, the problem addressed here is to find an input sequence from the corresponding output sequence based on pre-collected input and output data. The problem can be considered as a reverse of the recent use of behavioral approach, in which the output sequence is obtain

P. Zhang, A. Zarassi, L. Jarjat, V. Van de Sande

We investigate the current-phase relations of Al/InAs-quantum well planar Josephson junctions fabricated using nanowire shadowing technique. Based on several experiments, we conclude that the junctions exhibit an unusually large second-order Josephson harmonic, the $\sin(2\varphi)$ term. First, superconducting quantum interference devices (dc-SQUIDs) show ha

Quan Quan, Qingsong Yao, Jun Li, S. kevin Zhou

Contrastive learning (CL) is a form of self-supervised learning and has been widely used for various tasks. Different from widely studied instance-level contrastive learning, pixel-wise contrastive learning mainly helps with pixel-wise tasks such as medical landmark detection. The counterpart to an instance in instance-level CL is a pixel, along with its nei

Jinwoo Kim, Loris D'Antoni, Thomas Reps

We consider the problem of establishing that a program-synthesis problem is unrealizable (i.e., has no solution in a given search space of programs). Prior work on unrealizability has developed some automatic techniques to establish that a problem is unrealizable; however, these techniques are all black-box, meaning that they conceal the reasoning behind why

Deunsol Jung, Dahyun Kang, Suha Kwak, Minsu Cho

Metric learning aims to build a distance metric typically by learning an effective embedding function that maps similar objects into nearby points in its embedding space. Despite recent advances in deep metric learning, it remains challenging for the learned metric to generalize to unseen classes with a substantial domain gap. To tackle the issue, we explore

Amir Rezaie-Dereshgi, Hamidreza Khalilian, Jalal Sarabadani

Translocation dynamics of an active semi-flexible polymer through a nano-pore into a rigid two dimensional circular cavity, and the polymer packing dynamics have been studied by using Langevin dynamics (LD) simulations. The results show that the force exponent $\beta$, for regime of small cavity radius, i.e. $R \ll R_{\textrm{g}}$, where $R_{\textrm{g}}$ is

Hamidreza Khalilian, Jalal Sarabadani, Tapio Ala-Nissila

We consider the dynamics of a translocation process of a flexible linear polymer through a nanopore into an environment of active rods in the {\it trans} side. Using Langevin dynamics simulations we find that the rods facilitate translocation to the {\it trans} side even when there are initially more monomers on the {\it cis} than on the {\it trans} side. St

Zilai Si, Yucong Liu, Alexander Strang

Maximum a posteriori (MAP) estimation, like all Bayesian methods, depends on prior assumptions. These assumptions are often chosen to promote specific features in the recovered estimate. The form of the chosen prior determines the shape of the posterior distribution, thus the behavior of the estimator and complexity of the associated optimization problem. He

Wei Zhang, Jr-Shin Li

Koopman operators, since introduced by the French-born American mathematician Bernard Koopman in 1931, have been employed as a powerful tool for research in various scientific domains, such as ergodic theory, probability theory, geometry, and topology. The current use of Koopman operators mainly focuses on the characterization of spectral properties of ergod

Kieran F. Thomas, Zhuoxian Ou, Bryce M. Henson, Angela A. Baiju

We report on the achievement of quantum degeneracy in both components of a Bose-Fermi mixture of metastable helium atoms, $^4$He* and $^3$He*. Degeneracy is achieved via Doppler cooling and forced evaporation for $^4$He*, and sympathetically cooling $^3$He* with $^4$He*. We discuss our simplified implementation, along with the high versatility of our system.

Jingcheng Shen, Linbo Long, Masao Okita, Fumihiko Ino

Quantum computing is a hotspot technology for its potential to accelerate specific applications by exploiting quantum parallelism. However, current physical quantum computers are limited to a relatively small scale, simulators based on conventional machines are significantly relied on to perform quantum computing research. The straightforward array-based sim

Osama Elmabrok, Mohsen Razavi, Tawfig Eltaif, Khaled A. Alaghbari

We investigate the use of high-dimensional quantum key distribution (HD-QKD) in wireless access to hybrid quantum classical networks. We study the distribution of d-dimensional time-phase encoded states between an indoor wireless user and the central office on the other end of the access network. We evaluate the performance in the case of transmitting quantu

Shun Gui, Yan Luximon

Heavily relying on 3D annotations limits the real-world application of 3D object detection. In this paper, we propose a method that does not demand any 3D annotation, while being able to predict fully oriented 3D bounding boxes. Our method, called Recursive Cross-View (RCV), utilizes the three-view principle to convert 3D detection into multiple 2D detection

Kan Zhang, Jiling Li, Peitao Liu, Guowei Yang

Polyyne, a sp1-hybridized linear allotrope of carbon, has a tunable quasiparticle energy gap, which depends on the terminated chemical ending groups as well as the chain length. Previously, nitrogen doping was utilized to tailor the properties of different kinds of allotrope of carbon. However, how the nitrogen doping tailors the properties of the polyyne re

Zhaobing Fan, Shaolong Han, Seok-Jin Kang, Yong-Su Shin

With the help of path realization and affine energy function, we give a Young wall construction of level-1 highest weight crystals $B(\lambda)$ over $U_{q}(G_{2}^{(1)})$ and $U_{q}(D_{4}^{(3)})$. Our construction is based on four different shapes of colored blocks, $\mathbf O$-block, $\mathbf I$-block, $\mathbf L$-block and $\mathbf{LL}$-block, obtained by c

Weijie Sun, Sunil Vasu Kalmady, Nariman Sepehrvand, Luan Manh Chu

Pandemic outbreaks such as COVID-19 occur unexpectedly, and need immediate action due to their potential devastating consequences on global health. Point-of-care routine assessments such as electrocardiogram (ECG), can be used to develop prediction models for identifying individuals at risk. However, there is often too little clinically-annotated medical dat

Marjan Hosseini, Devin McConnell, Derek Aguiar

Characterizing the differential excision of mRNA is critical for understanding the functional complexity of a cell or tissue, from normal developmental processes to disease pathogenesis. Most transcript reconstruction methods infer full-length transcripts from high-throughput sequencing data. However, this is a challenging task due to incomplete annotations

Liangwei Yang, Shen Wang, Jibing Gong, Shaojie Zheng

Knowledge graph (KG) enhanced recommendation has demonstrated improved performance in the recommendation system (RecSys) and attracted considerable research interest. Recently the literature has adopted neural graph networks (GNNs) on the collaborative knowledge graph and built an end-to-end KG-enhanced RecSys. However, the majority of these approaches have

Cancan Huang, Brenda M. Rubenstein

Diffusion Monte Carlo (DMC) is one of the most accurate techniques available for calculating the electronic properties of molecules and materials, yet it often remains a challenge to economically compute forces using this technique. As a result, ab initio molecular dynamics simulations and geometry optimizations that employ Diffusion Monte Carlo forces are o

Xingwei Wang, Haiquan Lu, Yong Zeng

Delay alignment modulation (DAM) is a novel wideband communication technique, which exploits the high spatial resolution and multi-path sparsity of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems to mitigate inter-symbol interference (ISI), without relying on conventional techniques like channel equalization or multi-carrier tr

Stuart Lyall, Chris Blake, Ryan Turner, Rossana Ruggeri

The theoretical basis of dark energy remains unknown and could signify a need to modify the laws of gravity on cosmological scales. In this study we investigate how the clustering and motions of galaxies can be used as probes of modified gravity theories, using galaxy and direct peculiar velocity auto- and cross-correlation functions. We measure and fit thes

Abhin Shah, Raaz Dwivedi, Devavrat Shah, Gregory W. Wornell

Given an observational study with $n$ independent but heterogeneous units, our goal is to learn the counterfactual distribution for each unit using only one $p$-dimensional sample per unit containing covariates, interventions, and outcomes. Specifically, we allow for unobserved confounding that introduces statistical biases between interventions and outcomes

Yongliang Song, Xianyong Bai, Xu Yang, Wenda Cao

Solar observations of carbon monoxide (CO) indicate the existence of lower-temperature gas in the lower solar chromosphere. We present an observation of pores, and quiet-Sun, and network magnetic field regions with CO 4.66 {\mu}m lines by the Cryogenic Infrared Spectrograph (CYRA) at Big Bear Solar Observatory. We used the strong CO lines at around 4.66 {\mu

Alina Chertock, Shaoshuai Chu, Alexander Kurganov

We develop new adaptive alternative weighted essentially non-oscillatory (A-WENO) schemes for hyperbolic systems of conservation laws. The new schemes employ the recently proposed local characteristic decomposition based central-upwind numerical fluxes, the three-stage third-order strong stability preserving Runge-Kutta time integrator, and the fifth-order W

Yang Peng, Daisy Zhe Wang

Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge. However, these knowledge bases are highly incomplete. To solve this problem, we propose a web-based question answering system system with multimodal fusion of unstructured and structured information, to fill in missing information for knowledge bases.

Liora Mayats-Alpay

Detecting and classifying diseases using X-ray images is one of the more challenging core tasks in the medical and research world. Due to the recent high interest in radiological images and AI, early detection of diseases in X-ray images has become notably more essential to prevent further spreading and flatten the curve. Innovations and revolutions of Compu

Igor G. Vladimirov, Ian R. Petersen

This paper is concerned with the coherent quantum linear-quadratic-Gaussian control problem of minimising an infinite-horizon mean square cost for a measurement-free field-mediated interconnection of a quantum plant with a stabilising quantum controller. The plant and the controller are multimode open quantum harmonic oscillators, governed by linear quantum

Quan Xiao, Han Shen, Wotao Yin, Tianyi Chen

Stochastic bilevel optimization, which captures the inherent nested structure of machine learning problems, is gaining popularity in many recent applications. Existing works on bilevel optimization mostly consider either unconstrained problems or constrained upper-level problems. This paper considers the stochastic bilevel optimization problems with equality

Liyang Lu, Wenbo Xu, Yue Wang, Zhi Tian

This paper proposes two novel schemes of wideband compressive spectrum sensing (CSS) via block orthogonal matching pursuit (BOMP) algorithm, for achieving high sensing accuracy in real time. These schemes aim to reliably recover the spectrum by adaptively adjusting the number of required measurements without inducing unnecessary sampling redundancy. To this

T. Westmeier, N. Deg, K. Spekkens, T. N. Reynolds

We present WALLABY pilot data release 1, the first public release of HI pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder. Phase 1 of the WALLABY pilot survey targeted three $60~{\rm deg}^2$ regions on the sky in the direction of the Hydra and Norma galaxy clusters and

Ke Wang, Xin Ge, Jiayi Wang, Yu Zhao

Machine translation technology has made great progress in recent years, but it cannot guarantee error free results. Human translators perform post editing on machine translations to correct errors in the scene of computer aided translation. In favor of expediting the post editing process, many works have investigated machine translation in interactive modes,

Imon Banerjee, Harsha Honnappa, Vinayak Rao

In this work, we study a natural nonparametric estimator of the transition probability matrices of a finite controlled Markov chain. We consider an offline setting with a fixed dataset, collected using a so-called logging policy. We develop sample complexity bounds for the estimator and establish conditions for minimaxity. Our statistical bounds depend on th

Yefei He, Zhenyu Lou, Luoming Zhang, Jing Liu

Model binarization can significantly compress model size, reduce energy consumption, and accelerate inference through efficient bit-wise operations. Although binarizing convolutional neural networks have been extensively studied, there is little work on exploring binarization of vision Transformers which underpin most recent breakthroughs in visual recogniti

Yuwei Ren, Jiuyuan Lu, Andrian Beletchi, Yin Huang

We explore the feasibility of AI assisted hand-gesture recognition using 802.11ad 60GHz (mmWave) technology in smartphones. Range-Doppler information (RDI) is obtained by using pulse Doppler radar for gesture recognition. We built a prototype system, where radar sensing and WLAN communication waveform can coexist by time-division duplex (TDD), to demonstrate

Yunfeng Fan, Wenchao Xu, Haozhao Wang, Junxiao Wang

Multimodal learning (MML) aims to jointly exploit the common priors of different modalities to compensate for their inherent limitations. However, existing MML methods often optimize a uniform objective for different modalities, leading to the notorious "modality imbalance" problem and counterproductive MML performance. To address the problem, some existing

Houxin Zhou

In most medical image processing tasks, the orientation of an image would affect computing result. However, manually reorienting images wastes time and effort. In this paper, we study the problem of recognizing orientation in cardiac MRI and using deep neural network to solve this problem. For multiple sequences and modalities of MRI, we propose a transfer l

Jikang Wang

It was shown by Mondino-Wei that any $\mathrm{RCD}^{*}(K,N)$ space $(X,d,\mathfrak{m})$ has a universal cover. We prove that for any point $x \in X$ and $R>0$, there exists $r<R$ such that any loop in $B_r(x)$ is contractible in $B_R(x)$; in particular, $X$ is semi-locally simply connected and the universal cover of $X$ is simply connected. This generalizes

Chatchai Noytaptim, Clayton Petsche

We classify all post-critically finite unicritical polynomials defined over the maximal totally real algebraic extension of ${\mathbb Q}$. Two auxiliary results used in the proof of this result may be of some independent interest. The first is a recursion formula for the $n$-diameter of an interval, which uses properties of Jacobi polynomials. The second is

Wei Han, Yangqiming Wang, Christian Böhm, Junming Shao

Although deep neural networks have shown well-performance in various tasks, the poor interpretability of the models is always criticized. In the paper, we propose a new interpretable neural network method, by embedding neurons into the semantic space to extract their intrinsic global semantics. In contrast to previous methods that probe latent knowledge insi

Hsiao-Wen Yu, Cheng-En Lee, Ruhui Zhang, Cheng-Shang Chang

Most existing works on analyzing the performance of a random ensemble of low-density parity-check (LDPC) codes assume that the degree distributions of the two ends of a randomly selected edge are independent. In the paper, we take one step further and consider ensembles of LDPC codes with degree-degree correlations. For this, we propose two methods to constr

Xiaopei Wu, Yang Zhao, Liang Peng, Hua Chen

Current 3D object detection methods heavily rely on an enormous amount of annotations. Semi-supervised learning can be used to alleviate this issue. Previous semi-supervised 3D object detection methods directly follow the practice of fully-supervised methods to augment labeled and unlabeled data, which is sub-optimal. In this paper, we design a data augmenta

Xue-Chao Feng, Ke-Wei Wei, Jie-Wu

Based on the mass relations from the Regge phenomenology, we revisit the mass spectrum of $1^{3}D_{1}$ meson nonet. The masses of kaon and $s\bar{s}$ member of $1^{3}D_{1}$ ($1^{3}D_{1}(s\bar{s})$) meson nonet are obtained and the results are compared with the values from different theoretical models. Moreover, the strong decay properties of the kaon and $1^

Xiang Gao, Wei Hu, Renjie Liao

Strong evidence suggests that humans perceive the 3D world by parsing visual scenes and objects into part-whole hierarchies. Although deep neural networks have the capability of learning powerful multi-level representations, they can not explicitly model part-whole hierarchies, which limits their expressiveness and interpretability in processing 3D vision da

Jiaqi Hu, Zhuoran Du

We study anti-symmetric solutions about the hyperplane $\{x_n=0\}$ to the following fractional Hardy-H\'{e}non system $$ \left\{\begin{aligned} &(-\Delta)^{s_1}u(x)=|x|^\alpha v^p(x),\ \ x\in\mathbb{R}_+^n, \\&(-\Delta)^{s_2}v(x)=|x|^\beta u^q(x),\ \ x\in\mathbb{R}_+^n, \\&u(x)\geq 0,\ \ v(x)\geq 0,\ \ x\in\mathbb{R}_+^n, \end{aligned}\right. $$ where $0<s_1

Jaydip Sen

A pair-trading strategy is an approach that utilizes the fluctuations between prices of a pair of stocks in a short-term time frame, while in the long-term the pair may exhibit a strong association and co-movement pattern. When the prices of the stocks exhibit significant divergence, the shares of the stock that gains in price are sold (a short strategy) whi

Jaroslav Pavličko, Mário Ziman

We investigate robustness of probabilistic storage and retrieval device optimized for phase gates to noise. We use noisy input composed of convex combination of unitary channel with either depolarizing or dephasing channel. We find out that the resistance to dephasing noise is higher than to depolarization. Interestingly, for the depolarisation the retrieval

Yiyuan Li, Tong Che, Yezhen Wang, Zhengbao Jiang

Pretrained language models (PLMs) have been shown to accumulate factual knowledge during pretrainingng (Petroni et al., 2019). Recent works probe PLMs for the extent of this knowledge through prompts either in discrete or continuous forms. However, these methods do not consider symmetry of the task: object prediction and subject prediction. In this work, we

Byungho Jo, Donghyeon Cho, In Kyu Park, Sungeun Hong

Existing face restoration models have relied on general assessment metrics that do not consider the characteristics of facial regions. Recent works have therefore assessed their methods using human studies, which is not scalable and involves significant effort. This paper proposes a novel face-centric metric based on an adversarial framework where a generato

Yukti Makhija, Edward De Brouwer, Rahul G. Krishnan

Checklists, while being only recently introduced in the medical domain, have become highly popular in daily clinical practice due to their combined effectiveness and great interpretability. Checklists are usually designed by expert clinicians that manually collect and analyze available evidence. However, the increasing quantity of available medical data is c

Rodrigo Araiza Bravo, Khadijeh Najafi, Taylor L. Patti, Xun Gao

Quantum neuromorphic computing (QNC) is a sub-field of quantum machine learning (QML) that capitalizes on inherent system dynamics. As a result, QNC can run on contemporary, noisy quantum hardware and is poised to realize challenging algorithms in the near term. One key issue in QNC is the characterization of the requisite dynamics for ensuring expressive qu

Dan Zhang, Guoyang Fu, Xi-Jing Wang, Qiyuan Pan

The transport features of the holographic two-currents model are investigated in the Horndeski gravity framework. This system displays metallic or insulating characteristics depending on whether the Horndeski coupling parameter $\gamma$ is negative or positive, but is unaffected by other system parameters such as the strength of the momentum dissipation $\ha

Vinitha Balachandran, Lea F. Santos, Marcos Rigol, Dario Poletti

Out-of-time ordered correlators (OTOCs) help characterize the scrambling of quantum information and are usually studied in the context of nonintegrable systems. In this work, we compare the relaxation dynamics of OTOCs in interacting integrable and nonintegrable spin-1/2 XYZ chains in regimes without a classical counterpart. In both kinds of chains, using th

Yong Zheng

The usual implement procedure for the reconstruction of secular equation for an effective Hamiltonian has been discussed and improved. A relative characteristic polynomial has been introduced for the effective Hamiltonian, to obtain a simplified effective-secular-equation which is equivalent to the one obtained in the usual reconstruction procedure but shows

Cheng Zhang, Qian-Shun Dai, Ding Yu Shao

We study the azimuthal angular decorrelation of the dijet production via photon fusion in ultra-peripheral heavy ion collisions. The impact parameter dependent cross section of quark-antiquark pairs production is derived using the equivalent photon approximation, and the contribution from final-state QCD radiations to the azimuthal angular distribution are c

Huai-Yu Wang

In mathematical physics, time-dependent Green's functions (GFs) are the solutions of differential equations of the first and second time derivatives. Habitually, the time-dependent GFs are Fourier transformed into the frequency space. Then, analytical continuation of the frequency is extended to below or above the real axis. After inverse Fourier transformat

Zhen-Jie Wang, Ze-Rui Wang, Ruo-Yu Liu, Junfeng Wang

The radiation mechanism of Radio-Loud Narrow-Line Seyfert 1 (RL-NLS1) from X-ray to $\gamma$-ray bands remains an open question. While the leptonic model has been employed to explain the spectral energy distribution (SED), the hadronic process may potentially account for the high energy radiation of some $\gamma$-ray loud Narrow-Line Seyfert 1 (NLS1) as well

Jun Hu, Lei Shi

In this paper, we construct some integral bases for the cocenter of the cyclotomic Hecke algebra $\mathscr{H}_{n,K}$ of type $G(r,1,n)$ by generalizing Geck and Pfeiffer's work on the cocenters of the Iwahori-Hecke algebras associated to finite Weyl groups. We show that the dimensions of both the cocenter and the center of the cyclotomic Hecke algebra $\math

Yiwen Gao, Yuan Li, Haibin Kan

Complex orthogonal designs (CODs) play a crucial role in the construction of space-time block codes. Their real analog, real orthogonal designs (or equivalently, sum of squares composition formula) have a long history. Adams et al. (2011) introduced the concept of balanced complex orthogonal designs (BCODs) to address practical considerations. BCODs have a c

Xinya Du, Heng Ji

Event argument extraction has long been studied as a sequential prediction problem with extractive-based methods, tackling each argument in isolation. Although recent work proposes generation-based methods to capture cross-argument dependency, they require generating and post-processing a complicated target sequence (template). Motivated by these observation

Nianlong Gu, Richard H. R. Hahnloser

Citation generation aims to generate a citation sentence that refers to a chosen paper in the context of a manuscript. However, a rigid citation generation process is at odds with an author's desire to control specific attributes, such as 1) the citation intent, e.g., either introducing background information or comparing results, and 2) keywords that should

Byeongmin Choi, YongHyun Lee, Yeunwoong Kyung, Eunchan Kim

Recently, pre-trained language representation models such as bidirectional encoder representations from transformers (BERT) have been performing well in commonsense question answering (CSQA). However, there is a problem that the models do not directly use explicit information of knowledge sources existing outside. To augment this, additional methods such as

Yuzhou Chen, Tian Jiang, Miguel Heleno, Alexandre Moreira

Nowadays, it is broadly recognized in the power system community that to meet the ever expanding energy sector's needs, it is no longer possible to rely solely on physics-based models and that reliable, timely and sustainable operation of energy systems is impossible without systematic integration of artificial intelligence (AI) tools. Nevertheless, the adop

Adrian P. C. Lim

Let $\mathfrak{g}$ be the Lie Algebra of a compact semi-simple gauge group. For a $\mathfrak{g}$-valued 1-form $A$, consider the Yang-Mills action \begin{equation} S_{{\rm YM}}(A) = \int_{\mathbb{R}^4} \left|dA + A \wedge A \right|^2\ d\omega, \nonumber \end{equation} using the Euclidean metric on $T\mathbb{R}^4$. We want to make sense of the following path

Yong Zheng

In a recent comment by Fern\'{a}ndez, it has been argued that our solution method of an effective Hamiltonian based on the characteristic polynomial [Phys. Lett. A 443 (2022) 128215] had been developed several years earlier by Fried and Ezra [J. Chem. Phys. 90 (1989) 6378]. We show here several important differences between our treatment and the resummation

Weiwei Li, Ahmad Saleh, Manas Sharma, Marek Sierka

Organic semiconductors have attracted extensive attention due to their excellent optical and electronic properties. Here, we present an experimental and theoretical study of Brunel harmonic generation in two types of porphyrin thin films: tetraphenylporphyrin (TPP) and its organometallic complex derivative Zinc tetraphenylporphyrin (ZnTPP). Our results show

Keiji Oguiso

We give a counterexample of Morrison's cone conjecture for a strict Calabi-Yau threefold.

Z. Keszthelyi, A. de Koter, Y. Götberg, G. Meynet

Magnetism can greatly impact the evolution of stars. In some stars with OBA spectral types there is direct evidence via the Zeeman effect for stable, large-scale magnetospheres, which lead to the spin-down of the stellar surface and reduced mass loss. So far, a comprehensive grid of stellar structure and evolution models accounting for these effects was lack

Jahan C. Penny-Dimri, Christoph Bergmeir, Julian Smith

Most practical data science problems encounter missing data. A wide variety of solutions exist, each with strengths and weaknesses that depend upon the missingness-generating process. Here we develop a theoretical framework for training and inference using only observed variables enabling modeling of incomplete datasets without imputation. Using an informati

Amir Abboud, Karl Bringmann, Nick Fischer

The "short cycle removal" technique was recently introduced by Abboud, Bringmann, Khoury and Zamir (STOC '22) to prove fine-grained hardness of approximation. Its main technical result is that listing all triangles in an $n^{1/2}$-regular graph is $n^{2-o(1)}$-hard under the 3-SUM conjecture even when the number of short cycles is small; namely, when the num

Mario Hubert

The ontological models framework distinguishes $\psi$-ontic from $\psi$-epistemic wavefunctions. It is, in general, quite straightforward to categorize the wave-function of a certain quantum theory. Nevertheless, there has been a debate about the ontological status of the wave-function in the statistical interpretation of quantum mechanics: is it $\psi$-epis

Lirandë Pira, Chris Ferrie

Deep neural networks have established themselves as one of the most promising machine learning techniques. Training such models at large scales is often parallelized, giving rise to the concept of distributed deep learning. Distributed techniques are often employed in training large models or large datasets either out of necessity or simply for speed. Quantu

Pranjal Dutta, Fulvio Gesmundo, Christian Ikenmeyer, Gorav Jindal

According to Kumar's recent surprising result (ToCT'20), a small border Waring rank implies that the polynomial can be approximated as a sum of a constant and a small product of linear polynomials. We prove the converse of Kumar's result and establish a tight connection between border Waring rank and the model of computation in Kumar's result. In this way, w

Dasheng Wei

We produce a partial compactification of the variety given by P(t)=N_{K/k}(\mathbf z) whose Brauer group coincides with the unramified Brauer group, where K is an \'etale k-algebra and P(t)\in k[t] is a nonconstant polynomial. Then we obtain a systematic method to compute the unramified Brauer group for all such varieties.

Abey López-García, Alexander Tovbis

We consider several non-standard discrete and continuous Green energy problems in the complex plane and study the asymptotic relations between their solutions. In the discrete setting, we consider two problems; one with variable particle positions (within a given compact set) and variable particle masses, the other one with variable masses but prescribed pos

Adam Dejl, Harsh Deep, Jonathan Fei, Ardavan Saeedi

Sum-product networks (SPNs) have recently emerged as a novel deep learning architecture enabling highly efficient probabilistic inference. Since their introduction, SPNs have been applied to a wide range of data modalities and extended to time-sequence data. In this paper, we propose a general framework for modelling sequential treatment decision-making beha

Roman V. Bessonov, Sergey A. Denisov

We apply inverse spectral theory to study Sobolev norms of solutions to the nonlinear Schrodinger equation. For initial datum $q_0\in L^2(\mathbb{R})$ and $s\in [-1,0]$, we prove that there exists a conserved quantity that is equivalent to $H^s(\mathbb{R})$-norm of the solution.

Zhihao Li, Rebecca Tanzer-Gruener, Albert Presto, Peter Adams

A computational fluid dynamics (CFD) model that solves the steady-state Reynolds-Averaged Navier-Stokes (RANS) equations for buoyant compressible pollution dispersion under different meteorological conditions is developed. A 6.4 km by 6.4 km computational domain over a complex terrain with a height of 1 km above the ground surface is created. Meteorological

D. Dobie, J. Pritchard, Y. Wang, L. W. Graham

The Deeper, Wider, Faster (DWF) program coordinates observations with telescopes across the electromagnetic spectrum, searching for transients on timescales of milliseconds to days. The tenth DWF observing run was carried out in near real-time during September 2021 and consisted of six consecutive days of observations of the NGC 6744 galaxy group and a field

Ce Jin, Yinzhan Xu

Our work explores the hardness of $3$SUM instances without certain additive structures, and its applications. As our main technical result, we show that solving $3$SUM on a size-$n$ integer set that avoids solutions to $a+b=c+d$ for $\{a, b\} \ne \{c, d\}$ still requires $n^{2-o(1)}$ time, under the $3$SUM hypothesis. Such sets are called Sidon sets and are

Jing-Ling Chen, Xing-Yan Fan, Xiang-Ru Xie

The Aharonov-Bohm (AB) effect is an important discovery of quantum theory. It serves as a surprising quantum phenomenon in which an electrically charged particle can be affected by an electromagnetic potential, despite being confined to a region in which both the magnetic field and electric field are zero. This fact gives the electromagnetic potentials great

Grace Yang, Ming Cao, Lavender Y. Jiang, Xujin C. Liu

Traditional evaluation metrics for classification in natural language processing such as accuracy and area under the curve fail to differentiate between models with different predictive behaviors despite their similar performance metrics. We introduce sensitivity score, a metric that scrutinizes models' behaviors at the vocabulary level to provide insights i

Luca Galimberti, Helge Holden, Kenneth H. Karlsen, Peter H. C. Pang

We consider a nonlinear stochastic partial differential equation (SPDE) that takes the form of the Camassa--Holm equation perturbed by a convective, position-dependent, noise term. We establish the first global-in-time existence result for dissipative weak martingale solutions to this SPDE, with general finite-energy initial data. The solution is obtained as

Matthew Hampsey, Pieter van Goor, Robert Mahony

Accurate tracking of planned trajectories in the presence of perturbations is an important problem in control and robotics. Symmetry is a fundamental mathematical feature of many dynamical systems and exploiting this property offers the potential of improved tracking performance. In this paper, we investigate the tracking problem for systems on homogeneous s

Yi Wang, Nassim Ait Ali Braham, Zhitong Xiong, Chenying Liu

Self-supervised pre-training bears potential to generate expressive representations without human annotation. Most pre-training in Earth observation (EO) are based on ImageNet or medium-size, labeled remote sensing (RS) datasets. We share an unlabeled RS dataset SSL4EO-S12 (Self-Supervised Learning for Earth Observation - Sentinel-1/2) to assemble a large-sc

Surjyasish Mitra, Quoc Vo, Marcus Lin, Tuan Tran

From hydrogels and plastics to liquid crystals, soft solids cover a wide array of synthetic and biological materials that play key enabling roles in advanced technologies such as 3D printing, soft robotics, wearable electronics, self-assembly, and bioartificial tissues. Their elasticity and stimuli-induced changes in mechanical, optical, or electrical proper

Shyan Akmal, Nicole Wein

Amiri and Wargalla (2020) proved the following local-to-global theorem in directed acyclic graphs (DAGs): if $G$ is a weighted DAG such that for each subset $S$ of 3 nodes there is a shortest path containing every node in $S$, then there exists a pair $(s,t)$ of nodes such that there is a shortest $st$-path containing every node in $G$. We extend this theore

Serge Galam, Yuval Gefen, Yonathan Shapir

A new approach to the understanding of sociological collective behaviour, based on the framework of critical phenomena in physics, is presented. The first step consists of constructing a simple mean-behaviour model and applying it to a strike process in a plant. The model comprises only a limited number of parameters characteristic of the plant considered an

Adian Liusie, Vatsal Raina, Mark Gales

Recently it has been shown that without any access to the contextual passage, multiple choice reading comprehension (MCRC) systems are able to answer questions significantly better than random on average. These systems use their accumulated "world knowledge" to directly answer questions, rather than using information from the passage. This paper examines the

B. E. Zhilyaev, V. N. Petukhov, V. M. Reshetnyk

NASA commissioned a research team to study Unidentified Aerial Phenomena (UAP), observations of events that cannot scientifically be identified as known natural phenomena. The Main Astronomical Observatory of NAS of Ukraine conducts an independent study of UAP also. For UAP observations, we used two meteor stations installed in Kyiv and in the Vinarivka vill