November 2020 arXiv papers — page 23

Pritha Mondal, Subham Kumar Saha, Awadhesh Narayan, Anshu Pandey

We describe the process of electron condensation into a localized state in a structureless jellium that is coupled to a finite cavity. It is shown that there exists a temperature T_0 below which electrons within the jellium localize. This process is driven by enhancement of correlations between the electrons that are coupled to the cavity.

Ufuk Aydemir, Jing Ren

Primordial black holes have been considered as an attractive dark matter candidate, whereas some of the predictions heavily rely on the near-horizon physics that remains to be tested experimentally. As a concrete alternative, thermal 2-2-holes closely resemble black holes without event horizons. Being a probable endpoint of gravitational collapse, they not o

Josephine Seah

Brought into the public discourse through investigative work by journalists and scholars, awareness of algorithmic harms is at an all-time high. An increasing amount of research has been conducted under the banner of enhancing responsible artificial intelligence (AI), with the goal of addressing, alleviating, and eventually mitigating the harms brought on by

Yongming Huang, Shengheng Liu, Cheng Zhang, Xiaohu You

Future beyond fifth-generation (B5G) and sixth-generation (6G) mobile communications will shift from facilitating interpersonal communications to supporting Internet of Everything (IoE), where intelligent communications with full integration of big data and artificial intelligence (AI) will play an important role in improving network efficiency and providing

Yoshikazu Hagiwara, Cheng Zhang, Jian Zhou, Ya-jin Zhou

We study exclusive $\pi^+ \pi^-$ pair production near $\rho^0$ resonance peak in ultraperipheral heavy ion collisions. Pion pair can either be produced via two photon fusion process or from the decay of $\rho^0$ in photon-nuclear reaction. At very low pair transverse momentum, the electromagnetic and nuclear amplitudes become comparable. We show that the Cou

Serin Yang, Eung Yeop Kim, Jong Chul Ye

X-ray computed tomography (CT) uses different filter kernels to highlight different structures. Since the raw sinogram data is usually removed after the reconstruction, in case there are additional need for other types of kernel images that were not previously generated, the patient may need to be scanned again. Accordingly, there exists increasing demand fo

Wei Qu, Xiao-Yun Sun, Guan-Tie Deng

This paper concerns the study of reconstructing a function $f$ in the Hardy space of the unit disc $\D$ from intensity measurements $|f(z)|,\ z\in \D.$ It's known as the problem of phase retrieval. We transform it into solving the corresponding outer and inner function through the Nevanlinna factorization Theorem. The outer function will be established based

Ke Li, Shichong Peng, Kailas Vodrahalli, Jitendra Malik

In continual learning, new categories may be introduced over time, and an ideal learning system should perform well on both the original categories and the new categories. While deep neural nets have achieved resounding success in the classical supervised setting, they are known to forget about knowledge acquired in prior episodes of learning if the examples

Liang Lu, Naoyuki Kanda, Jinyu Li, Yifan Gong

End-to-end multi-talker speech recognition is an emerging research trend in the speech community due to its vast potential in applications such as conversation and meeting transcriptions. To the best of our knowledge, all existing research works are constrained in the offline scenario. In this work, we propose the Streaming Unmixing and Recognition Transduce

Peng Kang, Kui Cai, Xuan He, Shuangyang Li

In this paper, we propose a framework of the mutual information-maximizing (MIM) quantized decoding for low-density parity-check (LDPC) codes by using simple mappings and fixed-point additions. Our decoding method is generic in the sense that it can be applied to LDPC codes with arbitrary degree distributions, and can be implemented based on either the belie

Kal Backman, Dana Kulić, Hoam Chung

Unmanned aerial vehicles (UAVs) are often used for navigating dangerous terrains, however they are difficult to pilot. Due to complex input-output mapping schemes, limited perception, the complex system dynamics and the need to maintain a safe operation distance, novice pilots experience difficulties in performing safe landings in obstacle filled environment

Machiko Hatsuda, Shin Sasaki, Masaya Yata

We study the current algebras of the NS5-branes, the Kaluza-Klein (KK) five-branes and the exotic $5^2_2$-branes in type IIA/IIB superstring theories. Their worldvolume theories are governed by the six-dimensional $\mathcal{N}= (2,0)$ tensor and the $\mathcal{N} = (1,1)$ vector multiplets. We show that the current algebras are determined through the S- and T

Qijian Zhang, Runmin Cong, Chongyi Li, Ming-Ming Cheng

Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains an open and challenging problem. In this paper, we propose an end-to-end Dense Attention Fluid Network (DAFNet) for SOD in optical RSIs. A Global Context-aware Attention (GCA) modul

Matthew Otten, Keshav Kapoor, A. Barış Özgüler, Eric T. Holland

As larger, higher-quality quantum devices are built and demonstrated in quantum information applications, such as quantum computation and quantum communication, the need for high-quality quantum memories to store quantum states becomes ever more pressing. Future quantum devices likely will use a variety of physical hardware, some being used primarily for pro

P. Tuan-Anh, T. T. Thai, N. A. Tuan, P. Darriulat

Gravitational lensing of point sources located inside the lens caustic is known to produce four images in a configuration closely related to the source position. We study this relation in the particular case of a sample of quadruply-imaged quasars observed by the Hubble Space Telescope (HST). Strong correlations between the parameters defining the image conf

Neal Dalal, Jo Bovy, Lam Hui, Xinyu Li

We study how tidal streams from globular clusters may be used to constrain the mass of ultra-light dark matter particles, called `fuzzy' dark matter (FDM). A general feature of FDM models is the presence of ubiquitous density fluctuations in bound, virialized dark matter structures, on the scale of the de Broglie wavelength, arising from wave interference in

Weixin Huang, Huawei Liang, Linglong Lin, Zhiling Wang

Ground segmentation is an important preprocessing task for autonomous vehicles (AVs) with 3D LiDARs. To solve the problem of existing ground segmentation methods being very difficult to balance accuracy and computational complexity, a fast point cloud ground segmentation approach based on a coarse-to-fine Markov random field (MRF) method is proposed. The met

Ikuko Hamamoto

Using a simple model based on the knowledge of spherical and deformed Woods-Saxon potentials, it is shown that the recent observation of halo phenomena in $^{29}$F can be interpreted as an evidence for the prolate deformation of the ground state of $^{29}$F. The prolate deformation is the result of the shell structure, which is unique in one-neutron resonant

Mee Seong Im, Chun-Ju Lai, Arik Wilbert

We give an explicit description of the irreducible components of two-row Springer fibers for all classical types using cup diagrams. Cup diagrams can be used to label the irreducible components of two-row Springer fibers. Given a cup diagram, we explicitly write down all flags contained in the component associated to the cup diagram. This generalizes results

Yifan Gao, Henghui Zhu, Patrick Ng, Cicero Nogueira dos Santos

In open-domain question answering, questions are highly likely to be ambiguous because users may not know the scope of relevant topics when formulating them. Therefore, a system needs to find possible interpretations of the question, and predict one or multiple plausible answers. When multiple plausible answers are found, the system should rewrite the questi

Michel Bonnardeau

Eleven seasons, from 2004 to 2014, of photometric monitoring of the intermediate polar AO Psc are presented and are compared with previous observations. The spin up of the white dwarf is found to be slowing down. The amplitudes of the modulated and non-modulated components of the brightness are found to have undergone a major change in 2007.

Snehasish Bhattacharjee

In this work, we analyzed the effect of different prescriptions of the IR cutoffs, namely the Hubble horizon cutoff, particle horizon cutoff, Granda and Oliveros horizon cut off, and the Ricci horizon cutoff on the growth rate of clustering for the Tsallis holographic dark energy (THDE) model in an FRW universe devoid of any interactions between the dark Uni

Takashi Yoshizaki, Richard D. Ash, Marc D. Lipella, Tetsuya Yokoyama

Chondrites are sediments of materials left over from the earliest stage of the solar system history. Based on their undifferentiated nature and less fractionated chemical compositions, chondrites are widely considered to represent the unprocessed building blocks of the terrestrial planets and their embryos. Models of chemical composition of the terrestrial p

Jianan Lin

We consider the problem of locating a single facility for 2 agents in $L_p$ space ($1<p<\infty$) and give a nearly complete characterization of such deterministic strategyproof mechanisms. We use the distance between an agent and the facility in $L_p$ space to denote the cost of the agent. A mechanism is strategyproof iff no agent can reduce her cost from mi

Xiangqian Sun, Xing Yan, Qi Wu

We propose a multivariate generative model to capture the complex dependence structure often encountered in business and financial data. Our model features heterogeneous and asymmetric tail dependence between all pairs of individual dimensions while also allowing heterogeneity and asymmetry in the tails of the marginals. A significant merit of our model stru

Ahmad Saeed, Ebrahim Shahzad, Laeeq Aslam, Ijaz Mansoor Qureshi

The energy generation of a run of river hydropower plant depends upon the flow of river and the variations in the water flow makes the energy production unreliable. This problem is usually solved by constructing a small pond in front of the run of river hydropower plant. However, changes in water level of conventional single pond model results in sags, surge

Bhavana Burramukku

The amount of power generated by a wave farm depends on the Wave Energy Converter (WEC) arrangement along with the usual wave conditions. Therefore, forming the appropriate arrangement of WECs in an array is an important factor in maximizing power absorption. Data collected from the test sites is used to design a neural model for predicting wave farm's power

Lianzhang Bao

In this paper, we study pattern formations in an aggregation and diffusion cell migration model with Dirichlet boundary condition. The formal continuum limit of the model is a nonlinear parabolic equation with a diffusivity which can become negative if the cell density is small and spatial oscillations and aggregation occur in the numerical simulations. In t

H. B. Zeng

In this paper we consider relations between distributional chaos in a sequence with distributional chaos, w-chaos, R-T chaos, DC 3, respectively). We give a sufficient condition and prove that the distributional chaos is equivalent to the distributional chaos in a sequence under this condition. Besides, we get that distributional chaos in a sequence and w-ch

Haoran Xu, Fredrik Kjolstad

Fast compilation is important when compilation occurs at runtime, such as query compilers in modern database systems and WebAssembly virtual machines in modern browsers. We present copy-and-patch, an extremely fast compilation technique that also produces good quality code. It is capable of lowering both high-level languages and low-level bytecode programs t

Yichun Shi, Divyansh Aggarwal, Anil K. Jain

We propose a framework, called LiftedGAN, that disentangles and lifts a pre-trained StyleGAN2 for 3D-aware face generation. Our model is "3D-aware" in the sense that it is able to (1) disentangle the latent space of StyleGAN2 into texture, shape, viewpoint, lighting and (2) generate 3D components for rendering synthetic images. Unlike most previous methods,

Peng Gao, Liang Duan, Xian-Kun Yao, Zhan-Ying Yang

We propose a method to controllably generate six kinds of nonlinear waves on continuous waves, including the one- and multi-peak solitons, the Akhmediev, Kuznetsov-Ma, and Taijiri-Watanabe breathers, and stable periodic waves. In the nonlinear fiber system with third-order dispersion, we illustrate their generation conditions by the modified linear stability

Arnaud Brothier

In this second article, we continue to study classes of groups constructed from a functorial method due to Vaughan Jones. A key observation of the author shows that these groups have remarkable diagrammatic properties that can be used to deduce their properties. Given any group and two of its endomorphisms, we construct a semidirect product. In our first art

Qishan Wang, Shengbang Qian, Zhongtao Han, Xiaohui Fang

We improved the discless accretion models of Wynn \& King, considering the effects of the changing aspect due to the white dwarf spin and the variable feeding intensity caused by the asynchronism, and set up a more general spot model which is not sensitive to the different forms of these effects and can be applied for the period analysis of the optical and X

Georgi Marinov

Making a slight mistake during live music performance can easily be spotted by an astute listener, even if the performance is an improvisation or an unfamiliar piece. An example might be a highly dissonant chord played by mistake in a classical-era sonata, or a sudden off-key note in a recurring motif. The problem of identifying and correcting such errors ca

Jianxiong Chen, M. -C. Chu

We study the density profile of a dwarf halo in the decaying dark matter (DDM) cosmology, using a new algorithm that resolves halo density profiles down to the innermost $700$ pc robustly with high efficiency. Following Schwarzschild's orbit-based method, we have also developed a simplified model to calculate the DDM halo density profiles, which agree remark

Jeonghoon Park, Kyungmin Jo, Daehoon Gwak, Jimin Hong

We evaluate the out-of-distribution (OOD) detection performance of self-supervised learning (SSL) techniques with a new evaluation framework. Unlike the previous evaluation methods, the proposed framework adjusts the distance of OOD samples from the in-distribution samples. We evaluate an extensive combination of OOD detection algorithms on three different i

Yasuhisa Abe, David Boilley, Quentin Hourdillé, Caiwan Shen

A new framework is proposed for the study of collisions between very heavy ions which lead to the synthesis of Super-Heavy Elements (SHE), to address the fusion hindrance phenomenon. The dynamics of the reaction is studied in terms of collective degrees of freedom undergoing relaxation processes with different time scales. The Nakajima-Zwanzig projection ope

Xiaoxiao Long, Lingjie Liu, Wei Li, Christian Theobalt

We present a novel method for multi-view depth estimation from a single video, which is a critical task in various applications, such as perception, reconstruction and robot navigation. Although previous learning-based methods have demonstrated compelling results, most works estimate depth maps of individual video frames independently, without taking into co

Seung-Hwan Baek, Felix Heide

Active stereo cameras that recover depth from structured light captures have become a cornerstone sensor modality for 3D scene reconstruction and understanding tasks across application domains. Existing active stereo cameras project a pseudo-random dot pattern on object surfaces to extract disparity independently of object texture. Such hand-crafted patterns

Li Wei, Chongwen Huang, George C. Alexandropoulos, Zhaohui Yang

Reconfigurable Intelligent Surfaces (RISs) have been recently considered as an energy-efficient solution for future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Channel estimation and signal recovery in RISbased systems are among the most critical technical chal

Farhad Moghimifar, Afshin Rahimi, Mahsa Baktashmotlagh, Xue Li

Causal relationships form the basis for reasoning and decision-making in Artificial Intelligence systems. To exploit the large volume of textual data available today, the automatic discovery of causal relationships from text has emerged as a significant challenge in recent years. Existing approaches in this realm are limited to the extraction of low-level re

Mat Kelly, Jane Greenberg, Christopher B. Rauch, Sam Grabus

This paper presents a use case exploring the application of the Archival Resource Key (ARK) persistent identifier for promoting and maintaining ontologies. In particular, we look at improving computation with an in-house ontology server in the context of temporally aligned vocabularies. This effort demonstrates the utility of ARKs in preparing historical ont

Djoumbissie David Romain

We propose a unified multi-tasking framework to represent the complex and uncertain causal process of financial market dynamics, and then to predict the movement of any type of index with an application on the monthly direction of the S&P500 index. our solution is based on three main pillars: (i) the use of transfer learning to share knowledge and feature (r

Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone

Moving in complex environments is an essential capability of intelligent mobile robots. Decades of research and engineering have been dedicated to developing sophisticated navigation systems to move mobile robots from one point to another. Despite their overall success, a recently emerging research thrust is devoted to developing machine learning techniques

Rajesh Kumar, Md Zubair, Sudipto Mukherjee, Jacobo Antona Makoshi

Brain injuries are a major reason for mortality and morbidity following trauma in sports, work and traffic. Apart from the trauma at the site of impact (coup injury), other regions of the brain remote from the impact locations (non-coup) are commonly affected. We show that a screw theory-based method can be used to account for the combined effect of head rot

Emily Eckels, Ervin Gyori, Junsheng Liu, Sohaib Nasir

A tree $T$ on $2^n$ vertices is called set-sequential if the elements in $V(T)\cup E(T)$ can be labeled with distinct nonzero $(n+1)$-dimensional $01$-vectors such that the vector labeling each edge is the component-wise sum modulo $2$ of the labels of the endpoints. It has been conjectured that all trees on $2^n$ vertices with only odd degree are set-sequen

Tianxiao Liang, Zihan Zhang, Hao Song, Defang Duan

Lanthanum (La), the first member of the rare-earth elements, recently aroused strong interest due to its unique superhydride with superconducting properties. Although there is much theoretical and experimental work about phase transitions and superconductivity in metallic La, we got a new body-centred tetragonal ($bct$) phase in metallic La with space group

Youpeng Zhong, Hung-Shen Chang, Audrey Bienfait, Étienne Dumur

Quantum entanglement is a key resource for quantum computation and quantum communication \cite{Nielsen2010}. Scaling to large quantum communication or computation networks further requires the deterministic generation of multi-qubit entanglement \cite{Gottesman1999,Duan2001,Jiang2007}. The deterministic entanglement of two remote qubits has recently been dem

Myriam Hernández-Ketchul, Jesús Rodríguez-Viorato

We give a Python program that is capable to compute and print all the distinct trivalent 2-stratifold graphs up to $N$ white vertices with trivial fundamental group. Our algorithm uses the three basic operations to construct new graphs from any set of given graphs. We iterate this process to construct all the desired graphs. The algorithm includes an optimiz

Zexin Feng, Peixin Qin, Yali Yang, Han Yan

The coupling of optical and electronic degrees of freedom together with quantum confinement in low-dimensional electron systems is particularly interesting for achieving exotic functionalities in strongly correlated oxide electronics. Recently, high room-temperature mobility has been achieved for a large bandgap transparent oxide - BaSnO$_3$ upon extrinsic L

Aoxiao Zhong, Xiang Li, Dufan Wu, Hui Ren

In recent years, deep learning-based image analysis methods have been widely applied in computer-aided detection, diagnosis and prognosis, and has shown its value during the public health crisis of the novel coronavirus disease 2019 (COVID-19) pandemic. Chest radiograph (CXR) has been playing a crucial role in COVID-19 patient triaging, diagnosing and monito

Xionggui Tang, Yi Shen, Yanhua Xu

Optical centrifuge has emerged as a promising tool for achieving centrifuge motion of particles in many fields. Herein, we report a novel optical centrifuge, as driven by optical lateral force arising from transverse phase gradient of light in holographic optical tweezers. It has remarkable advantages, including rapid speed, small footprint, flexible design

Michael K. L. Man, Julien Madéo, Chakradhar Sahoo, Kaichen Xie

An exciton, a two-body composite quasiparticle formed of an electron and hole, is a fundamental optical excitation in condensed-matter systems. Since its discovery nearly a century ago, a measurement of the excitonic wavefunction has remained beyond experimental reach. Here, we directly image the excitonic wavefunction in reciprocal space by measuring the mo

Yingzhe Jia, Daizhan Cheng, Jun-e Feng

In this paper, the application of Ledley antecedence solutions in designing state feedback stabilizers of generic logic systems has been proposed. To make the method feasible, two modifications are made to the original Ledley antecedence solution theory: (i) the preassigned logical functions have been extended from being a set of equations to an admissible s

Peter Moeck

This book chapter reviews progress in crystallographic image processing (CIP) for scanning probe microscopy (SPM) that has occurred since our description of the technique was first put into open access in this book series in the year 2010. The signal to noise ratio in all kinds of experimental images of more or less regular 2D periodic arrays is significantl

Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

We study the problem of adaptively controlling a known discrete-time nonlinear system subject to unmodeled disturbances. We prove the first finite-time regret bounds for adaptive nonlinear control with matched uncertainty in the stochastic setting, showing that the regret suffered by certainty equivalence adaptive control, compared to an oracle controller wi

Zhaopeng Qiu, Xian Wu, Wei Fan

To assess the knowledge proficiency of a learner, multiple choice question is an efficient and widespread form in standard tests. However, the composition of the multiple choice question, especially the construction of distractors is quite challenging. The distractors are required to both incorrect and plausible enough to confuse the learners who did not mas

Majid Moghadam, Gabriel Hugh Elkaim

In this paper, we present a hierarchical framework for decision-making and planning on highway driving tasks. We utilized intelligent driving models (IDM and MOBIL) to generate long-term decisions based on the traffic situation flowing around the ego. The decisions both maximize ego performance while respecting other vehicles' objectives. Short-term trajecto

Majid Moghadam, Ali Alizadeh, Engin Tekin, Gabriel Hugh Elkaim

Tactical decision making and strategic motion planning for autonomous highway driving are challenging due to the complication of predicting other road users' behaviors, diversity of environments, and complexity of the traffic interactions. This paper presents a novel end-to-end continuous deep reinforcement learning approach towards autonomous cars' decision

Minji Yoon, Théophile Gervet, Bryan Hooi, Christos Faloutsos

Graph data is ubiquitous in academia and industry, from social networks to bioinformatics. The pervasiveness of graphs today has raised the demand for algorithms that can answer various questions: Which products would a user like to purchase given her order list? Which users are buying fake followers to increase their public reputation? Myriads of new graph

Shashi Raj Pandey, Kitae Kim, Madyan Alsenwi, Yan Kyaw Tun

In this letter, a novel framework to deliver critical spread out URLLC services deploying unmanned aerial vehicles (UAVs) in an out-of-coverage area is developed. To this end, the resource optimization problem, i.e., resource blocks (RBs) and power allocation, and optimal UAV deployment strategy are studied for UAV-assisted 5G networks to jointly maximize th

Sibo Qiao, Shanchen Pang, Gang Luo, Silin Pan

Echocardiography is a powerful prenatal examination tool for early diagnosis of fetal congenital heart diseases (CHDs). The four-chamber (FC) view is a crucial and easily accessible ultrasound (US) image among echocardiography images. Automatic analysis of FC views contributes significantly to the early diagnosis of CHDs. The first step to automatically anal

Shunsuke C. Furuya, Yusuke Horinouchi, Tsutomu Momoi

We discuss the ground-state degeneracy of spin-$1/2$ kagome-lattice quantum antiferromagnets on magnetization plateaus by employing two complementary methods: the adiabatic flux insertion in closed boundary conditions and a 't Hooft anomaly argument on inherent symmetries in a quasi-one-dimensional limit. The flux insertion with a tilted boundary condition r

Wen-Cong Chen

PSR J0636+5128 is a 2.87 ms binary millisecond pulsar (MSP) discovered by the Green Bank Northern Celestial Cap Pulsar Survey, and possesses the third shortest orbital period ($P=1.6$ hour) among confirmed binary pulsars. Recent observations reported that this source is experiencing a rapid orbital expansion at a rate of $\dot{P}=(1.89\pm0.05)\times 10^{-12}

Jungtaek Kim, Seungjin Choi, Minsu Cho

Bayesian optimization is a popular method for solving the problem of global optimization of an expensive-to-evaluate black-box function. It relies on a probabilistic surrogate model of the objective function, upon which an acquisition function is built to determine where next to evaluate the objective function. In general, Bayesian optimization with Gaussian

Sanghwa Lee, Jaeyoung Lee, Ichiro Hasuo

Prioritized experience replay (PER) samples important transitions, rather than uniformly, to improve the performance of a deep reinforcement learning agent. We claim that such prioritization has to be balanced with sample diversity for making the DQN stabilized and preventing forgetting. Our proposed improvement over PER, called Predictive PER (PPER), takes

Yingqiu Mao, Pei Zeng, Teng-Yun Chen

A crucial goal for quantum key distribution (QKD) is to transmit unconditionally secure keys over long distances. Previous studies show that the key rate of point-to-point QKD is limited by a secret key rate capacity bound, and higher key rates would require quantum repeaters. In 2018, the seminal twin-field (TF) QKD protocol was proposed to provide a remark

Kiran Sharma

Misconduct accounts for the majority of retracted scientific publications and this database reveals the disturbing trend in science~\citep{fang2012misconduct, brainard2018massive}. The objective of the study is to find the association among the authors' collaboration, the number of retracted papers, the number of retracted citations, journal impact factor, a

Jian Luo, Jianzong Wang, Ning Cheng, Guilin Jiang

In this paper, we propose an end-to-end speech recognition network based on Nvidia's previous QuartzNet model. We try to promote the model performance, and design three components: (1) Multi-Resolution Convolution Module, replaces the original 1D time-channel separable convolution with multi-stream convolutions. Each stream has a unique dilated stride on con

Hui Wei

A conceptual system with rich connotation is key to improving the performance of knowledge-based artificial intelligence systems. While a conceptual system, which has abundant concepts and rich semantic relationships, and is developable, evolvable, and adaptable to multi-task environments, its actual construction is not only one of the major challenges of kn

Qishan Wang, Shengbang Qian, Liying Zhu

As the only eclipsing asynchronous polar (AP), V1432 Aql provides an excellent laboratory to study the interaction between the accreted matter and the magnetic field. However, due to its complex emission, a more physical understanding of its accretion geometry is still outstanding. Here, we report an X-ray spectral study using contemporaneous observations fr

Alicia Y. Tsai, Selim Gunay, Minjune Hwang, Pengyuan Zhai

Post-hazard reconnaissance for natural disasters (e.g., earthquakes) is important for understanding the performance of the built environment, speeding up the recovery, enhancing resilience and making informed decisions related to current and future hazards. Natural language processing (NLP) is used in this study for the purposes of increasing the accuracy an

Takashi Shiroto, Akinobu Matsuyama, Nobuyuki Aiba, Masatoshi Yagi

Structure-preserving discretization of the Rosenbluth-Fokker-Planck equation is still an open question especially for unlike-particle collision. In this paper, a mass-energy-conserving isotropic Rosenbluth-Fokker-Planck scheme is introduced. The structure related to the energy conservation is skew-symmetry in mathematical sense, and the action-reaction law i

Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos

Given a dynamic graph stream, how can we detect the sudden appearance of anomalous patterns, such as link spam, follower boosting, or denial of service attacks? Additionally, can we categorize the types of anomalies that occur in practice, and theoretically analyze the anomalous signs arising from each type? In this work, we propose AnomRank, an online algor

Zhengqi Li, Simon Niklaus, Noah Snavely, Oliver Wang

We present a method to perform novel view and time synthesis of dynamic scenes, requiring only a monocular video with known camera poses as input. To do this, we introduce Neural Scene Flow Fields, a new representation that models the dynamic scene as a time-variant continuous function of appearance, geometry, and 3D scene motion. Our representation is optim

Benjamin Seiyon Lee, Jaewoo Park

Nonstationary non-Gaussian spatial data are common in many disciplines, including climate science, ecology, epidemiology, and social sciences. Examples include count data on disease incidence and binary satellite data on cloud mask (cloud/no-cloud). Modeling such datasets as stationary spatial processes can be unrealistic since they are collected over large

Parviz Khaledian, Armin Aligholian, Hamed Mohsenian-Rad

Solar distribution feeders are commonly used in solar farms that are integrated into distribution substations. In this paper, we focus on a real-world solar distribution feeder and conduct an event-based analysis by using micro-PMU measurements. The solar distribution feeder of interest is a behind-the-meter solar farm with a generation capacity of over 4 MW

Christopher C. Herrmann, Joseph Croman, Sergey V. Baryshev

Diamond holds promise to reshape ultrafast and high power electronics. One such solid-state device is the diode avalanche shaper (DAS), which functions as an ultrafast closing switch where closing is caused by the formation of the streamer traversing the diode much faster than 10$^7$ cm/s. One of the most prominent applications of DAS is in ultrawide band (U

Bolin Pan, Simon R. Arridge, Felix Lucka, Ben T. Cox

Curvelet frame is of special significance for photoacoustic tomography (PAT) due to its sparsifying and microlocalisation properties. We derive a one-to-one map between wavefront directions in image and data spaces in PAT which suggests near equivalence between the recovery of the initial pressure and PAT data from compressed/subsampled measurements when ass

Fnu Shilpika, Takanori Fujiwara, Naohisa Sakamoto, Jorji Nonaka

Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional, consisting of curves varying over a continuum (e.g., time). When analyzing continuous data, functional data analysis (FDA) provides substantial benefits, such as the ability to study the derivatives and to restrict the ordering of data. However, conti

Ignacio Ferrin, Vincenzo Orofino

Using the Secular Light Curve (SLC) formalism (Ferr\'in, 2010), we have catalogued 88 probable members of the Taurid Complex (TC). 51 of them have useful SLCs and 34 of these (67%) exhibit cometary activity. This high percentage of active asteroids gives support to the hypothesis of a catastrophe that took place during the Upper Paleolithic (Clube and Napier

Jordan Trinka, Hossein Haghbin, Mehdi Maadooliat

In this paper, we propose two nonparametric methods used in the forecasting of functional time-dependent data, namely functional singular spectrum analysis recurrent forecasting and vector forecasting. Both algorithms utilize the results of functional singular spectrum analysis and past observations in order to predict future data points where recurrent fore

Or Litany, Emanuele Rodolà, Alex Bronstein, Michael Bronstein

Shape correspondence is a fundamental problem in computer graphics and vision, with applications in various problems including animation, texture mapping, robotic vision, medical imaging, archaeology and many more. In settings where the shapes are allowed to undergo non-rigid deformations and only partial views are available, the problem becomes very challen

Haoxin Wang, BaekGyu Kim, Jiang Xie, Zhu Han

Applying deep learning to object detection provides the capability to accurately detect and classify complex objects in the real world. However, currently, few mobile applications use deep learning because such technology is computation-intensive and energy-consuming. This paper, to the best of our knowledge, presents the first detailed experimental study of

Peng Zhou, Lingxi Xie, Bingbing Ni, Cong Geng

The conditional generative adversarial network (cGAN) is a powerful tool of generating high-quality images, but existing approaches mostly suffer unsatisfying performance or the risk of mode collapse. This paper presents Omni-GAN, a variant of cGAN that reveals the devil in designing a proper discriminator for training the model. The key is to ensure that th

Rafael Lima

Hawkes Processes are a type of point process which models self-excitement among time events. It has been used in a myriad of applications, ranging from finance and earthquakes to crime rates and social network activity analysis.Recently, a surge of different tools and algorithms have showed their way up to top-tier Machine Learning conferences. This work aim

Marijana Butorac, Slaven Kožić

By using the ideas of Feigin and Stoyanovsky and Calinescu, Lepowsky and Milas we introduce and study the principal subspaces associated with the Etingof-Kazhdan quantum affine vertex algebra of integer level $k\geqslant 1$ and type $A_1^{(1)}$. We show that the principal subspaces possess the quantum vertex algebra structure, which turns to the usual vertex

Yicong Hong, Qi Wu, Yuankai Qi, Cristian Rodriguez-Opazo

Accuracy of many visiolinguistic tasks has benefited significantly from the application of vision-and-language(V&L) BERT. However, its application for the task of vision-and-language navigation (VLN) remains limited. One reason for this is the difficulty adapting the BERT architecture to the partially observable Markov decision process present in VLN, requir

N. C. Shrikanth, Suvodeep Majumder, Tim Menzies

Many researchers assume that, for software analytics, "more data is better." We write to show that, at least for learning defect predictors, this may not be true. To demonstrate this, we analyzed hundreds of popular GitHub projects. These projects ran for 84 months and contained 3,728 commits (median values). Across these projects, most of the defects occur

Jordan Mitchell Barrett

As the prototypical category, $\mathbf{Set}$ has many properties which make it special amongst categories. From the point of view of mathematical logic, one such property is that $\mathbf{Set}$ has enough structure to "properly" formalise logic. However, we could ask what it might mean to formalise logic in another category $\mathbf{C}$. The notion of an (el

Maxence Cassier, Trent DeGiovanni, Sébastien Guenneau, Fernando Guevara Vasquez

We present an active cloaking method for the parabolic heat (and mass or light diffusion) equation that can hide both objects and sources. By active we mean that it relies on designing monopole and dipole heat source distributions on the boundary of the region to be cloaked. The same technique can be used to make a source or an object look like a different o

Patrick Moss, Tom Ward

An integer sequence is called realizable if it is the count of periodic points of some map. The Fibonacci sequence $(F_n)$ does not have this property, and the Fibonacci sequence sampled along the squares $(F_{n^2})$ also does not have this property. We prove that this is an arithmetic phenomenon related to the discriminant of the Fibonacci sequence, by show

Ilyas Bayramov

The question of convergence of iterated integrals on Riemann surfaces goes back to Bloch, Levin, and Zagier, who have proved this fact for various iterated integrals in the context of elliptic curves. In this work, I prove the convergence of the iterated integral defining Bloch-Wigner function on higher genus curves, utilizing some novel results of Hou in th

Yixiong Chen, Chunhui Zhang, Li Liu, Cheng Feng

Most deep neural networks (DNNs) based ultrasound (US) medical image analysis models use pretrained backbones (e.g., ImageNet) for better model generalization. However, the domain gap between natural and medical images causes an inevitable performance bottleneck. To alleviate this problem, an US dataset named US-4 is constructed for direct pretraining on the

Elio Marconi

We study the fine properties of a class of weak solutions $u$ of the eikonal equation arising as asymptotic domain of a family of energy functionals introduced in (Rivi\`ere T, Serfaty S. Limiting domain wall energy for a problem related to micromagnetics. Comm Pure Appl Math 2001; 54(3):294-338). In particular we prove that the entropy defect measure associ

N. V. Rastegaev

Spectral asymptotics of the Sturm-Liouville problem with an arithmetically self-similar singular weight is considered. Previous results by A. A. Vladimirov and I. A. Sheipak, and also by the author, rely on the spectral periodicity property, which imposes significant restrictions on the self-similarity parameters of the weight. This work introduces a new met

Ion Victor Gosea, Dimitrios S. Karachalios, Athanasios C. Antoulas

In this paper, we address an extension of the Loewner framework for learning quadratic control systems from input-output data. The proposed method first constructs a reduced-order linear model from measurements of the classical transfer function. Then, this surrogate model is enhanced by incorporating a term that depends quadratically on the state. More prec

Hao-Chung Cheng, Andreas Winter, Nengkun Yu

We study quantum hypothesis testing between orthogonal states under restricted local measurements in the many-copy scenario. For testing arbitrary multipartite entangled pure state against its orthogonal complement state via the local operation and classical communication (LOCC) operation, we prove that the optimal average error probability always decays exp

Nao Tokui

Since the introduction of deep learning, researchers have proposed content generation systems using deep learning and proved that they are competent to generate convincing content and artistic output, including music. However, one can argue that these deep learning-based systems imitate and reproduce the patterns inherent within what humans have created, ins