July 2022 arXiv papers — page 98

Pallavi Sinha, Irinel-Constantin Morărescu, Sukumar Srikant

The study proposes new results on the set input-to-state stability (ISS) subject to a small input time delay for compact, invariant sets that contains the origin. First, using the nonlinear small-gain theory, we prove a Razumikhin-type theorem that ensures ISS for sets in the setup of functional differential equations (FDEs) with disturbances. Next we show h

Justin Engelmann, Ana Villaplana-Velasco, Amos Storkey, Miguel O. Bernabeu

A retinal trait, or phenotype, summarises a specific aspect of a retinal image in a single number. This can then be used for further analyses, e.g. with statistical methods. However, reducing an aspect of a complex image to a single, meaningful number is challenging. Thus, methods for calculating retinal traits tend to be complex, multi-step pipelines that c

Nicolas Michel, Romain Negrel, Giovanni Chierchia, Jean-François Bercher

We study Online Continual Learning with missing labels and propose SemiCon, a new contrastive loss designed for partly labeled data. We demonstrate its efficiency by devising a memory-based method trained on an unlabeled data stream, where every data added to memory is labeled using an oracle. Our approach outperforms existing semi-supervised methods when fe

Yunnuo Xu, Yijie Mao, Onur Dizdar, Bruno Clerckx

Rate-Splitting Multiple Access (RSMA) has emerged as a flexible and powerful framework for wireless networks. In this paper, we investigate the user fairness of downlink multi-antenna RSMA in short-packet communications with/without cooperative (user-relaying) transmission. We design optimal time allocation and linear precoders that maximize the Max-Min Fair

Zejun Zhang, Zhenchang Xing, Xin Xia, Xiwei Xu

Compared to other programming languages (e.g., Java), Python has more idioms to make Python code concise and efficient. Although pythonic idioms are well accepted in the Python community, Python programmers are often faced with many challenges in using them, for example, being unaware of certain pythonic idioms or do not know how to use them properly. Based

Thomas Ayral, Thibaud Louvet, Yiqing Zhou, Cyprien Lambert

We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of time-dependent DMRG from the usual situation of hermitian Hamiltonian matrices to quantum circuits defined by unitary matrices. For small circuit depths, the technique is exact and equivalent to other matri

Xianxin Song, Jie Xu, Fan Liu, Tony Xiao Han

This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is dedicatedly deployed to assist an access point (AP) to sense a target at its NLoS region. It is assumed that the AP is equipped with multiple antennas and the IRS is equipped with a uniform linear array. We consider two types of

Steven Obua

Abstraction logic is a new logic, serving as a foundation of mathematics. It combines features of both predicate logic and higher-order logic: abstraction logic can be viewed both as higher-order logic minus static types as well as predicate logic plus operators and variable binding. We argue that abstraction logic is the best foundational logic possible bec

Prerna Rana, A. Mangalam

We study the bound orbit conditions for equatorial and eccentric orbits around a Kerr black hole both in the parameter space ($E$, $L$, $a$) representing the energy, angular momentum of the test particle, and spin of the black hole, and also ($e$, $\mu$, $a$) space representing the eccentricity, inverse-latus rectum of the orbit, and spin. We apply these con

Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan

Recent works have shown how the reasoning capabilities of Large Language Models (LLMs) can be applied to domains beyond natural language processing, such as planning and interaction for robots. These embodied problems require an agent to understand many semantic aspects of the world: the repertoire of skills available, how these skills influence the world, a

Yaiza Canzani, John A. Toth

Let $(M,g)$ be a compact, smooth Riemannian manifold and $\{u_h\}$ be a sequence of $L^2$-normalized Laplace eigenfunctions that has a localized defect measure $\mu$ in the sense that $ M \setminus \text{supp}(\pi_* \mu) \neq \emptyset$ where $\pi:T^*M \to M$ is the canonical projection. Using Carleman estimates we prove that for any real-smooth closed hyper

Anton A. Kulbakov, Elaheh Sadrollahi, Florian Rasch, Maxim Avdeev

In frustrated magnetic systems, the competition amongst interactions can introduce extremely high degeneracy and prevent the system from readily selecting a unique ground state. In such cases, the magnetic order is often exquisitely sensitive to the balance among the interactions, allowing tuning among novel magnetically ordered phases. In antlerite, Cu$_3$S

Tian Ye, Sixiang Chen, Yun Liu, Yi Ye

In winter scenes, the degradation of images taken under snow can be pretty complex, where the spatial distribution of snowy degradation is varied from image to image. Recent methods adopt deep neural networks to directly recover clean scenes from snowy images. However, due to the paradox caused by the variation of complex snowy degradation, achieving reliabl

Vincenzo Petrone, Enrico Ferrentino, Pasquale Chiacchio

Optimal motion planning along prescribed paths can be solved with several techniques, but most of them do not take into account the wrenches exerted by the end-effector when in contact with the environment. When a dynamic model of the environment is not available, no consolidated methodology exists to consider the effect of the interaction. Regardless of the

Dulip Madurasinghe, Ganesh K. Venayagamoorthy

Power system transmission network topology is utilized in energy management system applications. Substation configurations are fundamental to transmission network topology processing. Modern power systems consisting of renewable energy sources require reliable and fast network topology processing due to the variable nature of wind and solar power plants. Cur

Benjamin Carlson, Quincy Bayer, Tae Min Hong, Stephen Roche

We present a novel application of the machine learning / artificial intelligence method called boosted decision trees to estimate physical quantities on field programmable gate arrays (FPGA). The software package fwXmachina features a new architecture called parallel decision paths that allows for deep decision trees with arbitrary number of input variables.

C. E. DeForest, C. Lowder, D. B. Seaton, M. J. West

We report on a particular example of noise and data representation interacting to introduce systematic error. Many instruments collect integer digitized values and appy nonlinear coding, in particular square-root coding, to compress the data for transfer or downlink; this can introduce surprising systematic errors when they are decoded for analysis. Square r

Yang Wang, Nicola R. Napolitano, Weiguang Cui, Xiao-Dong Li

The star formation history (SFH) of galaxies is critical for understanding galaxy evolution. Hydrodynamical simulations enable us to precisely reconstruct the SFH of galaxies and establish a link to the underlying physical processes. In this work, we present a model to describe individual galaxies' SFHs from three simulations: TheThreeHundred, Illustris-1 an

Eric Gottlieb, Matjaž Krnc, Peter Muršič

Given an integer partition of $n$, we consider the impartial combinatorial game LCTR in which moves consist of removing either the left column or top row of its Young diagram. We show that for both normal and mis\`ere play, the optimal strategy can consist mostly of mirroring the opponent's moves. We also establish that both LCTR and Downright are domestic a

Xiaohuang Hu, Jialun Ping

Inspired by the updated information on $\Omega(2012)$ by the Belle Collaboration, we conduct a study of all possible $S$-wave pentaquark systems with quark contents $sssq\bar{q},q=u,d$ in a chiral quark model with the help of Gaussian expansion method. Channel coupling is also considered. The real-scaling method (stabilization method) is employed to identify

Mengmeng Song, Yong Xia, Jinyang Zheng

The trust region subproblem (TRS) is to minimize a possibly nonconvex quadratic function over a Euclidean ball. There are typically two cases for (TRS), the so-called ``easy case'' and ``hard case''. Even in the ``easy case'', the sequence generated by the classical projected gradient method (PG) may converge to a saddle point at a sublinear local rate, when

P. Androvitsaneas, A. B. Young, T. Nutz, J. M. Lennon

The interaction of quantum objects lies at the heart of fundamental quantum physics and is key to a wide range of quantum information technologies. Photon-quantum-emitter interactions are among the most widely studied. Two-qubit interactions are generally simplified into two quantum objects in static well-defined states . In this work we explore a fundamenta

Xiaofeng Wang, James Daniel Brandenburg, Lijuan Ruan, Fenglan Shao

The collision energy dependence of the cross section and the transverse momentum distribution of dielectrons from the Breit-Wheeler process in heavy-ion collisions are computed in the lowest-order QED and found to be sensitive to the nuclear charge distribution and the infrared-divergence of the ultra-Lorentz boosted Coulomb field. Within a given experimenta

Prerna Rana, A. Mangalam

We derive the conditions for a non-equatorial eccentric bound orbit to exist around a Kerr black hole in two-parameter spaces: the energy, angular momentum of the test particle, spin of the black hole, and Carter's constant space ($E$, $L$, $a$, $Q$), and eccentricity, inverse-latus rectum space ($e$, $\mu$, $a$, $Q$). These conditions distribute various kin

Simone Di Cataldo, Lilia Boeri

The extreme pressures required to stabilize the recently discovered superhydrides represent a major obstacle to their practical application. In this paper, we propose a novel route to attain high-temperature superconductivity in hydrides at ambient pressure, by doping commercial metal borohydrides. Using first-principles calculations based on Density Functio

Manjul Bhargava, Arul Shankar, Xiaoheng Wang

We determine the density of integral binary forms of given degree that have squarefree discriminant, proving for the first time that the lower density is positive. Furthermore, we determine the density of integral binary forms that cut out maximal orders in number fields. The latter proves, in particular, an ``arithmetic Bertini theorem'' conjectured by Poon

A. M. S. Richards, E. Moravec, S. Etoka, E. B. Fomalont

This manual is intended to help ALMA and other interferometer users improve images by recognising limitations and how to overcome them and deciding when and how to use self-calibration. The images provided by the ALMA Science Archive are calibrated using standard observing and data processing routines, including a quality assurance process to make sure that

Nikolaos Ploskas, Kostas Stergiou

The p-median problem concerns the location of facilities so that the sum of distances between the demand points and their nearest facility is minimized. We study a variant of this classic location problem where minimum distance constraints exist both between the facilities and between the facilities and the demand points. This specific type of problem can be

Jonna C. Roden, Rory D. Mills-Williams, John W. Pearson, Benjamin D. Goddard

A numerical framework is developed to solve various types of PDEs on complicated domains, including steady and time-dependent, non-linear and non-local PDEs, with different boundary conditions that can also include non-linear and non-local terms. This numerical framework, called MultiShape, is a class in Matlab, and the software is open source. We demonstrat

Liren Yang

Event camera is a novel bio-inspired vision sensor that outputs event stream. In this paper, we propose a novel data fusion algorithm called EAS to fuse conventional intensity images with the event stream. The fusion result is applied to some ego-motion estimation frameworks, and is evaluated on a public dataset acquired in dim scenes. In our 3-DoF rotation

Alexandre Eremenko, Changfeng Gui, Qinfeng Li, Lu Xu

We give a complete classification of solutions bounded from above of the Liouville equation $$-\Delta u=e^{2u}\quad\mbox{in}\quad {\mathbf{R}}^2.$$ More generally, solutions in the class $$N:=\{ u:\limsup_{z\to\infty} u(z)/\log|z|:=k(u)<\infty\}$$ are described. As a consequence, we obtain five rigidity results. First, $k(u)$ can take only a discrete set of

Minh Tam, George Thomas, Dmitry S. Golubev

Superconducting circuits provide a favorable platform for quantum thermodynamic experiments. An important component for such experiments is a heat valve, i.e. a device which allows one to control the heat power flowing through the system. Here we theoretically study the heat valve based on a superconducting quantum interference device (SQUID) coupled to two

Nuno Freitas, Filip Najman

This note proves two theorems regarding Fermat-type equation $x^r + y^r = dz^p$ where $r \geq 5$ is a prime. Our main result shows that, for infinitely many integers~$d$, the previous equation has no non-trivial primitive solutions such that $2 \mid x+y$ or $r \mid x+y$, for a set of exponents $p$ of positive density. We use the modular method with a symplec

Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang

Learning dynamic user preference has become an increasingly important component for many online platforms (e.g., video-sharing sites, e-commerce systems) to make sequential recommendations. Previous works have made many efforts to model item-item transitions over user interaction sequences, based on various architectures, e.g., recurrent neural networks and

P. Wiseman, M. Vincenzi, M. Sullivan, L. Kelsey

Type Ia supernovae (SNe Ia) are used as standardisable candles to measure cosmological distances, but differences remain in their corrected luminosities which display a magnitude step as a function of host galaxy properties such as stellar mass and rest-frame $U-R$ colour. Identifying the cause of these steps is key to cosmological analyses and provides insi

Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj

Achieving at least some level of explainability requires complex analyses for many machine learning systems, such as common black-box models. We recently proposed a new rule-based learning system, SupRB, to construct compact, interpretable and transparent models by utilizing separate optimizers for the model selection tasks concerning rule discovery and rule

Yohei Onuki, Sylvain Joubaud, Thierry Dauxois

A gradient-wind balanced flow with an elliptic streamline parametrically excites internal inertia-gravity waves through ageostrophic anticyclonic instability (AAI). This study numerically investigates the breaking of internal waves and the following turbulence generation resulting from the AAI. In our simulation, we periodically distort the calculation domai

Xiang Li, Jinglu Wang, Xiaohao Xu, Bhiksha Raj

Video instance segmentation (VIS) aims at classifying, segmenting and tracking object instances in video sequences. Recent transformer-based neural networks have demonstrated their powerful capability of modeling spatio-temporal correlations for the VIS task. Relying on video- or clip-level input, they suffer from high latency and computational cost. We prop

Lin Shi, Fangwen Mu, Xiao Chen, Song Wang

Code summarization, the task of generating useful comments given the code, has long been of interest. Most of the existing code summarization models are trained and validated on widely-used code comment benchmark datasets. However, little is known about the quality of the benchmark datasets built from real-world projects. Are the benchmark datasets as good a

Guido Bell, Kevin Brune, Goutam Das, Marcel Wald

We consider the quark beam function that describes collinear initial-state radiation that is constrained by a veto on reconstructed jets. As the veto is imposed on the transverse momenta of the jets, the beam function is subject to rapidity divergences, and we use the collinear-anomaly framework to extract the perturbative matching kernels to next-to-next-to

Niki Maria Foteinopoulou, Ioannis Patras

Human affect and mental state estimation in an automated manner, face a number of difficulties, including learning from labels with poor or no temporal resolution, learning from few datasets with little data (often due to confidentiality constraints) and, (very) long, in-the-wild videos. For these reasons, deep learning methodologies tend to overfit, that is

Xizhi Liu, Oleg Pikhurko

Grosu [On the algebraic and topological structure of the set of Tur\'{a}n densities. \emph{J. Combin. Theory Ser. B} \textbf{118} (2016) 137--185] asked if there exist an integer $r\ge 3$ and a finite family of $r$-graphs whose Tur\'{a}n density, as a real number, has (algebraic) degree greater than~$r-1$. In this note we show that, for all integers $r\ge 3$

M. A. Kenworthy, D. González Picos, E. Elizondo, R. G. Martin

A deep (~70%) and extended (~150 days) eclipse was seen towards the young multiple stellar system V773 Tau in 2010. We interpret it as due to the passage of a circumbinary disk around the B components moving in front of the A components. Our aim is to characterise the orientation and structure of the disk, to refine the orbits of the subcomponents, and to pr

Xin Zhang, Kai Deng, Qing Mai

Envelope methods offer targeted dimension reduction for various models. The overarching goal is to improve efficiency in multivariate parameter estimation by projecting the data onto a lower-dimensional subspace known as the envelope. Envelope approaches have advantages in analyzing data with highly correlated variables, but their iterative Grassmannian opti

Niccolò Bucciantini, Riccardo Ferrazzoli, Matteo Bachetti, John Rankin

The Crab pulsar and its nebula are among the most studied astrophysical systems, and constitute one of the most promising environments where high energy processes and particle acceleration can be investigated. They are the only objects for which previous X-ray polarisation has been reported. We present here the first Imaging X-ray Polarimetry Explorer (IXPE)

Gabriel Picavet, Martine Picavet-L'Hermitte

We are dealing with extensions of commutative rings $R\subseteq S$ whose chains of the poset $[R,S]$ of their subextensions are finite ({\em i.e.} $R\subseteq S$ has the FCP property) and such that $[R,S]$ is a distributive lattice, that we call distributive FCP extensions. Note that the lattice $[R,S]$ of a distributive FCP extension is finite. This paper i

Till Domröse, Thomas Danz, Sophie F. Schaible, Kai Rossnagel

The tunability of materials properties by light promises a wealth of future applications in energy conversion and information technology. Strongly correlated materials such as transition-metal dichalcogenides (TMDCs) offer optical control of electronic phases, charge ordering and interlayer correlations by photodoping. Here, we find the emergence of a transi

Christopher Wyenberg, Fereshteh Rajabi, Martin Houde

We construct a model of cooperative superradiant emission from a highly relativistic multi-particle source. We revise an existing model of the literature for a relativistic two-level particle, and construct from it a Hamiltonian describing relativistic velocity dependent multi-particle superradiance. We adapt the standard diagrammatic framework to compute ti

Jacob B Khurgin

I present a simple view of nonlinear optcal phenomena as being determined mostly by the length of interaction time between photons and matter. This may explain why in the last decades the progress in developing better nonlinear materials has not been as rapid as wished. A few tentative routes towards possible improvements in the efficiency of nonlinear optic

Regina Finsterhoelzl, Guido Burkard

We evaluate the performance of small error-correcting codes, which we tailor to hardware platforms of very different connectivity and coherence: on a superconducting processor based on transmon qubits and a spintronic quantum register consisting of a nitrogen-vacancy center in diamond. Taking the hardware-specific errors and connectivity into account, we inv

Fei Gao, Xinyi Xie, Hui Zhan

For the nonlinear stochastic partial differential equation which is driven by multiplicative noise of the form \[D_t^\beta u = \left[ { - {{\left( { - \Delta } \right)}^s}u + \zeta \left( u \right)} \right]dt + A\sum\limits_{m \in Z_0^d} {\sum\limits_{j = 1}^{d - 1} {{\theta _m}{\sigma _{m,j}}\left( x \right)} } \circ dW_t^{m,j},\;\; s \ge 1,\;\;\frac{1}{2}

Isha Hameed, Samuel Sharpe, Daniel Barcklow, Justin Au-Yeung

Explainable artificial intelligence (XAI) methods lack ground truth. In its place, method developers have relied on axioms to determine desirable properties for their explanations' behavior. For high stakes uses of machine learning that require explainability, it is not sufficient to rely on axioms as the implementation, or its usage, can fail to live up to

Shuai Huo, Dong Liu, Li Li, Siwei Ma

Video coding is a mathematical optimization problem of rate and distortion essentially. To solve this complex optimization problem, two popular video coding frameworks have been developed: block-based hybrid video coding and end-to-end learned video coding. If we rethink video coding from the perspective of optimization, we find that the existing two framewo

Lluís Alemany-Puig, Ramon Ferrer-i-Cancho

Dependency trees have proven to be a very successful model to represent the syntactic structure of sentences of human languages. In these structures, vertices are words and edges connect syntactically-dependent words. The tendency of these dependencies to be short has been demonstrated using random baselines for the sum of the lengths of the edges or its var

Akinkunle Akinola, Akoh Atadoga, Kimberlyn Brooks, Vibhuti Chandna

Cumulative COVID-19 case counts by county in Ohio were gathered and combined with population data from the Census Bureau and student enrollment by county from the Integrated Postsecondary Education Data System (IPEDS) for colleges or universities that compete in NCAA sports. Monthly median percent increases, monthly average percent increases, and average cas

Alexander Heinlein, Kathrin Smetana

Two-level domain decomposition preconditioners lead to fast convergence and scalability of iterative solvers. However, for highly heterogeneous problems, where the coefficient function is varying rapidly on several possibly non-separated scales, the condition number of the preconditioned system generally depends on the contrast of the coefficient function le

Tao Huang, Lang Huang, Shan You, Fei Wang

Vision transformers (ViTs) are usually considered to be less light-weight than convolutional neural networks (CNNs) due to the lack of inductive bias. Recent works thus resort to convolutions as a plug-and-play module and embed them in various ViT counterparts. In this paper, we argue that the convolutional kernels perform information aggregation to connect

Sebastian Heintze

Let $ G_n $ and $ H_m $ be two non-degenerate linear recurrence sequences defined over a function field $ F $ in one variable over $ \mathbb{C} $, and let $ \mu $ be a valuation on $ F $. We prove that under suitable conditions there are effectively computable constants $ c_1 $ and $ C' $ such that the bound \begin{equation*} \mu(G_n - H_m) \leq \mu(G_n) + C

Laura Burdick, Jonathan K. Kummerfeld, Rada Mihalcea

We use paraphrases as a unique source of data to analyze contextualized embeddings, with a particular focus on BERT. Because paraphrases naturally encode consistent word and phrase semantics, they provide a unique lens for investigating properties of embeddings. Using the Paraphrase Database's alignments, we study words within paraphrases as well as phrase r

M. Akif Keskiner, M. Ö Oktel

Socolar dodecagonal lattice is a quasicrystal closely related to the better-known Ammann-Beenker and Penrose lattices. The cut and project method generates this twelve-fold rotationally symmetric lattice from the six-dimensional simple cubic lattice. We consider the vertex tight-binding model on this lattice and use the acceptance domains of the vertices in

Luca Demetrio, Battista Biggio, Fabio Roli

While machine learning is vulnerable to adversarial examples, it still lacks systematic procedures and tools for evaluating its security in different application contexts. In this article, we discuss how to develop automated and scalable security evaluations of machine learning using practical attacks, reporting a use case on Windows malware detection.

Jacob Fjeld Grevstad

We introduce the concept of an $n$-minimal Auslander--Gorenstein category and $n$-precluster tilting subcategory. With this, we create an analog of the higher Auslander--Solberg correspondence (arXiv:1608.04179) for exact categories. Our approach is based on the recent generalization of the (higher) Auslander correspondence to exact categories (arXiv:2011.15

Xiang Huang, Shengluo Ma, Haidong Wang, Shangchao Lin

Structural manipulation at the nanoscale breaks the intrinsic correlations among different energy carrier transport properties, achieving high thermoelectric performance. However, the coupled multifunctional (phonon and electron) transport in the design of nanomaterials makes the optimization of thermoelectric properties challenging. Machine learning brings

Tom Eulenfeld, Gregor Hillers, Tommi A. T. Vuorinen, Ulrich Wegler

We analyze envelopes of 233 and 22 $M_{\text L}$0.0 to $M_{\text L}$1.8 earthquakes induced by two geothermal stimulations in the Helsinki, Finland, metropolitan area. We separate source spectra and site terms and determine intrinsic attenuation and the scattering strength of shear waves in the 3 Hz to 200 Hz frequency range using radiative transfer based sy

Harun Teper, Anggera Bayuwindra, Raphael Riebl, Ricardo Severino

In the near future, the development of autonomous driving will get more complex as the vehicles will not only rely on their own sensors but also communicate with other vehicles and the infrastructure to cooperate and improve the driving experience. Towards this, several research areas, such as robotics, communication, and control, are required to collaborate

Harrison Zhu, Carles Balsells Rodas, Yingzhen Li

Sequential VAEs have been successfully considered for many high-dimensional time series modelling problems, with many variant models relying on discrete-time mechanisms such as recurrent neural networks (RNNs). On the other hand, continuous-time methods have recently gained attraction, especially in the context of irregularly-sampled time series, where they

Jeffrey Galkowski, David Lafontaine, Euan A. Spence, Jared Wunsch

We consider approximation of the variable-coefficient Helmholtz equation in the exterior of a Dirichlet obstacle using perfectly-matched-layer (PML) truncation; it is well known that this approximation is exponentially accurate in the PML width and the scaling angle, and the approximation was recently proved to be exponentially accurate in the wavenumber $k$

Jörg Encke, Mathias Dietz

Stimuli consisting of an interaurally phase-shifted tone in diotic noise -- often referred to as $N_0 S_\psi$ -- are commonly used in the field of binaural hearing. As a consequence of mixing diotic noise with a dichotic tone, this type of stimulus contains random fluctuations in both interaural phase- and level-difference. This study reports the joint proba

Michael Schürmann

This article is on the research of Wilhelm von Waldenfels in the mathematical field of quantum (or non-commutative) probability theory. Wilhelm von Waldenfels was one of the pioneers, even one of the founders, of quantum probability. We concentrate on a small part of his scientific work. The aspects of physics are practically not mentioned at all. There is n

Railana Santana, Luana Martins, Tássio Virgínio, Larissa Soares

Test smells can reduce the developers' ability to interact with the test code. Refactoring test code offers a safe strategy to handle test smells. However, the manual refactoring activity is not a trivial process, and it is often tedious and error-prone. This study aims to evaluate RAIDE, a tool for automatic identification and refactoring of test smells. We

Tara Abrishami, Maria Chudnovsky, Sepehr Hajebi, Sophie Spirkl

This paper continues a series of papers investigating the following question: which hereditary graph classes have bounded treewidth? We call a graph $t$-clean if it does not contain as an induced subgraph the complete graph $K_t$, the complete bipartite graph $K_{t, t}$, subdivisions of a $(t \times t)$-wall, and line graphs of subdivisions of a $(t \times t

Nathan Baum, Mark A. Minor

This paper evaluates the capabilities of a soft robotic pneumatic actuator derived from the terrain display haptic device, "The Smart Shoe." The bladder design of the Smart Shoe is upgraded to include a pressure supply and greater output flow capabilities. A bench top setup is created to rigorously test this new type of actuator. The bandwidth and stiffness

Gang Li, Xiang Li, Yujie Wang, Yichao Wu

The Mean-Teacher (MT) scheme is widely adopted in semi-supervised object detection (SSOD). In MT, the sparse pseudo labels, offered by the final predictions of the teacher (e.g., after Non Maximum Suppression (NMS) post-processing), are adopted for the dense supervision for the student via hand-crafted label assignment. However, the sparse-to-dense paradigm

Paul L. Ebert, Denis Gessert, Martin Weigel

Population annealing is a powerful sequential Monte Carlo algorithm designed to study the equilibrium behavior of general systems in statistical physics through massive parallelism. In addition to the remarkable scaling capabilities of the method, it allows for measurements to be enhanced by weighted averaging, admitting to reduce both systematic and statist

Gayathri S, Akshat Anand, Astha Vijayvargiya, Pushpalatha M

Smart wearables have played an integral part in our day to day life. From recording ECG signals to analysing body fat composition, the smart wearables can do it all. The smart devices encompass various sensors which can be employed to derive meaningful information regarding the user's physical and psychological conditions. Our approach focuses on employing s

Kevin Kouwenhoven, Daniel Fan, Enrico Biancalani, Steven A. H. de Rooij

Kinetic Inductance Detectors (KIDs) are superconducting energy-resolving detectors, sensitive to single photons from the near-infrared to ultraviolet. We study a hybrid KID design consisting of a beta phase tantalum ($\beta$-Ta) inductor and a NbTiN interdigitated capacitor (IDC). The devices show an average intrinsic quality factor $Q_i$ of 4.3$\times10^5$

Gregg M. Gallatin

Anderson localization is derived directly from the path integral representation of quantum mechanics in the presence of a random potential energy function. The probability distribution of the potential energy is taken to be a Gaussian in function space with a given autocorrelation function. Averaging the path integral itself we find that the localization len

Amit Henig, Raja Giryes

In this work, we suggest Kernel Filtering Linear Overparameterization (KFLO), where a linear cascade of filtering layers is used during training to improve network performance in test time. We implement this cascade in a kernel filtering fashion, which prevents the trained architecture from becoming unnecessarily deeper. This also allows using our approach w

Yinlin Deng, Chenyuan Yang, Anjiang Wei, Lingming Zhang

A growing body of research has been dedicated to DL model testing. However, there is still limited work on testing DL libraries, which serve as the foundations for building, training, and running DL models. Prior work on fuzzing DL libraries can only generate tests for APIs which have been invoked by documentation examples, developer tests, or DL models, lea

Yoli Shavit, Yosi Keller

Absolute pose regressor (APR) networks are trained to estimate the pose of the camera given a captured image. They compute latent image representations from which the camera position and orientation are regressed. APRs provide a different tradeoff between localization accuracy, runtime, and memory, compared to structure-based localization schemes that provid

Matthew Lau, Kayla Thames, Sakis Meliopoulos

The increasing deployment of end use power resources in distribution systems created active distribution systems. Uncontrolled active distribution systems exhibit wide variations of voltage and loading throughout the day as some of these resources operate under max power tracking control of highly variable wind and solar irradiation while others exhibit rand

Sylvain Barré, Mikaël Pichot

We study the distribution of roots of rank 2 in nonpositively curved 2-complexes with Moebius--Kantor links. For every face in such a complex, the parity of the number of roots of rank 2 in a neighbourhood of the face is a well-defined geometric invariant determined by the root distribution. We study the relation between the root distribution and the parity

Alex Gnech, Rocco Schiavilla

The five low-energy constants (LECs) in the electromagnetic current derived in chiral effective field theory ($\chi$EFT) up to one loop are determined by a simultaneous fit to the $A\,$=$\,2$--3 nuclei magnetic moments and to the deuteron magnetic form factor and threshold electrodisintegration at backward angles over a wide range of momentum transfers. The

Assaf Naor, Ashwin Sah, Mehtaab Sawhney, Yufei Zhao

We investigate which finite Cayley graphs admit a quantum ergodic eigenbasis, proving that this holds for any Cayley graph on a group of size $n$ for which the sum of the dimensions of its irreducible representations is $o(n)$, yet there exist Cayley graphs that do not have any quantum ergodic eigenbasis.

Hao Zhang, Lechao Cheng, Yanbin Hao, Chong-Wah Ngo

Video transformer naturally incurs a heavier computation burden than a static vision transformer, as the former processes $T$ times longer sequence than the latter under the current attention of quadratic complexity $(T^2N^2)$. The existing works treat the temporal axis as a simple extension of spatial axes, focusing on shortening the spatio-temporal sequenc

Meilin Yang, Jian Xu, Yang Liu, Wenbo Ding

Deep hashing has been widely applied in large-scale data retrieval due to its superior retrieval efficiency and low storage cost. However, data are often scattered in data silos with privacy concerns, so performing centralized data storage and retrieval is not always possible. Leveraging the concept of federated learning (FL) to perform deep hashing is a rec

Eduardo Gueron, Jeronimo Pellegrini

The invariance of Benford-Newcomb law under base changing is employed to test whether or not some data follow such distribution. Taking into account the Brazilian senate election in 1994, changes in the numerical base were able to evidence probable fraud.

Ming Xin, Mark A. Minor

Balancing path following accuracy and error convergence with graceful motion in steering control is challenging due to the competing nature of these requirements, especially across a range of operating speeds and conditions. This paper demonstrates that an integrated multi-tiered steering controller considering the impact of slip on kinematic control, dynami

Haoxin Ma, Jiangyan Yi, Chenglong Wang, Xinrui Yan

Fake audio detection is a growing concern and some relevant datasets have been designed for research. However, there is no standard public Chinese dataset under complex conditions.In this paper, we aim to fill in the gap and design a Chinese fake audio detection dataset (CFAD) for studying more generalized detection methods. Twelve mainstream speech-generati

Matías Chávez, Matthias Ernst

We present a framework that uses a continuous frequency space to describe and design solid-state NMR experiments. The approach is similar to the well established Floquet treatment for NMR, but is not restricted to periodic Hamiltonians and allows the design of experiments in a reverse fashion. The framework is based on perturbation theory on a continuous Fou

Jiebao Zhang, Wenhua Qian, Rencan Nie, Jinde Cao

A counter-intuitive property of convolutional neural networks (CNNs) is their inherent susceptibility to adversarial examples, which severely hinders the application of CNNs in security-critical fields. Adversarial examples are similar to original examples but contain malicious perturbations. Adversarial training is a simple and effective defense method to i

Anisa Halimi, Swanand Kadhe, Ambrish Rawat, Nathalie Baracaldo

With privacy legislation empowering the users with the right to be forgotten, it has become essential to make a model amenable for forgetting some of its training data. However, existing unlearning methods in the machine learning context can not be directly applied in the context of distributed settings like federated learning due to the differences in learn

Sabine Harribey

This thesis focuses on renormalization of tensor field theories. Its first part considers a quartic tensor model with $O(N)^3$ symmetry and long-range propagator. The existence of a non-perturbative fixed point in any $d$ at large $N$ is established. We found four lines of fixed points parametrized by the so-called tetrahedral coupling. One of them is infrar

Tomáš Kroupa, Sara Vannucci, Tomáš Votroubek

The information decomposition problem requires an additive decomposition of the mutual information between the input and target variables into nonnegative terms. The recently introduced solution to this problem, Information Attribution, involves the Shapley-style value measuring the influence of predictors in the coalitional game associated with the joint pr

Zelin Zhao, Ze Wu, Yueqing Zhuang, Boxun Li

Multi-object tracking (MOT) requires detecting and associating objects through frames. Unlike tracking via detected bounding boxes or tracking objects as points, we propose tracking objects as pixel-wise distributions. We instantiate this idea on a transformer-based architecture, P3AFormer, with pixel-wise propagation, prediction, and association. P3AFormer

T. Borkovits, S. A. Rappaport, S. Toonen, M. Moe

We report the results of the photodynamical analyses of four compact, tight triple stellar systems, KICs 6964043, 5653126, 5731312, 8023317, based largely on $Kepler$ and $TESS$ data. All systems display remarkable eclipse timing and eclipse depth variations, the latter implying a non-aligned outer orbit. Moreover, KIC 6964043 is also a triply eclipsing syst

R. Schoeffauer, G. Wunder

We derive key features of the Age-of-Information distribution in a system whose activities are strictly limited to periodic instances on a global time grid. In particular, one agent periodically generates updates while the other agent periodically uses the most recently received of those updates. Likewise, transmission of those updates over a network can onl

Yifei Huang, Lijin Yang, Yoichi Sato

Few-shot action recognition aims to recognize novel action classes using only a small number of labeled training samples. In this work, we propose a novel approach that first summarizes each video into compound prototypes consisting of a group of global prototypes and a group of focused prototypes, and then compares video similarity based on the prototypes.

Martha Dais Ferreira, Gabriel Spadon, Amilcar Soares, Stan Matwin

Automatic Identification System (AIS) messages are useful for tracking vessel activity across oceans worldwide using radio links and satellite transceivers. Such data plays a significant role in tracking vessel activity and mapping mobility patterns such as those found in fishing. Accordingly, this paper proposes a geometric-driven semi-supervised approach f

Anal Bhowmik, Ofir E. Alon

The dynamics of bosons in Josephson junctions have drawn much attention where the bosons are initially condensed. When interacting bosons tunnel back and forth along the junction, depletion and eventually fragmentation develop. Here, we pose the question how do fragmented bosons tunnel in a bosonic Josephson junction? To this end, we exploit the transverse d