January 2022 arXiv papers — page 7

Jacqueline Wentz, Alireza Doostan

We propose a method for quantifying uncertainty in high-dimensional PDE systems with random parameters, where the number of solution evaluations is small. Parametric PDE solutions are often approximated using a spectral decomposition based on polynomial chaos expansions. For the class of systems we consider (i.e., high dimensional with limited solution evalu

Faranak Khosravi, Mehdi Tarhani, Shivani Kurle, Mehdi Shadaram

We designed a Reconfigurable Optical Add/Drop Multiplexer (ROADM) based on a subcarrier add/drop node in an optical communication system that is suitable for all kinds of optical multiplexing signals. To achieve this goal, at first, we designed an optical comb generator based on a dual-drive Mach Zehnder. The new ROADM setup is validated by a 100 Gb/s 4-subc

Shannon P. Harvey, Bai Yang Wang, Jennifer Fowlie, Motoki Osada

Infinite-layer nickelates present a new family of potential unconventional superconductors. A key open question is the superconducting pairing symmetry. We present low-temperature measurements of the London penetration depth in optimally doped La_{0.8}Sr_{0.2}NiO_{2}, Pr_{0.8}Sr_{0.2}NiO_{2}, and Nd_{0.8}Sr_{0.2}NiO_{2}. For La and Pr-nickelates, the superfl

Baochi Fu, Longgang Pang, Huichao Song, Yi Yin

The spin Hall effect (SHE) is a generation of spin polarization for moving spin carriers in materials under an external electric field and has been observed in semiconductors, metals, and insulators at or below room temperature. Recent theoretical analyses show that spin Hall current can be induced by the baryon chemical potential gradient which plays the ro

Nader Inan

It is well known that a covariant Lagrangian for relativistic charged particles can lead to a vanishing Hamiltonian. Alternatively, it is shown that using a "space+time" Lagrangian leads to a new canonical momentum and minimal coupling rule that describes the coupling of both electromagnetic and gravitational fields to a relativistic charged particle. Discre

ChuMiao Li

With the improvement of social life quality and the real needs of daily work, images are more and more all around us. Image blurring due to camera shake, human movement, etc. has become the key to affecting image quality. How to remove image blur and restore clear image has gradually become an important research direction in the field of computer vision. Aft

Daodao Yang

In [Yan22a], we defined so-called ``log-type" GCD sums and proved the lower bounds $\Gamma^{(\ell)}_1(N) \gg_{\ell} \left(\log\log N\right)^{2+2\ell}$. We will establish the upper bounds $\Gamma^{(\ell)}_1(N)\ll_{\ell} \left(\log \log N\right)^{2+2\ell}$ in this note, which generalizes G\'{a}l's theorem on GCD sums (corresponding to the case $\ell = 0$). Thi

Mi Jiang

Motivated by the recent realization of the infinite-layer nickelate superconductivity (SC), we quantitatively investigate a two-orbital $d$-$s$ model by dynamic cluster quantum Monte Carlo calculations. Focusing on the impact of inter-orbital hybridization on the superconducting properties, our simulations indicate that the $d$-$s$ hybridization strength has

A. F. Krasnikov

In this paper we prove the theorem on freedom for relatively free Lie algebras with a single relation (analogous with the well-known result of Shirshov) and a generalized Freiheitssatz for relatively free Lie algebras (analogous with the well-known result of Kharlampovich).

Juliana Felkner, Zoltan Nagy, Ariane L. Beck, D. Cale Reeves

Increasing urbanization puts pressure on cities to prioritize sustainable growth and avoid carbon lock-in. Available modeling frameworks fall acutely of guiding such pivotal decision-making at the local level. Financial incentives, behavioral interventions, and mandates drive sustainable technology adoption, while land-use zoning plays a critical role in car

Martin F. Schubert, Alfred K. C. Cheung, Ian A. D. Williamson, Aleksandra Spyra

We introduce a new method for inverse design of nanophotonic devices which guarantees that resulting designs satisfy strict length scale constraints - including minimum width and spacing constraints required by commercial semiconductor foundries. The method adopts several concepts from machine learning to transform the problem of topology optimization with s

Weiwei Lao, Qiaojie Luo, Ying Huang, Haixu Zhong

Current contradictory understanding of passivation comes from overly-complex passive models, defective characterization and misplaced theoretical approaches. From brand-new experimentation, we find that a Ti passive membrane has spatiotemporally-ordered macrostructure. At the start, a thermodynamically-stable chemisorbed Ti-O monolayer is immediately formed

Shern R. Tee, Debra J. Searles

Molecular dynamics (MD) simulations of complex electrochemical systems, such as ionic liquid supercapacitors, are increasingly including the constant potential method (CPM) to model conductive electrodes at specified potential difference, but the inclusion of CPM can be computationally expensive. We demonstrate the computational savings available in CPM MD s

Marcos S. Ferreira, Geraldo de A. Júnior

A conjugation $C$ on a separable complex Hilbert space $\mathcal H$ is an antilinear operator that is isometric and involutive. In this notes, we characterize all conjugations on the Hardy-Hilbert space $H^{2}$ over the disk. In addition, we characterize complex symmetric Toeplitz operators with a special type of these conjugations.

Amin Ghiasi, Hamid Kazemi, Steven Reich, Chen Zhu

Existing techniques for model inversion typically rely on hard-to-tune regularizers, such as total variation or feature regularization, which must be individually calibrated for each network in order to produce adequate images. In this work, we introduce Plug-In Inversion, which relies on a simple set of augmentations and does not require excessive hyper-par

Amelia McNamara

There are many pedagogical considerations for incorporating programming into a statistics course. When using the programming language R, one consideration is the particular R syntax that will be used. This paper reports on a head-to-head comparison run in a pair of introductory statistics labs, one conducted fully in the formula syntax, the other in tidyvers

Thomas Leistner, Stuart Teisseire

We study conformal transformations of indecomposable Lorentzian symmetric spaces of non-constant sectional curvature, the so-called Cahen-Wallach spaces. When a Cahen-Wallach space is conformally curved, its conformal transformations are homotheties. Using this we show that a conformal transformation of a conformally curved Cahen-Wallach space is essential i

Xuanying Li, Changxing Miao, Lifeng Zhao

In this paper, we establish the soliton resolution for the energy critical wave equation with inverse square potential in the radial case and in all dimensions $N\geq3$. The structure of the radial linear operator $\mathcal{L}_a :=-\Delta +\frac{a}{|x|^2}=A^*A$, is essential for the channel of energy, where $A$ is a first order differential operator and $A^*

Puskar Mondal, Shing-Tung Yau

We study the aspects of quasi-local energy associated with a $2-$surface $\Sigma$ bounding a space-like domain $\Omega$ of a physical $3+1$ dimensional spacetime in the regime of gravity coupled to a gauge field. The Wang-Yau quasi-local energy together with an additional term arising due to the coupling of gravity to a gauge field constitutes the total ener

Ziyi Huang, Henry Lam, Amirhossein Meisami, Haofeng Zhang

Bayesian bandit algorithms with approximate Bayesian inference have been widely used in real-world applications. However, there is a large discrepancy between the superior practical performance of these approaches and their theoretical justification. Previous research only indicates a negative theoretical result: Thompson sampling could have a worst-case lin

Sheng Fang, Zongzheng Zhou, Youjin Deng

The upper critical dimension of the Ising model is known to be $d_c=4$, above which critical behavior is regarded as trivial. We hereby argue from extensive simulations that, in the random-cluster representation, the Ising model simultaneously exhibits two upper critical dimensions at $(d_c= 4, d_p=6)$, and critical clusters for $d \geq d_p$, except the larg

Daichi Matsuzuki

This paper pursues positive characteristic analogues of the results of Furusho, Komori, Matsumoto and Tsumura on $p$-adic multiple $L$-functions. We consider $\infty$-adic and $v$-adic multiple zeta functions concerned by Angl\`{e}s, Ngo Dac and Tavares Ribeiro. Our main results in this paper consist of: (1) integral expressions of special values of $\infty$

Milan Haiman

The Dushnik--Miller dimension of a poset $P$ is the least $d$ for which $P$ can be embedded into a product of $d$ chains. Lewis and Souza showed that the dimension of the divisibility order on the interval of integers $[N/\kappa, N]$ is bounded above by $\kappa (\log\kappa)^{1+o(1)}$ and below by $\Omega((\log\kappa/\log\log\kappa)^2)$. We improve the upper

Chi Hong Chow, Naichung Conan Leung

This paper is the $K$-theoretic analogue of a recent new proof, given by the first named author, of Peterson-Lam-Shimozono's theorem via Savelyev's generalization of Seidel representations. The outcome is a new proof of Lam-Li-Mihalcea-Shimozono's conjecture, including its extension to the parabolic case, which was first verified by Kato.

Dennis Volpano

The User Plane Function (UPF) aims to provide network services in the 3GPP 5G core network. These services need to be implemented on demand inexpensively with provable properties. Existing network dataplane programming languages are not up to the task. A new software paradigm is presented for the UPF. It is inspired by model checking a concurrent reactive sy

Alexander Woo

Diaconis and Graham studied a measure of distance from the identity in the symmetric group called total displacement and showed that it is bounded below by the sum of length and reflection length. They asked for a characterization of the permutations where this bound is an equality; we call these the shallow permutations. Cornwell and McNew recently interpre

Daisuke Kishimoto, Masahiro Takeda, Yichen Tong

Ganea proved that the loop space of $\mathbb{C}P^n$ is homotopy commutative if and only if $n=3$. We generalize this result to that the loop spaces of all irreducible Hermitian symmetric spaces but $\mathbb{C}P^3$ are not homotopy commutative. The computation also applies to determining the homotopy nilpotency of the loop spaces of flag manifolds.

N. Hasegawa, K. Hagino, Y. Tanimura

We reply to the criticisms of our publication (N. Hasegawa, K. Hagino, and Y. Tanimura, Phys. Lett. B808, 135693 (2020)) made by A. Ono in his recent article, arXiv:2201.02966.

Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour

We introduce a new family of techniques to post-process ("wrap") a black-box classifier in order to reduce its bias. Our technique builds on the recent analysis of improper loss functions whose optimization can correct any twist in prediction, unfairness being treated as a twist. In the post-processing, we learn a wrapper function which we define as an $\alp

Christine Ye, Maya Fishbach

Gravitational-wave (GW) detections of merging neutron star-black hole (NSBH) systems probe astrophysical neutron star (NS) and black hole (BH) mass distributions, especially at the transition between NS and BH masses. Of particular interest are the maximum NS mass, minimum BH mass, and potential mass gap between them. While previous GW population analyses as

Vedika Saravanan, Samah Mohamed Saeed

Noisy Intermediate-Scale Quantum (NISQ) algorithms, which run on noisy quantum computers should be carefully designed to boost the output state fidelity. While several compilation approaches have been proposed to minimize circuit errors, they often omit the detailed circuit structure information that does not affect the circuit depth or the gate count. In th

Weijie Lu, Manuel Pinto, Y-H Xia

Hartman-Grobman theorem states that there is a homeomorphism H sending the solutions of the nonlinear system onto those of its linearization under suitable assumptions. Many mathematicians have made contributions to prove H\"older continuity of the homeomorphisms. However, is it possible to improve the H\"older continuity to Lipschitzian continuity? This pap

Taraneh Ghandi, Hamidreza Pourreza, Hamidreza Mahyar

Image captioning is a research area of immense importance, aiming to generate natural language descriptions for visual content in the form of still images. The advent of deep learning and more recently vision-language pre-training techniques has revolutionized the field, leading to more sophisticated methods and improved performance. In this survey paper, we

Naoki Ide, Masayuki Ohzeki

An l0-regularized linear regression for a sparse signal reconstruction is implemented based on the quadratic unconstrained binary optimization (QUBO) formulation. In this method, the signal values are quantized and expressed as bit sequences. By transforming l0-norm to a quadratic form of these bits, the fully quadratic objective function is provided and opt

W. G. C. Oropesa, E. S. Nascimento, A. P. Vieira

We employ a lattice-gas extension of the Maier--Saupe model with discrete orientation states to study the phase behavior of a statistical model for biaxial nematogenic units in mean-field theory. The phase behavior of the system is investigated in terms of the strength of isotropic interaction between anisotropic objects, as well as the degree of biaxiality

Sophie MacDonald

We make progress on a generalization of the road (colouring) problem. The road problem was posed by Adler-Goodwyn-Weiss and solved by Trahtman. The generalization was posed, and solved in certain special cases, by Ashley-Marcus-Tuncel. We resolve two new families of cases, of which one generalizes the road problem and follows Trahtman's solution, and the oth

Promit Ghosal, Guilherme L. F. Silva

We study multiplicative statistics for the eigenvalues of unitarily-invariant Hermitian random matrix models. We consider one-cut regular polynomial potentials and a large class of multiplicative statistics. We show that in the large matrix limit several associated quantities converge to limits which are universal in both the potential and the family of mult

Ke-Xin Li, Xiqi Gao, Xiang-Gen Xia

In this paper, we investigate the ergodic sum rate (ESR) capacity achieving uplink (UL) transmit design for massive multiple-input multiple-output (MIMO) low-earth-orbit (LEO) satellite communications with statistical channel state information at the user terminals (UTs). The UL massive MIMO LEO satellite channel model with uniform planar array configuration

Mathieu Roget, Hachem Kadri, Giuseppe Di Molfetta

We contribute to fulfil the long-lasting gap in the understanding of the spatial search with multiple marked vertices. The theoretical framework is that of discrete-time quantum walks (QW), \textit{i.e.} local unitary matrices that drive the evolution of a single particle on the lattice. QW based search algorithms are well understood when they have to tackle

Jinglong Zhao, Zijie Zhou

Practitioners and academics have long appreciated the benefits of covariate balancing when they conduct randomized experiments. For web-facing firms running online A/B tests, however, it still remains challenging in balancing covariate information when experimental subjects arrive sequentially. In this paper, we study an online experimental design problem, w

Rohil Prasad

Right-handed and Reeb vector fields are two rich classes of vector fields on closed, oriented three-manifolds. Prior work of Dehornoy and Florio-Hryniewicz has produced many examples of Reeb vector fields which are right-handed. We prove a result in the other direction. We show that the closed two-form associated to a volume-preserving right-handed vector fi

Emily Adlam

In recent years the quantum foundations community has seen increasing interest in the possibility of using retrocausality as a route to rejecting the conclusions of Bell's theorem and restoring locality to quantum physics. On the other hand, it has also been argued that accepting nonlocality leads to a form of retrocausality. In this article we seek to eluci

Pieter Vlugter, Yves Bellouard

Materials with thermal-invariant elastic properties of materials are of interest for resonant device frequency and dimensional stability of precision devices. Here, we demonstrate that the temperature coefficient of elasticity (TCE) of amorphous silica can be locally reduced using femtosecond laser irradiation. Notably, a self-organized laser-induced modific

Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

In this work, we study the optimal transport (OT) problem between symmetric positive definite (SPD) matrix-valued measures. We formulate the above as a generalized optimal transport problem where the cost, the marginals, and the coupling are represented as block matrices and each component block is a SPD matrix. The summation of row blocks and column blocks

Jaume de Dios Pont, Paata Ivanisvili, José Madrid

We give new proofs of the description convex hulls of space curves $\gamma : [a,b] \mapsto \mathbb{R}^{d}$ having totally positive torsion. These are curves such that all the leading principal minors of $d\times d$ matrix $(\gamma', \gamma'', \ldots, \gamma^{(d)})$ are positive. In particular, we recover parametric representation of the boundary of the conve

Aneel Bhusal, Madhu Sudan Gautam

The purpose of this study is to examine the long-run relationship between gold prices and Nepal Stock Exchange (NEPSE).

Aneel Bhusal

This paper investigates the impact of information and communication technology (ICT) adoption on individual well-being.

Markus Bleuel, Miriam Siebenbürger, Peter Böni, Gerald J. Schneider

Nanoscale structure determination belongs to one of the crucial tasks in materials science. Small-angle neutron scattering (SANS) is a highly valuable tool to investigate nanostructures. Here, we explore the possibility of a compact SANS instrument to be installed at an individual accelerator based pulsed low-flux source, and discuss applications in structur

Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi

The space of value functions is a fundamental concept in reinforcement learning. Characterizing its geometric properties may provide insights for optimization and representation. Existing works mainly focus on the value space for Markov Decision Processes (MDPs). In this paper, we study the geometry of the robust value space for the more general Robust MDPs

Changbin Li, Suraj Kothawade, Feng Chen, Rishabh Iyer

Few-shot classification (FSC) requires training models using a few (typically one to five) data points per class. Meta learning has proven to be able to learn a parametrized model for FSC by training on various other classification tasks. In this work, we propose PLATINUM (semi-suPervised modeL Agnostic meTa-learnIng usiNg sUbmodular Mutual information), a n

Stephany Rajeh, Ali Yassin, Ali Jaber, Hocine Cherifi

Targeting influential nodes in complex networks allows fastening or hindering rumors, epidemics, and electric blackouts. Since communities are prevalent in real-world networks, community-aware centrality measures exploit this information to target influential nodes. Researches show that they compare favorably with classical measures that are agnostic about t

Hazem Abu-Farsakh, Abdallah Qteish

The modified Becke-Johnson exchange potential combined with local-density approximation correlation (mBJLDA) has recently attracted interest because it provides highly improved band gaps at a very low computational cost. In this work we performed an extensive investigation of the performance of the mBJLDA potential employing a norm-conserving pseudopotential

Workneh Y. Ayele, Gustaf Juell-Skielse

Idea generation is the core activity of innovation. Digital data sources, which are sources of innovation, such as patents, publications, social media, websites, etc., are increasingly growing at unprecedented volume. Manual idea generation is time-consuming and is affected by the subjectivity of the individuals involved. Therefore, the use machine-driven da

Ekin Akyürek, Jacob Andreas

In tasks like semantic parsing, instruction following, and question answering, standard deep networks fail to generalize compositionally from small datasets. Many existing approaches overcome this limitation with model architectures that enforce a compositional process of sentence interpretation. In this paper, we present a domain-general and model-agnostic

Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi

Identifying key nodes is crucial for accelerating or impeding dynamic spreading in a network. Community-aware centrality measures tackle this problem by exploiting the community structure of a network. Although there is a growing trend to design new community-aware centrality measures, there is no systematic investigation of the proposed measures' effectiven

Oswin So, Kyle Stachowicz, Evangelos A. Theodorou

Environments with multi-agent interactions often result a rich set of modalities of behavior between agents due to the inherent suboptimality of decision making processes when agents settle for satisfactory decisions. However, existing algorithms for solving these dynamic games are strictly unimodal and fail to capture the intricate multimodal behaviors of t

Pier Domenico Lamberti, Michele Zaccaron

We prove spectral stability results for the $curl curl$ operator subject to electric boundary conditions on a cavity upon boundary perturbations. The cavities are assumed to be sufficiently smooth but we impose weak restrictions on the strength of the perturbations. The methods are of variational type and are based on two main ingredients: the construction o

Petra Berenbrink, Martin Hoefer, Dominik Kaaser, Pascal Lenzner

Opinion spreading in a society decides the fate of elections, the success of products, and the impact of political or social movements. The model by Hegselmann and Krause is a well-known theoretical model to study such opinion formation processes in social networks. In contrast to many other theoretical models, it does not converge towards a situation where

Gabriel Dospinescu, Vytautas Paškūnas, Benjamin Schraen

We bound the Gelfand-Kirillov dimension of unitary Banach space representations of $p$-adic reductive groups, whose locally analytic vectors afford an infinitesimal character. We use the bound to study Hecke eigenspaces in completed cohomology of Shimura curves and $p$-adic Banach space representations of the group of units of a quarternion algebra over $\ma

Kelly Van Lancker, Joshua Betz, Michael Rosenblum

In clinical trials, there is potential to improve precision and reduce the required sample size by appropriately adjusting for baseline variables in the statistical analysis. This is called covariate adjustment. Despite recommendations by regulatory agencies in favor of covariate adjustment, it remains underutilized leading to inefficient trials. We address

Jacob D. Baron, R. W. R. Darling

A Java parallel streams implementation of the $K$-nearest neighbor descent algorithm is presented using a natural statistical termination criterion. Input data consist of a set $S$ of $n$ objects of type V, and a Function<V, Comparator<V>>, which enables any $x \in S$ to decide which of $y, z \in S\setminus\{x\}$ is more similar to $x$. Experiments with the

S Nibedita Swain, Yashovardhan Jha, Prasanta K. Panigrahi

The concept of photon added two-mode Schr\"odinger cat states in which both modes are independent is introduced, their non-classical properties and entanglement are studied. The introduced states emerge as the eigenstates of $f_1f_2a_1a_2$, where $f_1, f_2$ are nonlinear functions of the number operator and $a_1, a_2$ are annihilation operators. We study the

Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi

It is of paramount importance to uncover influential nodes to control diffusion phenomena in a network. In recent works, there is a growing trend to investigate the role of the community structure to solve this issue. Up to now, the vast majority of the so-called community-aware centrality measures rely on non-overlapping community structure. However, in man

Yu-Feng Li, Mark Vagins, Michael Wurm

The advent of gadolinium-loaded Super-Kamiokande (SK-Gd) and of the soon-to-start JUNO liquid scintillator detector marks a substantial improvement in the global sensitivity for the Diffuse Supernova Neutrino Background (DSNB). The present article reviews the detector properties most relevant for the DSNB searches in both experiments and estimates the expect

Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao

Domain generalization asks for models trained over a set of training environments to perform well in unseen test environments. Recently, a series of algorithms such as Invariant Risk Minimization (IRM) has been proposed for domain generalization. However, Rosenfeld et al. (2021) shows that in a simple linear data model, even if non-convexity issues are ignor

Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi

Unlike classical centrality measures, recently developed community-aware centrality measures use a network's community structure to identify influential nodes in complex networks. This paper investigates their relationship on a set of fifty real-world networks originating from various domains. Results show that classical and community-aware centrality measur

A. Mironov, A. Morozov

We enumerate generalizations of the superintegrability property $<character>\ \sim {\rm character}$ and illuminate possible general structures behind them. We collect variations of original formulas available up to date and emphasize the remaining difference between the cases of Hermitian and complex matrices, bosonic and fermionic ones. Especially important

Valentin Daniel Paccoia, Orlando Panella, Pinaki Roy

We study the quantum backflow problem of a relativistic charged Dirac fermion constrained to move on a ring of radius $R$. Using the relativistic current operator we compute the probability flux through a generic time interval to show emergence of quantum backflow. We also discuss the limiting case when the particle moves along a line.

Pedro T. P. Lopes, Nikolaos Roidos

We consider the Cahn-Hilliard equation on manifolds with conical singularities and prove existence of global attractors in higher order Mellin-Sobolev spaces with asymptotics. We also show convergence of solutions in the same spaces to an equilibrium point and provide asymptotic behavior of the equilibrium near the conical tips in terms of the local geometry

Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi

Centrality measures are crucial in quantifying the influence of the members of a social network. Although there has been a great deal of work dealing with this issue, the vast majority of classical centrality measures are agnostic of the community structure characterizing many social networks. Recent works have developed community-aware centrality measures t

Aimane Najmeddine, Maryam Shakiba

We propose a physics and chemistry-based constitutive framework to predict the stress responses of thermo-chemically aged elastomers and capture their brittle failure using the phase-field approach. High-temperature aging in the presence of oxygen causes the macromolecular network of elastomers to undergo complex chemical reactions inducing two main mechanis

Hayden Julius

In this paper, we describe linear maps between complex Banach algebras that preserve products equal to fixed elements. This generalizes some important special cases where the fixed elements are the zero or identity element. First we show that if such map preserves products equal to a finite-rank operator, then it must also preserve the zero product. In sever

Kyle Mahowald, Evgeniia Diachek, Edward Gibson, Evelina Fedorenko

Grammatical cues are sometimes redundant with word meanings in natural language. For instance, English word order rules constrain the word order of a sentence like "The dog chewed the bone" even though the status of "dog" as subject and "bone" as object can be inferred from world knowledge and plausibility. Quantifying how often this redundancy occurs, and h

Tomojit Ghosh, Michael Kirby

Autoencoders have been widely used as a nonlinear tool for data dimensionality reduction. While autoencoders don't utilize the label information, Centroid-Encoders (CE)\cite{ghosh2022supervised} use the class label in their learning process. In this study, we propose a sparse optimization using the Centroid-Encoder architecture to determine a minimal set of

Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko

Computing a Gaussian process (GP) posterior has a computational cost cubical in the number of historical points. A reformulation of the same GP posterior highlights that this complexity mainly depends on how many \emph{unique} historical points are considered. This can have important implication in active learning settings, where the set of historical points

Adriano M. Garsia, Timothy J. McLarnan

The numbers $f_\lambda$ of standard tableaux of shape $\lambda\vdash n$ satisfy 2 fundamental recursions: $f_\lambda = \sum f_{\lambda^-}$ and $(n + 1)f_\lambda=\sum f_{\lambda^+}$, where $\lambda^-$ and $\lambda^+$ run over all shapes obtained from $\lambda$ by adding or removing a square respectively. The first of these recursions is trivial; the second ca

Fenghuan He

Given a directed network $ G $, we are interested in studying the qualitative features of $ G $ which govern how perturbations propagate across $ G $. Various classical centrality measures have been already developed and proven useful to capture qualitative features and behaviors for undirected networks. In this paper, we use topological data analysis (TDA)

Kristen Hendricks, Jennifer Hom, Matthew Stoffregen, Ian Zemke

We prove first-order naturality of involutive Heegaard Floer homology, and furthermore construct well-defined maps on involutive Heegaard Floer homology associated to cobordisms between three-manifolds. We also prove analogous naturality and functoriality results for involutive Floer theory for knots and links. The proof relies on the doubling model for the

Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi

The constantly growing size of real-world networks is a great challenge. Therefore, building a compact version of networks allowing their analyses is a must. Backbone extraction techniques are among the leading solutions to reduce network size while preserving its features. Coarse-graining merges similar nodes to reduce the network size, while filter-based m

Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Goliński

Neural compression algorithms are typically based on autoencoders that require specialized encoder and decoder architectures for different data modalities. In this paper, we propose COIN++, a neural compression framework that seamlessly handles a wide range of data modalities. Our approach is based on converting data to implicit neural representations, i.e.

Krushi Patel, Andres M. Bur, Fengjun Li, Guanghui Wang

Local Transformer-based classification models have recently achieved promising results with relatively low computational costs. However, the effect of aggregating spatial global information of local Transformer-based architecture is not clear. This work investigates the outcome of applying a global attention-based module named multi-resolution overlapped att

Hanan Alahmadi, Håvard Rue, Janet van Niekerk

Statistical analysis based on quantile regression methods is more comprehensive, flexible, and less sensitive to outliers when compared to mean regression methods. When the link between different diseases are of interest, joint disease mapping is useful for measuring directional correlation between them. Most studies study this link through multiple correlat

Shubham Chandel, Colin B. Clement, Guillermo Serrato, Neel Sundaresan

We study the feasibility of a Data Science assistant powered by a sequence-to-sequence transformer by training a new model JuPyT5 on all publicly available Jupyter Notebook GitHub repositories and developing a new metric: Data Science Problems (DSP). DSP is a collection of 1119 problems curated from 306 pedagogical notebooks with 92 dataset dependencies, nat

Matin Macktoobian, Zhan Shu, Qing Zhao

In this paper, we synthesize a data-driven method to predict the optimal topology of an ad-hoc robot network. This problem is technically a multi-task classification problem. However, we divide it into a class of multi-class classification problems that can be more efficiently solved. For this purpose, we first compose an algorithm to create ground-truth opt

Usama Masood, Hasan Farooq, Ali Imran, Adnan Abu-Dayya

In modern wireless communication systems, radio propagation modeling to estimate pathloss has always been a fundamental task in system design and optimization. The state-of-the-art empirical propagation models are based on measurements in specific environments and limited in their ability to capture idiosyncrasies of various propagation environments. To cope

Giuseppe C. Calafiore, Giulia Fracastoro, Anton V. Proskurnikov

This paper proposes a novel dynamical model for determining clearing payments in financial networks. We extend the classical Eisenberg-Noe model of financial contagion to multiple time periods, allowing financial operations to continue after possible initial pseudo defaults, thus permitting nodes to recover and eventually fulfil their liabilities. Optimal cl

R. A. Konoplya, A. Zhidenko

The general parametrization of spherically symmetric and asymptotically flat black-hole spacetimes in arbitrary metric theories of gravity was suggested in [3]. The parametrization is based on the continued fraction expansion in terms of the compact radial coordinate and has superior convergence and strict hierarchy of parameters. It is known that some obser

Rui P. Cardoso, Emma Hart, David Burth Kurka, Jeremy V. Pitt

Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using gradient descent to train evolved architectures during the search can be computationally prohibitive. Here we propose a method to overcome this limitation by using a surrogate model which e

Angelos Toytziaridis, Paolo Falcone, Jonas Sjöberg

This paper focuses on the problem of predicting the future position of a target road user given its current state, consisting of position and velocity. A weighted average approach is adopted, where the weights are determined from data containing the state trajectories of previously observed road users. In particular, a similarity function is introduced to ex

Ruizhi Cheng, Nan Wu, Songqing Chen, Bo Han

Metaverse, with the combination of the prefix "meta" (meaning transcending) and the word "universe", has been deemed as the next-generation (NextG) Internet. It aims to create a shared virtual space that connects all virtual worlds via the Internet, where users, represented as digital avatars, can communicate and collaborate as if they are in the physical wo

Yulin Liu, Luyao Zhang

Currently, there are no convincing proxies for the fundamentals of cryptocurrency assets. We propose a new market-to-fundamental ratio, the price-to-utility (PU) ratio, utilizing unique blockchain accounting methods. We then proxy various existing fundamental-to-market ratios by Bitcoin historical data and find they have little predictive power for short-ter

Jens Helge Reelfs, Oliver Hohlfeld, Niklas Henckell

In this paper, we empirically analyze two examples of a Western (DE) versus Middle-East (SA) Online Social Messaging App. By focusing on the system interactions over time in comparison, we identify inherent differences in user engagement. We take a deep dive and shed light onto differences in user attention shifts and showcase their structural implications t

Ramona Merhej, Fernando P. Santos, Francisco S. Melo, Mohamed Chetouani

Collective risk dilemmas (CRDs) are a class of n-player games that represent societal challenges where groups need to coordinate to avoid the risk of a disastrous outcome. Multi-agent systems incurring such dilemmas face difficulties achieving cooperation and often converge to sub-optimal, risk-dominant solutions where everyone defects. In this paper we inve

D. S. Agafontsev, E. A. Kuznetsov, A. A. Mailybaev, E. V. Sereshchenko

We study formation of quasi two-dimensional (thin pancakes) vortex structures in three-dimensional flows, and quasi one-dimensional structures in two-dimensional hydrodynamics. These structures are formed at high Reynolds numbers, when their evolution is described at the leading order by the Euler equations for an ideal incompressible fluid. We show numerica

Lorenzo Rosso, Leonardo Mazza, Alberto Biella

We study the quantum dynamics of a one-dimensional SU(3)-symmetric system of cold atoms in the presence of two-body losses. We exploit the representation theory of SU(3), the so-called eightfold way, as a scheme to organize the dark states of the dissipative dynamics in terms of generalized Dicke states and show how they are dynamically approached, both in t

Deepak Gupta, Kush Attal, Dina Demner-Fushman

This paper introduces a new challenge and datasets to foster research toward designing systems that can understand medical videos and provide visual answers to natural language questions. We believe medical videos may provide the best possible answers to many first aids, medical emergency, and medical education questions. Toward this, we created the MedVidCL

Jennifer Elder

Any permutation in the finite symmetric group can be written as a product of simple transpositions $s_i = (i~i+1)$. For a fixed permutation $\sigma \in \mathfrak{S}_n$ the products of minimal length are called reduced decompositions or reduced words, and the collection of all such reduced words is denoted $\mathcal{R}(\sigma)$. Any reduced word of $\sigma$ c

Cristian Challu, Kin G. Olivares, Boris N. Oreshkin, Federico Garza

Recent progress in neural forecasting accelerated improvements in the performance of large-scale forecasting systems. Yet, long-horizon forecasting remains a very difficult task. Two common challenges afflicting the task are the volatility of the predictions and their computational complexity. We introduce N-HiTS, a model which addresses both challenges by i

Amila Dautbasic, Senad Becirovic

In March 2020, the World Health Organization declared the COVID pandemic, which caused interruptions and delays in many activities, but most importantly, it led to some huge changes in education. Online teaching will prove to be the most commonly used method that should compensate for the inability to work in the classroom and allow the educational process t

Henning Kirchberg, Peter Nalbach, Christian Bressler, Michael Thorwart

When a hydrophilic solute in water is suddenly turned into a hydrophobic species, for instance, by photoionization, a layer of hydrated water molecules forms around the solute on a time scale of a few picoseconds. We study the dynamic build-up of the hydration shell around a hydrophobic solute on the basis of a time-dependent dielectric continuum model. Info