arXiv papers from April 2023

Tianxiang Hao, Hui Chen, Yuchen Guo, Guiguang Ding

Recently, transformers have shown strong ability as visual feature extractors, surpassing traditional convolution-based models in various scenarios. However, the success of vision transformers largely owes to their capacity to accommodate numerous parameters. As a result, new challenges for adapting large models to downstream tasks arise. On the one hand, cl

Tianyi Yang, Romeel Davé, Weiguang Cui, Yan-Chuan Cai

We use the SIMBA galaxy formation simulation suite to explore anisotropies in the properties of circumgalactic gas that result from accretion and feedback processes. We particularly focus on the impact of bipolar active galactic nuclei (AGN) jet feedback as implemented in SIMBA, which quenches galaxies and has a dramatic effect on large-scale gas properties.

Chin-Yu Hsiao, Rung-Tzung Huang, Xiaoshan Li, Guokuan Shao

Let $M$ be a complex manifold with boundary $X$, which admits a holomorphic Lie group $G$-action preserving $X$. We establish a full asymptotic expansion for the $G$-invariant Bergman kernel under certain assumptions. As an application, we get $G$-invariant version of Fefferman's result about regularity of biholomorphic maps on strongly pseudoconvex domains

Vamsi Krishna Yepuri, Venkata Kalyan Polamarasetty, Shivani Donthi, Ajay Kumar Reddy Gondi

This project investigates the benefits of containerization technology in modern software development and deployment. The study emphasizes the advantages of using Kubernetes and Docker in the development process, including the easy packaging and deployment of microservices, efficient resource utilization, faster startup times, and greater scalability and flex

Evangelos Ntavelis, Mohamad Shahbazi, Iason Kastanis, Radu Timofte

We propose a discrete latent distribution for Generative Adversarial Networks (GANs). Instead of drawing latent vectors from a continuous prior, we sample from a finite set of learnable latents. However, a direct parametrization of such a distribution leads to an intractable linear increase in memory in order to ensure sufficient sample diversity. We address

Antonio Abelem, Don Towsley, Gayane Vardoyan

Quantum information, computation and communication, will have a great impact on our world. One important subfield will be quantum networking and the quantum Internet. The purpose of a quantum Internet is to enable applications that are fundamentally out of reach for the classical Internet. Quantum networks enable new capabilities to communication systems. Th

Leonardo de Lellis Rossi, Leticia Mara Berto, Eric Rohmer, Paula Paro Costa

The ability to automatically learn movements and behaviors of increasing complexity is a long-term goal in autonomous systems. Indeed, this is a very complex problem that involves understanding how knowledge is acquired and reused by humans as well as proposing mechanisms that allow artificial agents to reuse previous knowledge. Inspired by Jean Piaget's the

Ben Zandonati, Ruohan Wang, Ruihan Gao, Yan Wu

Tactile representation learning (TRL) equips robots with the ability to leverage touch information, boosting performance in tasks such as environment perception and object manipulation. However, the heterogeneity of tactile sensors results in many sensor- and task-specific learning approaches. This limits the efficacy of existing tactile datasets, and the su

Ming-Chang Lee, Jia-Chun Lin

Providing online adaptive lightweight time series anomaly detection without human intervention and domain knowledge is highly valuable. Several such anomaly detection approaches have been introduced in the past years, but all of them were only implemented in one deep learning library. With the development of deep learning libraries, it is unclear how differe

Jon Crall

The performance of a binary classifier is described by a confusion matrix with four entries: the number of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN). The Matthews Correlation Coefficient (MCC), F1, and Fowlkes-Mallows (FM) scores are scalars that summarize a confusion matrix. Both the F1 and FM scores are based

Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das

Due to privacy or commercial constraints, large pre-trained language models (PLMs) are often offered as black-box APIs. Fine-tuning such models to downstream tasks is challenging because one can neither access the model's internal representations nor propagate gradients through it. This paper addresses these challenges by developing techniques for adapting P

L. A. Kurdachenko, O. O. Pypka, M. M. Semko

Let $L$ be an algebra over a field $F$ with the binary operations $+$ and $[,]$. Then $L$ is called a left Leibniz algebra if it satisfies the left Leibniz identity: $[[a,b],c]=[a,[b,c]]-[b,[a,c]]$ for all elements $a,b,c\in L$. A linear transformation $f$ of $L$ is called an endomorphism of $L$, if $f([a,b])=[f(a),f(b)]$ for all elements $a,b\in L$. A bijec

S. J. Ben Yoo, Sandeep Kumar Singh, Mehmet Berkay On, Gamze Gul

We introduce a new concept of Quantum Wrapper Networking, which enables control, management, and operation of quantum networks that can co-exist with classical networks while keeping the requirements for quantum networks intact. The quantum wrapper networks (QWNs) enable the transparent and interoperable transportation of quantum wrapper datagrams consisting

J. Menezes, E. Rangel

We investigate the spatial dynamics of two disease epidemics reaching a three-species cyclic model. Regardless of their species, all individuals are susceptible to being infected with two different pathogens, which spread through person-to-person contact. The occurrence of coinfection leads to a synergistic increase in the risk of hosts dying due to complica

M. O. Ajeesh, M. Bordelon, C. Girod, S. Mishra

Topological superconductivity is a long-sought state of matter in bulk materials, and odd-parity superconductor UTe$_2$ is a prime candidate. The recent observation of a field-trainable spontaneous Kerr signal in UTe$_2$ at the onset of superconductivity provides strong evidence that the superconducting order parameter is multicomponent and breaks time-rever

Zhen Miao, Yen-Chi Chen, Adrian Dobra

We introduce finite mixtures of Ising models as a novel approach to study multivariate patterns of associations of binary variables. Our proposed models combine the strengths of Ising models and multivariate Bernoulli mixture models. We examine conditions required for the identifiability of Ising mixture models, and develop a Bayesian framework for fitting t

Tomáš Kepka, Miroslav Korbelář

Let $S$ be an additively idempotent semiring and $\mathbf{M}_n(S)$ be the semiring of all $n\times n$ matrices over $S$. We characterize the conditions of when the semiring $\mathbf{M}_n(S)$ is congruence-simple provided that the semiring $S$ is either commutative or finite. We also give a characterization of when the semiring $\mathbf{M}_n(S)$ is subdirectl

Michael Hanna, Ollie Liu, Alexandre Variengien

Pre-trained language models can be surprisingly adept at tasks they were not explicitly trained on, but how they implement these capabilities is poorly understood. In this paper, we investigate the basic mathematical abilities often acquired by pre-trained language models. Concretely, we use mechanistic interpretability techniques to explain the (limited) ma

Célestin Coquidé, José Lages, Dima L. Shepelyansky

During his state visit to China in April 2023, Brazilian President Lula proposed the creation of a trade currency supported by the BRICS countries. Using the United Nations Comtrade database, providing the frame of the world trade network associated to 194 UN countries during the decade 2010 - 2020, we study a mathematical model of influence battle of three

Jan Wichelmann, Christopher Peredy, Florian Sieck, Anna Pätschke

RISC-V is an emerging technology, with applications ranging from embedded devices to high-performance servers. Therefore, more and more security-critical workloads will be conducted with code that is compiled for RISC-V. Well-known microarchitectural side-channel attacks against established platforms like x86 apply to RISC-V CPUs as well. As RISC-V does not

Matthew Weidner, Martin Kleppmann

Most existing algorithms for replicated lists, which are widely used in collaborative text editors, suffer from a problem: when two users concurrently insert text at the same position in the document, the merged outcome may interleave the inserted text passages, resulting in corrupted and potentially unreadable text. The problem has gone unnoticed for decade

Augustine Musukwa

We determine a connection between the weight of a Boolean function and the total weight of its first-order derivatives. The relationship established is used to study some cryptographic properties of Boolean functions. We establish a characterization of APN permutations in terms of the weight of the first-order derivatives of their components. We also charact

Xuehai He, Xin Eric Wang

Despite the success of Transformer models in vision and language tasks, they often learn knowledge from enormous data implicitly and cannot utilize structured input data directly. On the other hand, structured learning approaches such as graph neural networks (GNNs) that integrate prior information can barely compete with Transformer models. In this work, we

Tristan Milne, Adrian Nachman

We develop a theory for image restoration with a learned regularizer that is analogous to that of Meyer's characterization of solutions of the classical variational method of Rudin-Osher-Fatemi (ROF). The learned regularizer we use is a Kantorovich potential for an optimal transport problem of mapping a distribution of noisy images onto clean ones, as first

Yixuan Jia, Maulik Bhatt, Negar Mehr

In this work, we consider the problem of autonomous racing with multiple agents where agents must interact closely and influence each other to compete. We model interactions among agents through a game-theoretical framework and propose an efficient algorithm for tractably solving the resulting game in real time. More specifically, we capture interactions amo

Harshita Sahijwani, Kaustubh Dhole, Ankur Purwar, Venugopal Vasudevan

Structured interviews are used in many settings, importantly in market research on topics such as brand perception, customer habits, or preferences, which are critical to product development, marketing, and e-commerce at large. Such interviews generally consist of a series of questions that are asked to a participant. These interviews are typically conducted

Lunet Yifru, Ali Baheri

In many real-world applications, safety constraints for reinforcement learning (RL) algorithms are either unknown or not explicitly defined. We propose a framework that concurrently learns safety constraints and optimal RL policies in such environments, supported by theoretical guarantees. Our approach merges a logically-constrained RL algorithm with an evol

C. X. Zhang, M. Ulybyshev, C. Northe, E. M. Hankiewicz

The Callan-Harvey mechanism in 2+1 D Jackiw-Rebbi model is revisited. We analyzed Callan-Harvey anomaly inflow in the massive Chern insulator (quantum anomalous Hall system) subject to external electric field. In addition to the conventional current flowing from the bulk to edge due to parity anomaly, we considered the dissipation of the edge charge due to i

Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang

Deep learning-based recommender systems have become an integral part of several online platforms. However, their black-box nature emphasizes the need for explainable artificial intelligence (XAI) approaches to provide human-understandable reasons why a specific item gets recommended to a given user. One such method is counterfactual explanation (CF). While C

Tim Barklow, Spencer Gessner, Mark Hogan, Cho-Kuen Ng

As part of the Snowmass'21 community planning excercise, the Advanced Accelerator Concepts (AAC) community proposed future linear colliders with center-of-mass energies up to 15 TeV and luminosities up to 50$\times10^{34}$ cm$^{-2}$s$^{-1}$ in a compact footprint. In addition to being compact, these machines must also be energy efficient. We identify two cha

Peter James Hobson, Noah Louis Hardwicke, Alister Davis, Thomas Smith

Adaptable, low-cost, coils designed by carefully selecting the arrangements and geometries of simple primitive units are used to generate magnetic fields for diverse applications. These extend from magnetic resonance and fundamental physics experiments to active shielding of quantum devices including magnetometers, interferometers, clocks, and computers. How

Wágner Badilla-Céspedes, Edwin León-Cardenal

We compute the $F$-pure threshold of some non-principal ideals which satisfy a geometric generic condition about their Newton polyhedron. We also contribute some evidence in favor of the conjectured equality between the $F$-pure threshold and the log canonical threshold of ideals for infinitely many primes $p$. These results are obtained by generalizing the

Denis Uhland, Helena Dillmann, Yijun Wang, Ilja Gerhardt

The nature of atomic vapors, their natural alignment with interatomic transitions, and their ease of use make them highly suited for spectrally narrow-banded optical filters. Atomic filters come in two flavors: a filter based on the absorption of light by the Doppler broadened atomic vapor, i.e., a notch filter, and a bandpass filter based on the transmissio

Antal Joós

Let $\gamma^d_m(K)$ be the smallest positive number $\lambda$ such that the convex body $K$ can be covered by $m$ translates of $\lambda K$. Let $K^d$ be the $d$-dimensional crosspolytope. It will be proved that $\gamma^d_m(K^d)=1$ for $1\le m< 2d$, $d\ge4$; $\gamma^d_m(K^d)=\frac{d-1}{d}$ for $m=2d,2d+1,2d+2$, $d\ge4$; $\gamma^d_m(K^d)=\frac{d-1}{d}$ for $

Tristan Zaborniak, Ulrike Stege

Many computational problems involve optimization over discrete variables with quadratic interactions. Known as discrete quadratic models (DQMs), these problems in general are NP-hard. Accordingly, there is increasing interest in encoding DQMs as quadratic unconstrained binary optimization (QUBO) models to allow their solution by quantum and quantum-inspired

Baiting Zhu, Meihua Dang, Aditya Grover

The goal of multi-objective reinforcement learning (MORL) is to learn policies that simultaneously optimize multiple competing objectives. In practice, an agent's preferences over the objectives may not be known apriori, and hence, we require policies that can generalize to arbitrary preferences at test time. In this work, we propose a new data-driven setup

Silke Schicktanz, Johannes Welsch, Mark Schweda, Andreas Hein

Current ethical debates on the use of artificial intelligence (AI) in health care treat AI as a product of technology in three ways: First, by assessing risks and potential benefits of currently developed AI-enabled products with ethical checklists; second, by proposing ex ante lists of ethical values seen as relevant for the design and development of assist

Benjamin Jourdain, Kexin Shao

For many examples of couples $(\mu,\nu)$ of probability measures on the real line in the convex order, we observe numerically that the Hobson and Neuberger martingale coupling, which maximizes for $\rho=1$ the integral of $|y-x|^\rho$ with respect to any martingale coupling between $\mu$ and $\nu$, is still a maximizer for $\rho\in(0,2)$ and a minimizer for

Yuri Ozhigov, You Jiangchuan

The quantum master equation (QME), used to describe the Markov process of interaction between atoms and field, has a number of significant drawbacks. It is extremely memory intensive, and also inapplicable to the case of long-term memory in the environment. An iterative algorithm for modeling the dynamics of an atomic system in the extended Tavis-Cummings mo

David Broadhurst, Stephan Ohlmeyer

The Dickman function $\rho(u)$ gives the asymptotic probability that a large integer $N$ has no prime divisor exceeding $N^{1/u}$. We expand it in terms of rapidly computable multiple polylogarithms, as defined by Goncharov and intensively used for evaluations of Feynman integrals in quantum field theory. In parallel, we solve Buchstab's differential-delay e

Yiming Qin, Huangjie Zheng, Jiangchao Yao, Mingyuan Zhou

Diffusion-based models have shown the merits of generating high-quality visual data while preserving better diversity in recent studies. However, such observation is only justified with curated data distribution, where the data samples are nicely pre-processed to be uniformly distributed in terms of their labels. In practice, a long-tailed data distribution

Junchao Li, Mingyu Cai, Zhen Kan, Shaoping Xiao

Motion planning of autonomous agents in partially known environments with incomplete information is a challenging problem, particularly for complex tasks. This paper proposes a model-free reinforcement learning approach to address this problem. We formulate motion planning as a probabilistic-labeled partially observable Markov decision process (PL-POMDP) pro

Yiran Wang

We study the inverse problem of recovering primordial perturbations from anisotropies of Cosmic Microwave Background (CMB) using the kinetic model. Mathematically, the problem in concern is the inverse source problem for the linear Boltzmann equation with measurements on some Cauchy surface. We obtain two stable determination results for generic absorption c

Svenja Uhlemeyer, Julian Lienen, Eyke Hüllermeier, Hanno Gottschalk

For open world applications, deep neural networks (DNNs) need to be aware of previously unseen data and adaptable to evolving environments. Furthermore, it is desirable to detect and learn novel classes which are not included in the DNNs underlying set of semantic classes in an unsupervised fashion. The method proposed in this article builds upon anomaly det

Florian Emmrich, Lucía Gómez Álvarez, Hannes Strass

We present a tool for modelling and reasoning with knowledge from various diverse (and possibly conflicting) viewpoints. The theoretical underpinnings are provided by enhancing base logics by standpoints according to a recently introduced formalism that we also recall. The tool works by translating the standpoint-enhanced version of the description logic SRO

M. S. Lukashov, Yu. A. Simonov

The phenomenon of the deconfinement -- the spectacular drop of the colorelectric string tension at the critical temperature $T_c$ -- is studied within the method of field correlators (FCM) taking into account directly the contribution of the gluon condensate into the hadronic free energy. Using the resulting expressions for the free energy as a sum of the gl

Zhichao Han, Olga Fink, David S. Kammer

Interacting systems are ubiquitous in nature and engineering, ranging from particle dynamics in physics to functionally connected brain regions. These interacting systems can be modeled by graphs where edges correspond to the interactions between interactive entities. Revealing interaction laws is of fundamental importance but also particularly challenging d

Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves, Thomas Naselaris

Visual reconstruction algorithms are an interpretive tool that map brain activity to pixels. Past reconstruction algorithms employed brute-force search through a massive library to select candidate images that, when passed through an encoding model, accurately predict brain activity. Here, we use conditional generative diffusion models to extend and improve

Yibo Gao, Reuven Hodges, Alexander Yong

We prove a short, root-system uniform, combinatorial classification of Levi-spherical Schubert varieties for any generalized flag variety $G/B$ of finite Lie type. We apply this to the study of multiplicity-free decompositions of a Demazure module into irreducible representations of a Levi subgroup.

Lam Pham, Trang Le, Cam Le, Dat Ngo

In this paper, we present a deep learning based multimodal system for classifying daily life videos. To train the system, we propose a two-phase training strategy. In the first training phase (Phase I), we extract the audio and visual (image) data from the original video. We then train the audio data and the visual data with independent deep learning based m

Haoqian Zhang, Mahsa Bastankhah, Louis-Henri Merino, Vero Estrada-Galiñanes

Blockchain systems often rely on rationality assumptions for their security, expecting that nodes are motivated to maximize their profits. These systems thus design their protocols to incentivize nodes to execute the honest protocol but fail to consider out-of-band collusion. Existing works analyzing rationality assumptions are limited in their scope, either

Shaodong Wang, Qing Li, Wenli Zhang

Effectively representing medical concepts and patients is important for healthcare analytical applications. Representing medical concepts for healthcare analytical tasks requires incorporating medical domain knowledge and prior information from patient description data. Current methods, such as feature engineering and mapping medical concepts to standardized

Pangoth Santhosh Kumar, Garika Akshay

In low-resource computing contexts, such as smartphones and other tiny devices, Both deep learning and machine learning are being used in a lot of identification systems. as authentication techniques. The transparent, contactless, and non-invasive nature of these face recognition technologies driven by AI has led to their meteoric rise in popularity in recen

A. B. Drovosekov, N. M. Kreines, D. A. Ziganurov, A. V. Sitnikov

Films of metal-insulator nanogranular composites M$_x$D$_{100-x}$ with different composition and percentage of metal and dielectric phases (M = Fe, Co, CoFeB; D = Al$_2$O$_3$, SiO$_2$, LiNbO$_3$; x $\approx$ 15-70 at.%) are investigated by magnetic resonance in a wide range of frequencies (f = 7-37 GHz) and temperatures (T = 4.2-360 K). In addition to the us

Giovanni Apruzzese, Pavel Laskov, Johannes Schneider

Machine Learning (ML) has become a valuable asset to solve many real-world tasks. For Network Intrusion Detection (NID), however, scientific advances in ML are still seen with skepticism by practitioners. This disconnection is due to the intrinsically limited scope of research papers, many of which primarily aim to demonstrate new methods ``outperforming'' p

T. Karabassov, I. V. Bobkova, V. M. Silkin, B. G. Lvov

Recently the superconducting diode effect (SDE) has attracted a lot of attention due to new possibilities in the field of superconducting electronics. One of the possible realizations of the SDE is the implementation in superconducting hybrid structures. In this case the SDE is achieved by means of the proximity effect. However, the optimal conditions for th

Carolin Joy, Bikramaditya Mandal, Dulat Bostan, Dmitri Babikov

The extension of mixed quantum/classical theory (MQCT) to describe collisional energy transfer is developed for symmetric-top-rotor + linear-rotor system type and is applied to $ \rm ND_3 + \rm D_2 $. State-to-state transition cross sections are computed in a broad energy range for all possible processes: when both $ \rm ND_3$ and $ \rm D_2$ molecules are ex

Cameron Cianci

Error correction has long been suggested to extend the sensitivity of quantum sensors into the Heisenberg Limit. However, operations on logical qubits are only performed through universal gate sets consisting of finite-sized gates such as Clifford+T. Although these logical gate sets allow for universal quantum computation, the finite gate sizes present a pro

Lesley Frew, Michael L. Nelson, Michele C. Weigle

Webpages change over time, and web archives hold copies of historical versions of webpages. Users of web archives, such as journalists, want to find and view changes on webpages over time. However, the current search interfaces for web archives do not support this task. For the web archives that include a full-text search feature, multiple versions of the sa

Emmanuel Aboah Boateng, Jerry Bruce

Critical infrastructures like water treatment facilities and power plants depend on industrial control systems (ICS) for monitoring and control, making them vulnerable to cyber attacks and system malfunctions. Traditional ICS anomaly detection methods lack transparency and interpretability, which make it difficult for practitioners to understand and trust th

Achim Ahrens, Alessandra Stampi-Bombelli, Selina Kurer, Dominik Hangartner

Research underscores the role of naturalization in enhancing immigrants' socio-economic integration, yet application rates remain low. We estimate a policy rule for a letter-based information campaign encouraging newly eligible immigrants in Zurich, Switzerland, to naturalize. The policy rule assigns one out of three treatment letters to each individual, bas

Siyao Li, Giuseppe Caire

Sensing capabilities as an integral part of the network have been identified as a novel feature of sixth-generation (6G) wireless networks. As a key driver, millimeterwave (mmWave) communication largely boosts speed, capacities, and connectivity. In order to maximize the potential of mmWave communication, precise and fast beam acquisition (BA) is crucial, si

Geetanjali Bihani, Julia Taylor Rayz

Neural network-based decisions tend to be overconfident, where their raw outcome probabilities do not align with the true decision probabilities. Calibration of neural networks is an essential step towards more reliable deep learning frameworks. Prior metrics of calibration error primarily utilize crisp bin membership-based measures. This exacerbates skew in

Nazmul Hasan, Alamgir Kabir

Emergence of inorganic metal halide perovskites as multifunctional optoelectronic materials are due to their exceptional tunability in optoelectronic properties. This study sought to enhance the physical and mechanical properties of lead-free FrGeI3 perovskites by introducing transition metal dopants (Mn, Co, and Ni). First-principle calculations based densi

René Aid, Matteo Basei, Giorgio Ferrari

We consider a mean-field model of firms competing \`a la Cournot on a commodity market, where the commodity price is given in terms of a power inverse demand function of the industry-aggregate production. Investment is irreversible and production capacity depreciates at a constant rate. Production is subject to Gaussian productivity shocks, while large non-a

Hua Tong, Kuanren Qian, Eni Halilaj, Yongjie Jessica Zhang

High-quality mesh generation is the foundation of accurate finite element analysis. Due to the vast interior vertices search space and complex initial boundaries, mesh generation for complicated domains requires substantial manual processing and has long been considered the most challenging and time-consuming bottleneck of the entire modeling and analysis pr

Nikita Frolov, Bram Bijnens, Daniel Ruiz-Reynés, Lendert Gelens

Microtubules self-organize to form part of the cellular cytoskeleton. They give cells their shape and play a crucial role in cell division and intracellular transport. Strikingly, microtubules driven by motor proteins reorganize into stable mitotic/meiotic spindles with high spatial and temporal precision during successive cell division cycles. Although the

A. K. Bhuniya, Puja Sarkar

Based on the minimal and simple representations, we introduce two Jacobson-type Hoehnke radicals, m-radical and s-radical, of a semiring $S$. Every minimal (simple) $S$-semimodule is a quotient of $S$ by a regular right congruence (maximal) $\mu$ on $S$ such that $[0]_\mu$ is a maximal $\mu$-saturated right ideal in $S$. Thus the m(s)-radical becomes an inte

Yanfang Le, Jeongkeun Lee, Jeremias Blendin, Jiayi Chen

State-of-the-art congestion control algorithms for data centers alone do not cope well with transient congestion and high traffic bursts. To help with these, we revisit the concept of direct \emph{backward} feedback from switches and propose Back-to-Sender (BTS) signaling to many concurrent incast senders. Combining it with our novel approach to in-network c

Lei Gao, Ling Guan

The proliferation of machine learning (ML) has drawn unprecedented interest in the study of various multimedia contents such as text, image, audio and video, among others. Consequently, understanding and learning ML-based representations have taken center stage in knowledge discovery in intelligent multimedia research and applications. Nevertheless, the blac

James Taylor

A new definition of a real number is that it is a rule which says Yes or No based on whether the real number ought to be in a given rational interval. This is a teaser paper for formalizing, exploring, and generalizing this definition. The full exploration is given in the paper "Defining Real Numbers as Oracles".

Mohamed Debbagh

Structured output representation is a generative task explored in computer vision that often times requires the mapping of low dimensional features to high dimensional structured outputs. Losses in complex spatial information in deterministic approaches such as Convolutional Neural Networks (CNN) lead to uncertainties and ambiguous structures within a single

Francesco Andreucci, Stefano Lepri, Stefano Ruffo, Andrea Trombettoni

We perform a numerical study of transport properties of a one-dimensional chain with couplings decaying as an inverse power $r^{-(1+\sigma)}$ of the intersite distance $r$ and open boundary conditions, interacting with two heat reservoirs. Despite its simplicity, the model displays highly nontrivial features in the strong long-range regime, $-1<\sigma<0$. At

Reyan Ahmed, Mithun Ghosh, Kwang-Sung Jun, Stephen Kobourov

Graph neural networks are useful for learning problems, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem. We describe an approach for computing Steiner Trees by combining a graph neural network and Monte Carlo Tree Search. We first train a graph neural network that takes as input a pa

Cyril Closset, Osama Khlaif

We consider unitary SQCD, a three-dimensional $\mathcal{N}=2$ supersymmetric Chern-Simons-matter theory consisting of one $U(N_c)_{k, k+l N_c}$ vector multiplet coupled to $n_f$ fundamental and $n_a$ antifundamental chiral multiplets, where $k$ and $l$ parameterise generic CS levels for $U(N_c)=(SU(N_c)\times U(1))/\mathbb{Z}_{N_c}$. We study the moduli spac

Roee M. Francos, Alfred M. Bruckstein

Assume that inside an initial planar area there are smart mobile evaders attempting to avoid detection by a team of sweeping searching agents. All sweepers detect evaders with fan-shaped sensors, modeling the field of view of real cameras. Detection of all evaders is guaranteed with cooperative sweeping strategies, by setting requirements on sweepers' speed,

Tara Abrishami, Maria Chudnovsky, Yaqian Tang

Let $G$ be a Berge graph that has no odd prism and no antihole of length at least six as an induced subgraph. We show that every such graph $G$ with no balanced skew-partition is either complete or has an even pair.

Chaoming Song

Unraveling the complexities of random packing in three dimensions has long puzzled physicists. While both experiments and simulations consistently show a maximum density of 64 percent for tightly packed random spheres, we still lack an unambiguous and universally accepted definition of random packing. This paper introduces an innovative standpoint, depicting

Sergei Sakovich

We study the Lax integrability of a nonlinear system of two coupled second-order evolution equations introduced by Ibragimov and Shabat. For this system we find a zero-curvature representation with an essential parameter, construct an infinite integrable hierarchy which the system belongs to, and show that this hierarchy does not possess a recursion operator

Alexander V. Turbiner, Juan Carlos Lopez Vieyra, Miguel Ayala

It is shown that the $\mathfrak{gl}(3)$ polynomial integrable system, introduced by Sokolov-Turbiner in [arXiv:1409.7439], is equivalent to the $\mathfrak{gl}(3)$ quantum Euler-Arnold top in a constant magnetic field. Their Hamiltonian as well as their third-order integral can be rewritten in terms of $\mathfrak{gl}(3)$ algebra generators. In turn, all these

Fathima Zarin Faizal, Adway Girish, Manjesh Kumar Hanawal, Nikhil Karamchandani

We study the problem of best-arm identification in a distributed variant of the multi-armed bandit setting, with a central learner and multiple agents. Each agent is associated with an arm of the bandit, generating stochastic rewards following an unknown distribution. Further, each agent can communicate the observed rewards with the learner over a bit-constr

Osama Khalil

We prove that the geodesic flow on a geometrically finite locally symmetric space of negative curvature is exponentially mixing with respect to the Bowen-Margulis-Sullivan measure. The approach is based on constructing a suitable anisotropic Banach space on which the infinitesimal generator of the flow admits an essential spectral gap. A key step in the proo

Giuseppe Fabiano, Giulia Gubitosi, Fedele Lizzi, Luca Scala

We discuss the quantum Poincar\'e symmetries of the $\varrho$-Minkowski spacetime, a space characterised by an angular form of noncommutativity. We show that it is possible to give them both a bicrossproduct and a Drinfel'd twist structure. We also obtain a new noncommutative $\star$-product, which is cyclic with respect to the standard integral measure.

Piermarco Cannarsa, Masahiro Yamamoto

For solution $u(x,t)$ to degenearte parabolic equations in a bounded domain $\Omega$ with homogenous boundary condition, we consider backward problems in time: determine $u(\cdot,t_0)$ in $\Omega$ by $u(\cdot,T)$, where $t$ is the time variable and $0\le t_0 < T$. Our main results are conditional stability under boundedness assumptions on $u(\cdot,0)$. The p

C. Pallis

Models of induced-gravity inflation are formulated within Supergravity employing as inflaton the Higgs field which leads to a spontaneous breaking of a U(1)_{B-L} symmetry at Mgut=2x10^16 GeV. We use a renormalizable superpotential, fixed by a U(1) R symmetry, and logarithmic or semi-logarithmic Kahler potentials with integer prefactors which exhibit a quadr

Steven T. Piantadosi

I present a simple algorithm for enumerating the trees generated by a Context Free Grammar (CFG). The algorithm uses a pairing function to form a bijection between CFG derivations and natural numbers, so that trees can be uniquely decoded from counting. This provides a general way to number expressions in natural logical languages, and potentially can be ext

Taekyung Ki, Dongchan Min

In this paper, we present StyleLipSync, a style-based personalized lip-sync video generative model that can generate identity-agnostic lip-synchronizing video from arbitrary audio. To generate a video of arbitrary identities, we leverage expressive lip prior from the semantically rich latent space of a pre-trained StyleGAN, where we can also design a video c

Boxiang Wang, Yunan Wu, Chenglong Ye

Transfer learning is an essential tool for improving the performance of primary tasks by leveraging information from auxiliary data resources. In this work, we propose Adaptive Robust Transfer Learning (ART), a flexible pipeline of performing transfer learning with generic machine learning algorithms. We establish the non-asymptotic learning theory of ART, p

Oleksandr Pryshliak

To investigate the topological structure of Morse flows on the 2-disk we use the planar graphs as destinguished graph of the flow. We assume, that the flow is transversal to the boundary of the 2-disk. We give a list of all planar graph with at least 3 edges and describe all planar graphs with 4 edges. We use a list of spherical graph with at least 4 edges.

Kai Zhang, Xiaoqian Jiang

In the era of big data, there is an increasing need for healthcare providers, communities, and researchers to share data and collaborate to improve health outcomes, generate valuable insights, and advance research. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) is a federal law designed to protect sensitive health information by defi

Yinhuan Li, Tsz Chai Fung, Liang Peng, Linyi Qian

In non-life insurance, it is essential to understand the serial dynamics and dependence structure of the longitudinal insurance data before using them. Existing actuarial literature primarily focuses on modeling, which typically assumes a lack of serial dynamics and a pre-specified dependence structure of claims across multiple years. To fill in the research

Yasith Amarasinghe, Darshana Sandaruwan, Thilina Madusanka, Indika Perera

Energy Expenditure Estimation (EEE) is vital for maintaining weight, managing chronic diseases, achieving fitness goals, and improving overall health and well-being. Gold standard measurements for energy expenditure are expensive and time-consuming, hence limiting utility and adoption. Prior work has used wearable sensors for EEE as a workaround. Moreover, e

Vladimir L. Kalashnikov, Alexander Rudenkov, Evgeni Sorokin, Irina Sorokina

We present the adiabatic theory of dissipative solitons (DS) of complex cubic-quintic nonlinear Ginzburg-Landau equation (CQGLE). Solutions in the closed analytical form in the spectral domain have the shape of Rayleigh-Jeans distribution for a positive (normal) dispersion. The DS parametric space forms a two-dimensional (or three-dimensional for the complex

Qiong Chang, Xin Li, Yun Li, Jun Miyazaki

Sobel is one of the most popular edge detection operators used in image processing. To date, most users utilize the two-directional 3x3 Sobel operator as detectors because of its low computational cost and reasonable performance. Simultaneously, many studies have been conducted on using large multi-directional Sobel operators to satisfy their needs consideri

Long Li, Junwei Han, Ni Zhang, Nian Liu

Most previous co-salient object detection works mainly focus on extracting co-salient cues via mining the consistency relations across images while ignoring explicit exploration of background regions. In this paper, we propose a Discriminative co-saliency and background Mining Transformer framework (DMT) based on several economical multi-grained correlation

Rambabu Rajpoot, Amol R. Holkundkar, Navdeep Rana, Gopal Dixit

The present work introduces a robust way to generate attosecond pulses with tunable ellipticity via high-order harmonic generation by co-rotating $\omega - 2\omega$ bicircular laser fields. The total electric field of the laser fields exhibits an absence of rotational symmetry, which leads to the generation of high harmonics of the same helicity across a bro

Nick Brown, Maurice Jamieson, Joseph K. L. Lee

Funded by the UK ExCALIBUR H\&ES exascale programme, in early 2022 a RISC-V testbed for HPC was stood up to provide free access for scientific software developers to experiment with RISC-V for their workloads. Here we report on successes, challenges, and lessons learnt from this activity with a view to better understanding the suitability of RISC-V for HPC a

Efe A. Ok

We study the problem of extending an order-preserving real-valued Lipschitz map defined on a subset of a partially ordered metric space without increasing its Lipschitz constant and preserving its monotonicity. We show that a certain type of relation between the metric and order of the space, which we call radiality, is necessary and sufficient for such an e

Anqi Wang, Jiahua Dong, Lik-Hang Lee, Jiachuan Shen

3D shape generation techniques leveraging deep learning have garnered significant interest from both the computer vision and architectural design communities, promising to enrich the content in the virtual environment. However, research on virtual architectural design remains limited, particularly regarding designer-AI collaboration and deep learning-assiste

Liyuan Lin, Fangda Liu, Jingzhen Liu abd Luyang Yu

We study optimal reinsurance in the framework of stochastic game theory, in which there is an insurer and two reinsurers. A Stackelberg model is established to analyze the non-cooperative relationship between the insurer and reinsurers, where the insurer is considered as the follower and the reinsurers are considered as the leaders. The insurer is a price ta