March 2024 arXiv papers — page 26

Jose Garre Rubio, Andras Molnar, Yoshiko Ogata

We consider the classification problem of quantum spin chains invariant under local decomposable group actions, covering matrix product unitaries (MPUs), using an operator algebraic approach. We focus on finite group symmetries hosting both symmetric and symmetry broken phases. The local-decomposable group actions we consider have a 3-cocycle class of the sy

Gijs Wijngaard, Elia Formisano, Bruno L. Giordano, Michel Dumontier

Automated Audio Captioning is a multimodal task that aims to convert audio content into natural language. The assessment of audio captioning systems is typically based on quantitative metrics applied to text data. Previous studies have employed metrics derived from machine translation and image captioning to evaluate the quality of generated audio captions.

Igor Ivkić, Tobias Buhmann, Burkhard List, Clemens Gnauer

The landscape of traditional industrial manufacturing is undergoing a pivotal shift from resource-intensive production and long supply chains to more sustainable and regionally focused economies. In this evolving scenario, the move towards local, on-demand manufacturing is emerging as a remedy to the environmentally damaging practice of mass-producing produc

Sebastian Schlor, Frank Allgöwer

Encrypted dynamic controllers that operate for an unlimited time have been a challenging subject of research. The fundamental difficulty is the accumulation of errors and scaling factors in the internal state during operation. Bootstrapping, a technique commonly employed in fully homomorphic cryptosystems, can be used to avoid overflows in the controller sta

Inaam Ashraf, Janine Strotherm, Luca Hermes, Barbara Hammer

Water distribution systems (WDS) are an integral part of critical infrastructure which is pivotal to urban development. As 70% of the world's population will likely live in urban environments in 2050, efficient simulation and planning tools for WDS play a crucial role in reaching UN's sustainable developmental goal (SDG) 6 - "Clean water and sanitation for a

Yuxiang Zhao, Zhuomin Chai, Xun Jiang, Yibo Lin

IR drop on the power delivery network (PDN) is closely related to PDN's configuration and cell current consumption. As the integrated circuit (IC) design is growing larger, dynamic IR drop simulation becomes computationally unaffordable and machine learning based IR drop prediction has been explored as a promising solution. Although CNN-based methods have be

V. N. Obridko, A. S. Shibalova, D. D. Sokoloff

The phenomenon of the Gnevyshev gap was first identified in the solar-corona irradiance data (green line). Later, it was studied in the sunspot, coronal, and heliospheric data. We have investigated the Gnevyshev gap in the magnetic field data and have arrived at the conclusion that it reflects the behavior of the large-scale magnetic field. The Gnevyshev gap

Nicolò Cedola

Aims: we propose that the condition of relative motion between us and the objects that we observe in the Universe should generate relativistic aberration on the photons that such objects emit, varying the observed flux similarly to the cases of blazars and neutron stars, with instead a decrease of this radiative flux. Methods: we follow some important papers

Alex Haro, Eric Sandin Vidal

The goal of this paper is to provide a methodology to prove existence of (fiberwise hyperbolic) real-analytic invariant tori in real-analytic quasi-periodic skew-product dynamical systems that present nearly-invariant tori of the same characteristics. The methodology is based on the application of a Newton-Kantorovich theorem whose hypotheses are tested usin

Mohammadreza Amirian, Daniel Barco, Ivo Herzig, Frank-Peter Schilling

Deep learning based approaches have been used to improve image quality in cone-beam computed tomography (CBCT), a medical imaging technique often used in applications such as image-guided radiation therapy, implant dentistry or orthopaedics. In particular, while deep learning methods have been applied to reduce various types of CBCT image artifacts arising f

Ahmad Hafez, Frank J. Jiang, Karl H. Johansson, Amr Alanwar

In this paper, we propose reachability analysis using constrained polynomial logical zonotopes. We perform reachability analysis to compute the set of states that could be reached. To do this, we utilize a recently introduced set representation called polynomial logical zonotopes for performing computationally efficient and exact reachability analysis on log

Yow-Ren Chang, Seong-Min Kim, Young Jong Lee

Absolute quantity imaging of biomolecules on a single cell level is critical for measurement assurance in biosciences and bioindustries. While infrared (IR) transmission microscopy is a powerful label-free imaging modality capable of chemical quantification, its applicability to hydrated biological samples remains challenging due to the strong water absorpti

Zheng Zheng, Laurette S. Tuckerman, Tobias M. Schneider

Vertical thermal convection is a non-equilibrium system in which both buoyancy and shear forces play a role in driving the convective flow. Beyond the onset of convection, the driven dissipative system exhibits chaotic dynamics and turbulence. In a three-dimensional domain extended in both the vertical and the transverse dimensions, Gao et al. (2018) have ob

Paweł Duch

The Gross-Neveu model is a quantum field theory model of Dirac fermions in two dimensions with a quartic interaction term. Like Yang-Mills theory in four dimensions, the model is scaling critical (i.e. renormalizable but not super-renormalizable) and asymptotically free (i.e. its short-distance behavior is governed by the free theory). We give a new construc

Mattia Laurini, Irene Saccani, Stefano Ardizzoni, Luca Consolini

We consider a road network represented by a directed graph. We assume to collect many measurements of traffic flows on all the network arcs, or on a subset of them. We assume that the users are divided into different groups. Each group follows a different path. The flows of all user groups are modeled as a set of independent Poisson processes. Our focus is e

Jacob Mørk, Holger Severin Bovbjerg, Gergely Kiss, Zheng-Hua Tan

Voice assistants are now widely available, and to activate them a keyword spotting (KWS) algorithm is used. Modern KWS systems are mainly trained using supervised learning methods and require a large amount of labelled data to achieve a good performance. Leveraging unlabelled data through self-supervised learning (SSL) has been shown to increase the accuracy

Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer

Pretraining language models on large text corpora is a common practice in natural language processing. Fine-tuning of these models is then performed to achieve the best results on a variety of tasks. In this paper, we investigate the problem of catastrophic forgetting in transformer neural networks and question the common practice of fine-tuning with a flat

Joshua Kortum, Changyou Wang

In dimension three, the existence of global weak solutions to the axisymmetric simplified Ericksen-Leslie system without swirl is established. This is achieved by analyzing weak convergence of solutions of the axisymmetric Ginzburg-Landau approximated solutions as the penalization parameter $\varepsilon$ tends to zero. The proof relies on the one hand on the

Guillaume Vanderhaegen, Pascal Szriftgiser, Alexandre Kudlinski, Andrea Armaroli

We show how the recurrence phenomenon characteristic of the nonlinear stage of induced modulational instability in a passive fiber is affected by forcing. An additional linear amplification, even if extremely weak, induces separatrix crossing in correspondence of critical values of the gain around which the recurrence process considerably slows down, switchi

Anton V. Proskurnikov, Alexander Medvedev

The Impulsive Goodwin's Oscillator (IGO) is a mathematical model of a hybrid closed-loop system. It arises by closing a special kind of continuous linear positive time-invariant system with impulsive feedback, which employs both amplitude and frequency pulse modulation. The structure of IGO precludes the existence of equilibria, and all its solutions are osc

Pedro R. S. Antunes, Francisco Bento, David Krejcirik

Motivated by relativistic materials, we develop a numerical scheme to support existing or state new conjectures in the spectral optimisation of eigenvalues of the Dirac operator, subject to infinite-mass boundary conditions. We study the optimality of the regular polygon (respectively, disk) among all polygons of a given number of sides (respectively, arbitr

Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer

Over the last years, various sentence embedders have been an integral part in the success of current machine learning approaches to Natural Language Processing (NLP). Unfortunately, multiple sources have shown that the bias, inherent in the datasets upon which these embedding methods are trained, is learned by them. A variety of different approaches to remov

Jiayi Zhu, Qing Guo, Felix Juefei-Xu, Yihao Huang

Co-salient object detection (CoSOD) aims to identify the common and salient (usually in the foreground) regions across a given group of images. Although achieving significant progress, state-of-the-art CoSODs could be easily affected by some adversarial perturbations, leading to substantial accuracy reduction. The adversarial perturbations can mislead CoSODs

Oriel A. Humes, Cristina A. Thomas, Lauren E. McGraw

Red (S > 10%/0.1 micron) spectral slopes are common among Centaurs and trans-Neptunian objects (TNOs) in the outer solar system. Interior to and co-orbital with Jupiter, the red (S approx. = 10%/0.1 micron) slopes of D-type main-belt and Jupiter Trojan asteroids are thought to reflect their hypothesized shared origin with TNOs beyond the orbit of Jupiter. In

Balint Negyesi, Zhipeng Huang, Cornelis W. Oosterlee

We are concerned with high-dimensional coupled FBSDE systems approximated by the deep BSDE method of Han et al. (2018). It was shown by Han and Long (2020) that the errors induced by the deep BSDE method admit a posteriori estimate depending on the loss function, whenever the backward equation only couples into the forward diffusion through the Y process. We

Yanbing Zhang, Mengping Yang, Qin Zhou, Zhe Wang

Recent thrilling progress in large-scale text-to-image (T2I) models has unlocked unprecedented synthesis quality of AI-generated content (AIGC) including image generation, 3D and video composition. Further, personalized techniques enable appealing customized production of a novel concept given only several images as reference. However, an intriguing problem

Noor Ahmed, Anna Kukleva, Bernt Schiele

Few-Shot Class-Incremental Learning (FSCIL) introduces a paradigm in which the problem space expands with limited data. FSCIL methods inherently face the challenge of catastrophic forgetting as data arrives incrementally, making models susceptible to overwriting previously acquired knowledge. Moreover, given the scarcity of labeled samples available at any g

Ziyang Yang, Idris A. Eckley, Paul Fearnhead

We consider the challenge of efficiently detecting changes within a network of sensors, where we also need to minimise communication between sensors and the cloud. We propose an online, communication-efficient method to detect such changes. The procedure works by performing likelihood ratio tests at each time point, and two thresholds are chosen to filter un

Xiaofeng Cong, Jie Gui, Jing Zhang, Junming Hou

Existing research based on deep learning has extensively explored the problem of daytime image dehazing. However, few studies have considered the characteristics of nighttime hazy scenes. There are two distinctions between nighttime and daytime haze. First, there may be multiple active colored light sources with lower illumination intensity in nighttime scen

Philip Kenneweg, Sarah Schröder, Barbara Hammer

Pre training of language models on large text corpora is common practice in Natural Language Processing. Following, fine tuning of these models is performed to achieve the best results on a variety of tasks. In this paper we question the common practice of only adding a single output layer as a classification head on top of the network. We perform an AutoML

Siang Chen, Wei Tang, Pengwei Xie, Wenming Yang

Fast and robust object grasping in clutter is a crucial component of robotics. Most current works resort to the whole observed point cloud for 6-Dof grasp generation, ignoring the guidance information excavated from global semantics, thus limiting high-quality grasp generation and real-time performance. In this work, we show that the widely used heatmaps are

Zizhao Mo, Huanle Xu, Wing Cheong Lau

Ensuring the highest training throughput to maximize resource efficiency, while maintaining fairness among users, is critical for deep learning (DL) training in heterogeneous GPU clusters. However, current DL schedulers provide only limited fairness properties and suboptimal training throughput, impeding tenants from effectively leveraging heterogeneous reso

Viveka Erlandsson, Juan Souto

We study the distribution of the individual components of a random multicurve under the action of the mapping class group.

Jonathan Claros, Emanuel Gallo

We present new, simple analytical formulas to accurately describe light rays in spherically symmetric static spacetimes. These formulas extend those introduced by Beloborodov and refined by Poutanen for the Schwarzschild metric. Our enhanced formulas are designed to be applicable to a broader range of spacetimes, making them particularly valuable for describ

Kun Sun

In recent years, several influential computational models and metrics have been proposed to predict how humans comprehend and process sentence. One particularly promising approach is contextual semantic similarity. Inspired by the attention algorithm in Transformer and human memory mechanisms, this study proposes an ``attention-aware'' approach for computing

Haiyuan Feng, Rong-Jia Yang, Wei-Qiang Chen

We investigate the thin disk and shadow of Kerr-Sen black hole in Einstein-Maxwell-dilaton-axion gravity. The results reveal that as the dilaton parameter $r_2$ increase, the energy flux, the radiation temperature, the spectra luminosity, and the radiative efficiency of the disk all increase. By narrowing down the dilaton parameter range to $0\leqslant \frac

Sanjay More, Anil Khairnar, B. N. Waphare

S. K. Berberian raised the open problem ``Can every weakly Rickart $*$-ring be embedded in a Rickart $*$-ring? with preservation of right projections?" Berberian has given a partial solution to this problem. Khairnar and Waphare raised a similar problem for p.q.-Baer $*$-rings and gave a partial solution. In this paper, we give more general partial solutions

Zezhi Wang, Jin Zhu, Peng Chen, Huiyang Peng

Applying iterative solvers on sparsity-constrained optimization (SCO) requires tedious mathematical deduction and careful programming/debugging that hinders these solvers' broad impact. In the paper, the library skscope is introduced to overcome such an obstacle. With skscope, users can solve the SCO by just programming the objective function. The convenienc

Taku Yamagata, Raul Santos-Rodriguez

Reinforcement Learning (RL) has shown remarkable success in solving relatively complex tasks, yet the deployment of RL systems in real-world scenarios poses significant challenges related to safety and robustness. This paper aims to identify and further understand those challenges thorough the exploration of the main dimensions of the safe and robust RL land

Benjamin Sorkin, David S. Dean

Single-file diffusion is a paradigmatic model for the transport of Brownian colloidal particles in narrow one-dimensional channels, such as those found in certain porous media, where the particles cannot cross each other. We consider a system where a different external uniform potential is present to the right and left of an origin. For example, this is the

Axel Constant, Hannes Westermann, Bryan Wilson, Alex Kiefer

Legal autonomy - the lawful activity of artificial intelligence agents - can be achieved in one of two ways. It can be achieved either by imposing constraints on AI actors such as developers, deployers and users, and on AI resources such as data, or by imposing constraints on the range and scope of the impact that AI agents can have on the environment. The l

Reza Barzegar Nozari, Mahdi Divsalar, Sepehr Akbarzadeh Abkenar, Mohammadreza Fadavi Amiri

The majority of existing recommender systems rely on user ratings, which are limited by the lack of user collaboration and the sparsity problem. To address these issues, this study proposes a behavior-based recommender system that leverages customers' natural behaviors, such as browsing and clicking, on e-commerce platforms. The proposed recommendation syste

Yichi Zhang, Zhihao Duan, Yuning Huang, Fengqing Zhu

Recent studies reveal a significant theoretical link between variational autoencoders (VAEs) and rate-distortion theory, notably in utilizing VAEs to estimate the theoretical upper bound of the information rate-distortion function of images. Such estimated theoretical bounds substantially exceed the performance of existing neural image codecs (NICs). To narr

Grzegorz Adamski, Sylwia Antoniuk, Małgorzata Bednarska-Bzdęga, Dennis Clemens

For a positive integer $n$ and a tree $T_n$ on $n$ vertices, we consider an unbiased Waiter-Client game $\textrm{WC}(n,T_n)$ played on the complete graph~$K_n$, in which Waiter's goal is to force Client to build a copy of $T_n$. We prove that for every constant $c<1/3$, if $\Delta(T_n)\le cn$ and $n$ is sufficiently large, then Waiter has a winning strategy

Eiki Kagohashi, Ryotaku Suzuki, Shinya Tomizawa

Using the exact solution that describes multi-centered rotating black holes, recently discovered by Teo and Wan, we investigate the innermost stable circular orbit (ISCO) for massive particles and the circular orbit for massless particles moving around a spinning black hole binary. We assume equal masses $M_1 = M_2=m$ and equal spin angular momenta $|J_1| =

Thanh-Thien Le, Linh The Nguyen, Dat Quoc Nguyen

We introduce PhoWhisper in five versions for Vietnamese automatic speech recognition. PhoWhisper's robustness is achieved through fine-tuning the Whisper model on an 844-hour dataset that encompasses diverse Vietnamese accents. Our experimental study demonstrates state-of-the-art performances of PhoWhisper on benchmark Vietnamese ASR datasets. We have open-s

Noam Berger, Yuki Tokushige

We study limit laws for simple random walks on supercritical long-range percolation clusters on the integer lattice. For the long range percolation model, the probability that two vertices are connected behaves asymptotically as a negative power of distance between them. We prove that the scaling limit of simple random walk on the infinite component converge

Vincent Goumarre, Yasith Amarasinghe, Martin Lahn Henriksen, Mogens Hinge

With the development of terahertz time-domain spectroscopy, methods have been proposed to precisely estimate the thickness, refractive index, and attenuation coefficient of a sample. In this article, we propose a new method to compute these parameters. In this method, the attenuation is expressed in function of the refractive index. The theoretical unwrapped

Elizabeth Lee, Jens Chluba

Future observations of the Sunyaev-Zeldovich (SZ) effect promise ever improving measurements in terms of both sensitivity and angular resolution. As such, it is increasingly relevant to model `higher-order' contributions to the SZ effect. This work examines the effects of high-energy non-thermal electron distributions and those of anisotropic electron and ph

Zi-Chang Zhang, Yong Tang

Dark matter (DM) constitutes the predominant portion of matter in our universe. Despite compelling evidence, the precise characteristics of DM remain elusive. Among the leading DM candidates are weakly-interacting massive particles, which may clump into steep concentrations around the central black holes of galaxies. However, DM profiles of the resulting den

Xiangyu Cui, Jianjun Gao, Lingjie Kong

This study addresses limited attention allocation in a stochastic linear quadratic system with multiplicative noise. Our approach enables strategic resource allocation to enhance noise estimation and improve control decisions. We provide analytical optimal control and propose a numerical method for optimal attention allocation. Additionally, we apply our ffn

Benedikt Diederichs, Frank Filbir, Patricia Römer

The problem of phase retrieval has many applications in the field of optical imaging. Motivated by imaging experiments with biological specimens, we primarily consider the setting of low-dose illumination where Poisson noise plays the dominant role. In this paper, we discuss gradient descent algorithms based on different loss functions adapted to data affect

G. Molchan

Let $V_M,(m_0)$ be the number of m>M aftershocks caused by $m_0$ event. We consider the $V_M,(m_0)$ distribution within epidemic-type seismicity models, ETAS(F). These models include the Gutenberg-Richter law for magnitude and Utsu law for average productivity of m0, but differ in the type of F distribution for the number v(m0) of direct aftershocks. The cla

Reza Abbasi, Mohammad Samiei, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah

Vision-language models, such as CLIP, have shown promising Out-of-Distribution (OoD) generalization under various types of distribution shifts. Recent studies attempted to investigate the leading cause of this capability. In this work, we follow the same path, but focus on a specific type of OoD data - images with novel compositions of attribute-object pairs

Elias Goldsztejn, Ronen I. Brafman

Classical navigation planners can provide safe navigation, albeit often suboptimally and with hindered human norm compliance. ML-based, contemporary autonomous navigation algorithms can imitate more natural and humancompliant navigation, but usually require large and realistic datasets and do not always provide safety guarantees. We present an approach that

Kazuya Fujimoto, Tomohiro Sasamoto

Emergence of hydrodynamics in quantum many-body systems has recently garnered growing interest. The recent experiment of ultracold atoms [J. F. Wienand {\it et al.}, Nat. Phys. (2024), doi:10.1038/s41567-024-02611-z] studied emergent hydrodynamics in hard-core bosons using a bipartite fluctuation, which quantifies how the particle number fluctuates in a subs

Zihan Zhou, Shuchao Li

Given a graph $G,$ a subset of vertices is called a maximum dissociation set of $G$ if it induces a subgraph with vertex degree at most 1, and the subset has maximum cardinality. The cardinality of a maximum dissociation set is called the dissociation number of $G$. The adjacency matrix and the degree diagonal matrix of $G$ are denoted by $A(G)$ and $D(G),$

Victor Galaz, Megan Meacham

The Amazon Basin and the Latin America and Caribbean (LAC) region stands at a critical juncture, grappling with pressing environmental challenges while holding immense potential for transformative change through innovative solutions. This report illuminates the diverse landscape of social-ecological issues, technological advancements, community-led initiativ

Herbert Egger, Felix Engertsberger, Bogdan Radu

We consider the convergence of iterative solvers for problems of nonlinear magnetostatics. Using the equivalence to an underlying minimization problem, we can establish global linear convergence of a large class of methods, including the damped Newton-method, fixed-point iteration, and the Kacanov iteration, which can all be interpreted as generalized gradie

Philip Kenneweg, Tristan Kenneweg, Barbara Hammer

In recent studies, line search methods have shown significant improvements in the performance of traditional stochastic gradient descent techniques, eliminating the need for a specific learning rate schedule. In this paper, we identify existing issues in state-of-the-art line search methods, propose enhancements, and rigorously evaluate their effectiveness.

Guy Ohad, Michal Hartstein, Tim Gould, Jeffrey B. Neaton

The ionization potential of molecular chains is well-known to be a tunable nano-scale property that exhibits clear quantum confinement effects. State-of-the-art methods can accurately predict the ionization potential in the small molecule limit and in the solid-state limit, but for intermediate, nano-sized systems prediction of the evolution of the electroni

Jeremy E. Cohen, Valentin Leplat

Regularized nonnegative low-rank approximations, such as sparse Nonnegative Matrix Factorization or sparse Nonnegative Tucker Decomposition, form an important branch of dimensionality reduction models known for their enhanced interpretability. From a practical perspective, however, selecting appropriate regularizers and regularization coefficients, as well a

Hannes Warnhofer, Samuel T. Spencer, Alison M. W. Mitchell

This research note concerns the application of deep-learning-based multi-view-imaging techniques to data from the H.E.S.S. Imaging Atmospheric Cherenkov Telescope array. We find that the earlier the fusion of layer information from different views takes place in the neural network, the better our model performs with this data. Our analysis shows that the poi

Miika Rasola, Mikko Möttönen

We propose a recipe for demonstrating an autonomous quantum heat engine where the working fluid consists of a harmonic oscillator, the frequency of which is tuned by a driving mode. The working fluid is coupled two heat reservoirs each exhibiting a peaked power spectrum, a hot reservoir peaked at a higher frequency than the cold reservoir. Provided that the

Aissam Djahnine, Alexandre Popoff, Emilien Jupin-Delevaux, Vincent Cottin

Unsupervised pathology detection can be implemented by training a model on healthy data only and measuring the deviation from the training set upon inference, for example with CNN-based feature extraction and one-class classifiers, or reconstruction-score-based methods such as AEs, GANs and Diffusion models. Normalizing Flows (NF) have the ability to directl

George B. Mertzios, Hendrik Molter, Nils Morawietz, Paul G. Spirakis

In this paper, we study the complexity of the periodic temporal graph realization problem with respect to upper bounds on the fastest path durations among its vertices. This constraint with respect to upper bounds appears naturally in transportation network design applications where, for example, a road network is given, and the goal is to appropriately sche

Qiran Zou, Shangyuan Yuan, Shian Du, Yu Wang

We study a challenging task: text-to-motion synthesis, aiming to generate motions that align with textual descriptions and exhibit coordinated movements. Currently, the part-based methods introduce part partition into the motion synthesis process to achieve finer-grained generation. However, these methods encounter challenges such as the lack of coordination

Julian Jack

Bolzano and Cantor were the first mathematicians to make significant attempts to measure the size (numerosity) of different infinite collections. They differed in their methodological approaches, with Cantor's prevailing. This led to the foundation of the theory of sets as well as Cantor's transfinite arithmetic. This paper argues that Bolzano's conjecture i

Eva Casotti, Elena Poli, Lauritz Klaus, Andrea Litvinov

Supersolids are states of matter that spontaneously break two continuous symmetries: translational invariance due to the appearance of a crystal structure and phase invariance due to phase locking of single-particle wave functions, responsible for superfluid phenomena. While originally predicted to be present in solid helium, ultracold quantum gases provided

Ehsan Lari, Reza Arablouei, Naveen K. D. Venkategowda, Stefan Werner

We introduce a distributed algorithm, termed noise-robust distributed maximum consensus (RD-MC), for estimating the maximum value within a multi-agent network in the presence of noisy communication links. Our approach entails redefining the maximum consensus problem as a distributed optimization problem, allowing a solution using the alternating direction me

Matteo Acclavio, Fabrizio Montesi, Marco Peressotti

Dynamic logic is a powerful approach to reasoning about programs and their executions, obtained by extending classical logic with modalities that can express program executions as formulas. However, the use of dynamic logic in the setting of concurrency has proved problematic because of the challenge of capturing interleaving. This challenge stems from the f

Giuseppe Zappalà

We study the Hilbert function and the graded Betti numbers of almost complete intersection artinian algebras. We show that that every Hilbert function of a complete intersection artinian algebra is the Hilbert function of an almost complete intersection algebra. In codimension $3$ we focus on almost complete intersection artinian algebras whose Hilbert funct

Philip Kenneweg, Leonardo Galli, Tristan Kenneweg, Barbara Hammer

Recent works have shown that line search methods greatly increase performance of traditional stochastic gradient descent methods on a variety of datasets and architectures [1], [2]. In this work we succeed in extending line search methods to the novel and highly popular Transformer architecture and dataset domains in natural language processing. More specifi

Jean Douçot, Gabriele Rembado, Matteo Tamiozzo

We construct moduli stacks of wild Riemann surfaces in the (pure) untwisted case, for any complex reductive structure group, and we define the corresponding (pure) wild mapping class groups.

Felix Virgo, Fei Cheng, Lis Kanashiro Pereira, Masayuki Asahara

We propose a voting-driven semi-supervised approach to automatically acquire the typical duration of an event and use it as pseudo-labeled data. The human evaluation demonstrates that our pseudo labels exhibit surprisingly high accuracy and balanced coverage. In the temporal commonsense QA task, experimental results show that using only pseudo examples of 40

Myungkou Shin

Treatment effect heterogeneity is of a great concern when evaluating policy impact: "is the treatment Pareto-improving?", "what is the proportion of people who are better off under the treatment?", etc. However, even in the simple case of a binary random treatment, existing analysis has been mostly limited to an average treatment effect or a quantile treatme

J Morava

We propose a toy model for symmetry-breaking or bubbling, in terms of cobordism of manifolds with circle actions free on a possible boundary. The Swan-Tate cohomology $t_\T E$ of a complex-oriented $E_\infty$ ring-spectrum $E$ is the extension of a Hopf algebra by its dual, which provides an algebraic rigidification of geometric interest. This note reviews t

Florian Domingo, Herbi K. Dreiner, Dominik Köhler, Saurabh Nangia

Proton decay, although unobserved so far, is a natural expectation when attempting to explain the baryon asymmetry of the universe. $p\to K^+\bar{\nu}$ or $p\to K^+\tilde{\chi}_1^0$, with $\tilde{\chi}_1^0$ a light exotic neutral particle, represent possible decay channels achievable in models of physics beyond the Standard Model, such as the MSSM with trili

Chang Bian, Beth Philips, Tim Cootes, Martin Fergie

Computational analysis of multiplexed immunofluorescence histology data is emerging as an important method for understanding the tumour micro-environment in cancer. This work presents HEMIT, a dataset designed for translating Hematoxylin and Eosin (H&E) sections to multiplex-immunohistochemistry (mIHC) images, featuring DAPI, CD3, and panCK markers. Distinct

Diogo Arsénio, Haroune Houamed, Belkacem Said--Houari

The evolution of an electrically conducting imcompressible fluid with nonconstant density can be described by a set of equations combining the continuity, momentum and Maxwell's equations; altogether known as the inhomogeneous Navier--Stokes--Maxwell system. In this paper, we focus on the global well-posedness of these equations in two dimensions. Specifical

A. A. Molavi Choobini, S. S. Ghaffari-Oskooei, M. Shahmansouri, F. M. Aghamir

The exploration of Terahertz (THz) waves has captivated researchers across diverse scientific disciplines such as physics, spectroscopy, chemistry, biology, and engineering, driven by the myriad applications these waves offer. Within this expansive landscape, the development of efficient and reliable THz sources stands as a paramount objective. In the pursui

Dylan Johnston, Diego Martín Duro, Dmitriy Rumynin

Global representation rings were discovered by Sarah Witherspoon in 1995 and the Knutson Index was introduced by the second author in 2022. In the present paper we introduce the Knutson Index for general commutative rings and study it for Burnside rings and global representation rings. We also introduce the global table of a finite group, that encompasses bo

Yixin Cao, Ling Gai, Jingyi Liu, Jianxin Wang

Given an ordering of the vertices of a graph, the cost of covering an edge is the smaller number of its two ends. The minimum sum vertex cover problem asks for an ordering that minimizes the total cost of covering all edges. We consider parameterized complexity of this problem, using the largest cost~$k$ of covering a single edge as the parameter. Note that

Anusuiya Baishya, Apurba Das

The notion of pre-Poisson algebras was introduced by Aguiar in his study of zinbiel algebras and pre-Lie algebras. In this paper, we first introduce NS-Poisson algebras as a generalization of both Poisson algebras and pre-Poisson algebras. An NS-Poisson algebra has an associated sub-adjacent Poisson algebra. We show that a Nijenhuis operator and a twisted Ro

Romana Boiger, Sergey V. Churakov, Ignacio Ballester Llagaria, Georg Kosakowski

Deep subsurface exploration is important for mining, oil and gas industries, as well as in the assessment of geological units for the disposal of chemical or nuclear waste, or the viability of geothermal energy systems. Typically, detailed examinations of subsurface formations or units are performed on cuttings or core materials extracted during drilling cam

Sokratis J. Anagnostopoulos, Juan Diego Toscano, Nikolaos Stergiopulos, George Em Karniadakis

We investigate the learning dynamics of fully-connected neural networks through the lens of the neural gradient signal-to-noise ratio (SNR), examining the behavior of first-order optimizers in non-convex objectives. Interpreting the drift/diffusion phases as proposed in the information bottleneck theory, we identify a third phase termed &#34;diffusion equili

Jianshu Guo, Wenhao Chai, Jie Deng, Hsiang-Wei Huang

Recent text-to-image (T2I) models have benefited from large-scale and high-quality data, demonstrating impressive performance. However, these T2I models still struggle to produce images that are aesthetically pleasing, geometrically accurate, faithful to text, and of good low-level quality. We present VersaT2I, a versatile training framework that can boost t

M. Kravtsov, A. L. Shilov, Y. Yang, T. Pryadilin

Light incident upon materials can induce changes in their electrical conductivity, a phenomenon referred to as photoresistance. In semiconductors, the photoresistance is negative, as light-induced promotion of electrons across the band gap enhances the number of charge carriers participating in transport. In superconductors, the photoresistance is positive b

Kamil Dudka, Petr Muller, Petr Peringer, Veronika Šoková

This chapter, which is an extended and revised version of the conference paper 'Predator: Byte-Precise Verification of Low-Level List Manipulation', concentrates on a detailed description of the algorithms behind the Predator shape analyser based on abstract interpretation and symbolic memory graphs. Predator is particularly suited for formal analysis and ve

Ayoub Karine, Thibault Napoléon, Maher Jridi

This paper proposes a new knowledge distillation method tailored for image semantic segmentation, termed Intra- and Inter-Class Knowledge Distillation (I2CKD). The focus of this method is on capturing and transferring knowledge between the intermediate layers of teacher (cumbersome model) and student (compact model). For knowledge extraction, we exploit clas

Pedro J. Vaz, Gabriela Schütz, Carlos Guerrero, Pedro J. S. Cardoso

Reference Evapotranspiration (ET0) is a key parameter for designing smart irrigation scheduling, since it is related by a coefficient to the water needs of a crop. The United Nations Food and Agriculture Organization, proposed a standard method for ET0 computation (FAO56PM), based on the parameterization of the Penman-Monteith equation, that is widely adopte

Chentao Yue, Changyang She, Branka Vucetic, Yonghui Li

This paper investigates guesswork over ordered statistics and formulates the achievable guesswork complexity of ordered statistics decoding (OSD) in binary additive white Gaussian noise (AWGN) channels. The achievable guesswork complexity is defined as the number of test error patterns (TEPs) processed by OSD immediately upon finding the correct codeword est

Matteo Gallone, Sandra Lucente

In this paper we explore the relationships between Calvino's memos and Mathematics. In the first part, we discuss how Lightness, Quickness, Exactitude, Visibility, Multiplicity are present in the mathematical language, reasoning and in the work of the mathematician. In addiction, we follow a similar path for the topics of Calvino's lecture of which we only k

Guido Klein, Pierre Guetschel, Gianluigi Silvestri, Michael Tangermann

Data scarcity in the brain-computer interface field can be alleviated through the use of generative models, specifically diffusion models. While diffusion models have previously been successfully applied to electroencephalogram (EEG) data, existing models lack flexibility w.r.t.~sampling or require alternative representations of the EEG data. To overcome the

Saurav Islam, Emma Steinebronn, Kaijie Yang, Bimal Neupane

We use a concerted theory-experiment effort to investigate the formation of chiral real space spin texture when the archetypal Dirac semimetal Cd$_3$As$_2$ is interfaced with In$_{1-x}$Mn$_x$As, a ferromagnetic semiconductor with perpendicular magnetic anisotropy. Our calculations reveal a nonzero off-diagonal spin susceptibility in the Cd$_3$As$_2$ layer du

Dominique M. -A. Meyer

Cosmic rays are highly energetic messengers propagating in magnetized plasma, which are, possibly but not exclusively, accelerated at astrophysical shocks. Amongst the variety of astrophysical objects presenting shocks, the huge circumstellar stellar wind bubbles forming around very massive stars, are potential non thermal emitters. We present the 1D magneto

C. F. J. Flipse, T. J. N. van Stralen, D. M. Kepaptsoglou, Q. M. Ramasse

The strange metal phase is characteristic for the $T$-linear dc resistivity behaviour over a large $T$-range. The effect of the strength of the charge-paramagnon interactions on the charge fluctuations in optimally doped and underdoped regions of Bi$_2$Sr$_2$CaCu$_2$O$_{8+y}$ (Bi-2212) may shine light on the anomalous behaviour of the optical conductivity re

David Romero-Organvidez, Jose A. Galindo, David Benavides

Feature models have become a de facto standard for representing variability in software product lines. UVL (Universal Variability Language) is a language which expresses the features, dependencies, and constraints between them. This language is written in plain text and follows a syntactic structure that needs to be processed by a parser. This parser is soft

Gavin A. L. Coleman

Free-floating planets are a new class of planets recently discovered. These planets don't orbit within stellar systems, instead living a nomadic life within the galaxy. How such objects formed remains elusive. Numerous works have explored mechanisms to form such objects, but have not yet provided predictions on their distributions that could differentiate be

Yidan Wang, Zhaochun Ren, Weiwei Sun, Jiyuan Yang

Generative models have emerged as a promising utility to enhance recommender systems. It is essential to model both item content and user-item collaborative interactions in a unified generative framework for better recommendation. Although some existing large language model (LLM)-based methods contribute to fusing content information and collaborative signal