March 2024 arXiv papers — page 155

Peidong Li, Wancheng Shen, Qihao Huang, Dixiao Cui

Camera-based Bird's-Eye-View (BEV) perception often struggles between adopting 3D-to-2D or 2D-to-3D view transformation (VT). The 3D-to-2D VT typically employs resource-intensive Transformer to establish robust correspondences between 3D and 2D features, while the 2D-to-3D VT utilizes the Lift-Splat-Shoot (LSS) pipeline for real-time application, potentially

Geoffrey Beck, Charles-Edouard Bréhier, Laurent Chevillard, Ricardo Grande

Motivated by the modeling of the spatial structure of the velocity field of three-dimensional turbulent flows, and the phenomenology of cascade phenomena, a linear dynamics has been recently proposed able to generate high velocity gradients from a smooth-in-space forcing term. It is based on a linear Partial Differential Equation (PDE) stirred by an additive

Nanami Hashimoto, Emma Hagens, Arkady Zgonnikov, Maria Luce Lupetti

Unprecedented possibilities of quadruped robots have driven much research on the technical aspects of these robots. However, the social perception and acceptability of quadruped robots so far remain poorly understood. This work investigates whether the way we design quadruped robots' behaviors can affect people's perception of safety in interactions with the

Cristian Morasso, Daniele Meli, Yann Divet, Salvatore Sessa

Hyper-redundant Robotic Manipulators (HRMs) offer great dexterity and flexibility of operation, but solving Inverse Kinematics (IK) is challenging. In this work, we introduce VO-FABRIK, an algorithm combining Forward and Backward Reaching Inverse Kinematics (FABRIK) for repeatable deterministic IK computation, and an approach inspired from velocity obstacles

Vincenzo Mainieri, Richard I. Anderson, Jarle Brinchmann, Andrea Cimatti

The Wide-field Spectroscopic Telescope (WST) is proposed as a new facility dedicated to the efficient delivery of spectroscopic surveys. This white paper summarises the initial concept as well as the corresponding science cases. WST will feature simultaneous operation of a large field-of-view (3 sq. degree), a high multiplex (20,000) multi-object spectrograp

Francois-Baptiste Cartiaux, Frederic Legoll, Alex Libal, Julien Reygner

This article addresses the probabilistic nature of fatigue life in structures subjected to cyclic loading with variable amplitude. Drawing on the formalisation of Miner's cumulative damage rule that we introduced in the recent article [Cartiaux, Ehrlacher, Legoll, Libal and Reygner, Prob. Eng. Mech. 2023], we apply our methodology to estimate the survival pr

Zhengrui Guo, Jiabo Ma, Yingxue Xu, Yihui Wang

Histopathology serves as the gold standard in cancer diagnosis, with clinical reports being vital in interpreting and understanding this process, guiding cancer treatment and patient care. The automation of histopathology report generation with deep learning stands to significantly enhance clinical efficiency and lessen the labor-intensive, time-consuming bu

Nathan Buskulic, Jalal Fadili, Yvain Quéau

Advanced machine learning methods, and more prominently neural networks, have become standard to solve inverse problems over the last years. However, the theoretical recovery guarantees of such methods are still scarce and difficult to achieve. Only recently did unsupervised methods such as Deep Image Prior (DIP) get equipped with convergence and recovery gu

Purna Kar, Jordan J. Bird, Yangang Xing, Alexander Sumich

Biophilia is an innate love for living things and nature itself that has been associated with a positive impact on mental health and well-being. This study explores the application of deep learning methods for the classification of Biophilic artwork, in order to learn and explain the different Biophilic characteristics present in a visual representation of a

Vikas Tokala, Eric Grinstein, Mike Brookes, Simon Doclo

Studies have shown that in noisy acoustic environments, providing binaural signals to the user of an assistive listening device may improve speech intelligibility and spatial awareness. This paper presents a binaural speech enhancement method using a complex convolutional neural network with an encoder-decoder architecture and a complex multi-head attention

Péter L. Várkonyi

In a recent paper published in Nature, Y.I. Sobolev et al. introduced the concept of trajectoids: convex, rigid objects, which roll without slip or spin on a flat plane along a prescribed periodic, unbounded planar path. A geometric construction method applicable to many paths was introduced, and the theory was experimentally verified using objects rolling d

Siyuan Niu, Aida Todri-Sanial, Nicholas T. Bronn

Dynamical decoupling (DD) is one of the simplest error suppression methods, aiming to enhance the coherence of qubits in open quantum systems. Moreover, DD has demonstrated effectiveness in reducing coherent crosstalk, one major error source in near-term quantum hardware, which manifests from two types of interactions. Static crosstalk exists in various hard

Gabriela Barenboim, P. Ko, Wan-il Park

We propose a novel minimal scenario which simultaneously addresses the following theoretical/cosmological/phenomenological puzzles: (i) the origin of scales, (ii) primordial inflation, (iii) matter-antimatter asymmetry, (iv) tiny neutrino masses, (v) dark matter, and (vi) the strong CP-problem. Exact scale-symmetry was assumed. A global $U(1)_{\rm PQ}$-symme

Alexander Gunasekera, Nicholas Lee, David P. Tew

Properly spin-adapted coupled-cluster theory for general open-shell configurations remains an active area of research in electronic structure theory. In this contribution we examine Lindgren's normal-ordered exponential ansatz to correlate specific spin states using spin-free excitation operators, with the aid of automatic equation generation software. We pr

Yu Han, Ziwei Long, Yanting Zhang, Jin Wu

Correspondence matching plays a crucial role in numerous robotics applications. In comparison to conventional hand-crafted methods and recent data-driven approaches, there is significant interest in plug-and-play algorithms that make full use of pre-trained backbone networks for multi-scale feature extraction and leverage hierarchical refinement strategies t

Matthew Yancey

Borodin and Kostochka proved that for $d_2 \geq 2d_1+2$ and a graph $G$ where every subgraph $H$ satisfies $$ e(H) < \left(2 - \frac{d_2+2}{(d_1+2)(d_2+1)}\right)n(H) + \frac{1}{d_2+1} $$ has a vertex partition $V(G) = V_1 \cup V_2$ such that $G[V_i]$ has maximum degree at most $d_i$ for each $i$. We show that under the same conditions we can additionally co

Krishnendu Chatterjee, Amir Kafshdar Goharshady, Ehsan Kafshdar Goharshady, Mehrdad Karrabi

We study the classical problem of verifying programs with respect to formal specifications given in the linear temporal logic (LTL). We first present novel sound and complete witnesses for LTL verification over imperative programs. Our witnesses are applicable to both verification (proving) and refutation (finding bugs) settings. We then consider LTL formula

Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson

We propose training fitted Q-iteration with log-loss (FQI-log) for batch reinforcement learning (RL). We show that the number of samples needed to learn a near-optimal policy with FQI-log scales with the accumulated cost of the optimal policy, which is zero in problems where acting optimally achieves the goal and incurs no cost. In doing so, we provide a gen

Cristiana Tiago, Andrew Gilbert, Ahmed S. Beela, Svein Arne Aase

Due to privacy issues and limited amount of publicly available labeled datasets in the domain of medical imaging, we propose an image generation pipeline to synthesize 3D echocardiographic images with corresponding ground truth labels, to alleviate the need for data collection and for laborious and error-prone human labeling of images for subsequent Deep Lea

Aravind Puthirath Balan, Aditya Kumar, Patrick Reiser, Joseph Vas

The exchange bias phenomenon, inherent in exchange-coupled ferromagnetic and antiferromagnetic systems, has intrigued researchers for decades. Van der Waals materials, with their layered structure, provide an optimal platform for probing such physical phenomena. However, achieving a facile and effective means to manipulate exchange bias in van der Waals hete

Soumya Ranjan Padhi, Ashirbad Padhan, Sanchayan Banerjee, Tapan Mishra

We study the effect of quasiperiodic and periodic onsite potentials in a Hatano-Nelson model with next-nearest-neighbour hopping. By considering a non-reciprocal next-nearest-neighbour hopping and a quasiperiodic onsite potential under periodic boundary conditions, we show a breakdown of the typical correspondence between the delocalization-localization and

Xavier Bou, Gabriele Facciolo, Rafael Grompone von Gioi, Jean-Michel Morel

The goal of this paper is to perform object detection in satellite imagery with only a few examples, thus enabling users to specify any object class with minimal annotation. To this end, we explore recent methods and ideas from open-vocabulary detection for the remote sensing domain. We develop a few-shot object detector based on a traditional two-stage arch

Mahyar Gohari, Paolo Bestagini, Sergio Benini, Nicola Adami

In the domain of music production and audio processing, the implementation of automatic pitch correction of the singing voice, also known as Auto-Tune, has significantly transformed the landscape of vocal performance. While auto-tuning technology has offered musicians the ability to tune their vocal pitches and achieve a desired level of precision, its use h

Salome Kazeminia, Max Joosten, Dragan Bosnacki, Carsten Marr

Automated disease diagnosis using medical image analysis relies on deep learning, often requiring large labeled datasets for supervised model training. Diseases like Acute Myeloid Leukemia (AML) pose challenges due to scarce and costly annotations on a single-cell level. Multiple Instance Learning (MIL) addresses weakly labeled scenarios but necessitates pow

Will Ma, Calum MacRury, Jingwei Zhang

We study the Network Revenue Management (NRM) and Online Combinatorial Auctions (OCA) problems, in which products composed of up to L resources are allocated in an online fashion. We take a randomized rounding approach to these problems, employing the modern tool of Online Contention Resolution Schemes (OCRS) and their random-order analogues (RCRS). However

Ardy Dedase

This paper explores the architecture of Software as a Service (SaaS) platforms, emphasizing scalability and maintainability. SaaS, a flexible software distribution model suitable for individuals and organizations, has become prevalent with the advent of Cloud services. This paper aims to provide a high-level design reference for establishing a scalable and m

Samuel Johnston

Using recent results of Battistella, Nabijou, Ranganathan and the author, we compare candidate mirror algebras associated with certain log Calabi-Yau pairs constructed by Gross-Siebert using log Gromov-Witten theory and Tseng-You using orbifold Gromov- Witten theory of root stacks. Although the structure constants used to defined these mirror algebras do not

Michael Chow, Hee Oh

We describe multiple correlations of Jordan and Cartan spectra for any finite number of Anosov representations of a finitely generated group. This extends our previous work on correlations of length and displacement spectra for rank one convex cocompact representations. Examples include correlations of the Hilbert length spectra for convex projective structu

Alexander N. Rudenko, Mikhail I. Katsnelson

Among a huge variety of known two-dimensional materials, some of them have anisotropic crystal structures; examples include so different systems as a few-layer black phoshphorus (phosphorene), beryllium nitride BeN$_4$, van der Waals magnet CrSBr, rhenium dichalgogenides ReX$_2$. As a consequence, their optical and electronic properties turn out to be highly

Carlo Zaccardi, Pasquale Valentini, Luigi Ippoliti, Alexandra M. Schmidt

This paper proposes a new approach to address the problem of unmeasured confounding in spatial designs. Spatial confounding occurs when some confounding variables are unobserved and not included in the model, leading to distorted inferential results about the effect of an exposure on an outcome. We show the relationship existing between the confounding bias

Umberto De Ambroggio, Tamás Makai, Konstantinos Panagiotou, Annika Steibel

We consider a synchronous process of particles moving on the vertices of a graph $G$, introduced by Cooper, McDowell, Radzik, Rivera and Shiraga (2018). Initially, $M$ particles are placed on a vertex of $G$. In subsequent time steps, all particles that are located on a vertex inhabited by at least two particles jump independently to a neighbour chosen unifo

Marcin Maździarz, Szymon Nosewicz

This paper focuses on the development of the atomistic framework for determining the lower scale mechanical parameters of single components of a metal matrix composite for final application to a micromechanical damage model. Here, the deformation and failure behavior of NiAl-Al$_2$O$_3$ interfaces and their components, metal and ceramic, are analyzed in dept

Linwei Chen, Lin Gu, Ying Fu

Dilated convolution, which expands the receptive field by inserting gaps between its consecutive elements, is widely employed in computer vision. In this study, we propose three strategies to improve individual phases of dilated convolution from the view of spectrum analysis. Departing from the conventional practice of fixing a global dilation rate as a hype

Oleksii Molodchyk, Timm Faulwasser

Generalizations and variations of the fundamental lemma by Willems et al. are an active topic of recent research. In this note, we explore and formalize the links between kernel regression and some known nonlinear extensions of the fundamental lemma. Applying a transformation to the usual linear equation in Hankel matrices, we arrive at an alternative implic

Lorenzo Sforni, Guido Carnevale, Ivano Notarnicola, Giuseppe Notarstefano

In this paper, we investigate a data-driven framework to solve Linear Quadratic Regulator (LQR) problems when the dynamics is unknown, with the additional challenge of providing stability certificates for the overall learning and control scheme. Specifically, in the proposed on-policy learning framework, the control input is applied to the actual (unknown) l

Patrik L. Ferrari, Sabrina Gernholt

We consider the totally asymmetric simple exclusion process on $\Z$ with step initial condition and with the presence of a rightward-moving wall that prevents the particles from jumping. This model was first studied in [Borodin-Bufetov-Ferrari'21]. We extend their work by determining the limiting distribution of a tagged particle in the case where the wall h

Seyed Parsa Neshaei, Yasaman Boreshban, Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel

Transformer-based models have made remarkable advancements in various NLP areas. Nevertheless, these models often exhibit vulnerabilities when confronted with adversarial attacks. In this paper, we explore the effect of quantization on the robustness of Transformer-based models. Quantization usually involves mapping a high-precision real number to a lower-pr

Andrew Newman, Marta Pavelka

We consider the hypergraph Tur\'an problem of determining $\mathrm{ex}(n, S^d)$, the maximum number of facets in a $d$-dimensional simplicial complex on $n$ vertices that does not contain a simplicial $d$-sphere (a homeomorph of $S^d$) as a subcomplex. We show that if there is an affirmative answer to a question of Gromov about sphere enumeration in high dim

Cheng Li, Michael Allison, Sushil Atreya, Shawn Brueshaber

The temperature structure of a giant planet was traditionally thought to be an adiabat assuming convective mixing homogenizes entropy. The only in-situ measurement made by the Galileo Probe detected a near-adiabatic temperature structure within one of Jupiter's 5$\mu$m hot spots with small but definite local departures from adiabaticity. We analyze Juno's mi

M. Llerena, R. Amorín, L. Pentericci, P. Arrabal Haro

Extreme emission line galaxies (EELGs) are typically characterized by high equivalent widths (EWs) which are driven by elevated specific star formation rates (sSFR) in low-mass galaxies with subsolar metallicities and little dust. Such extreme systems are rare in the local universe, but the number density of EELGs increases with redshift. Such starburst gala

Andreas Sperlich, Klaus H. Eckstein, Florian Oberndorfer, Bernd K. Sturzda

Nanoscale semiconductors with isolated spin impurities have been touted as promising materials for their potential use at the intersection of quantum, spin, and information technologies. Electron paramagnetic resonance (EPR) studies of spins in semiconducting carbon nanotubes have overwhelmingly focused on spins more strongly localized by $\rm sp^3$-type lat

Paul Bastide, Claire Hilaire, Eileen Robinson

The central path problem is a variation on the single facility location problem. The aim is to find, in a given connected graph $G$, a path $P$ minimizing its eccentricity, which is the maximal distance from $P$ to any vertex of the graph $G$. The path eccentricity of $G$ is the minimal eccentricity achievable over all paths in $G$. In this article we consid

Jacopo Lenti, Fabrizio Silvestri, Gianmarco De Francisci Morales

Despite the frequent use of agent-based models (ABMs) for studying social phenomena, parameter estimation remains a challenge, often relying on costly simulation-based heuristics. This work uses variational inference to estimate the parameters of an opinion dynamics ABM, by transforming the estimation problem into an optimization task that can be solved dire

A. Akbar, M. Kozbiál, L. Elson, A. Meraki

In this work, we present a comprehensive and comparative analysis of two detection modalities, i.e., polarization rotation and absorption measurement of light, for a double resonance alignment based optical magnetometer (DRAM). We derive algebraic expressions for magnetometry signals based on multipole moments description. Experiments are carried out using a

P. Hofman, F. P. van der Meer, L. J. Sluys

A numerical framework for simulating progressive failure under high-cycle fatigue loading is validated against experiments of composite quasi-isotropic open-hole laminates. Transverse matrix cracking and delamination are modeled with a mixed-mode fatigue cohesive zone model, covering crack initiation and propagation. Furthermore, XFEM is used for simulating

Markus Hausmann, Stefan Schwede

We calculate the representation-graded Bredon homology rings of all elementary abelian 2-groups with coefficients in the constant mod-2 Mackey functor. We exhibit minimal presentations for these rings as quotients of the polynomial algebra on the pre-Euler and inverse Thom classes of all nontrivial characters, subject to an explicit finite list of relations

Summer A. J. McLaughlin, James R. Mullaney, Stuart P. Littlefair

A key feature of active galactic nuclei (AGN) is their variability across all wavelengths. Typically, AGN vary by a few tenths of a magnitude or more over periods lasting from hours to years. By contrast, extreme variability of AGN -- large luminosity changes that are a significant departure from the baseline variability -- are known as AGN flares. These eve

Maleka Khatun, Md Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid

Brain-related diseases are more sensitive than other diseases due to several factors, including the complexity of surgical procedures, high costs, and other challenges. Alzheimer's disease is a common brain disorder that causes memory loss and the shrinking of brain cells. Early detection is critical for providing proper treatment to patients. However, ident

Jiajie Fan, Amal Trigui, Thomas Bäck, Hao Wang

A great interest has arisen in using Deep Generative Models (DGM) for generative design. When assessing the quality of the generated designs, human designers focus more on structural plausibility, e.g., no missing component, rather than visual artifacts, e.g., noises or blurriness. Meanwhile, commonly used metrics such as Fr\'echet Inception Distance (FID) m

H. Keshvarikhojasteh, J. P. W. Pluim, M. Veta

In computational pathology, random sampling of patches during training of Multiple Instance Learning (MIL) methods is computationally efficient and serves as a regularization strategy. Despite its promising benefits, questions concerning performance trends for varying sample sizes and its influence on model interpretability remain. Addressing these, we reach

Zhi Zhang, Chenyu Ma, Saleh Soudijani, Sadegh Soudjani

A novel data-driven method for formal verification is proposed to study complex systems operating in safety-critical domains. The proposed approach is able to formally verify discrete-time stochastic dynamical systems against temporal logic specifications only using observation samples and without the knowledge of the model, and provide a probabilistic guara

Aleksandr Murach, Tetiana Zinchenko

We study an extended Sobolev scale for smooth vector bundles over a smooth closed manifold. This scale is built on the base of inner product distribution spaces of generalized smoothness given by an arbitrary positive function OR-varying at infinity. We show that this scale is obtained by the quadratic interpolation (with a function parameter) between inner

Nilay Ekiz Yazici, Ayse Borat

In this paper, we introduce the higher analogues of contiguity distance and its relations with simplicial Lusternik-Schnirelmann category and discrete topological complexity. Also we study the effects of geometric realisation and barycentric subdivision in the sense that how the geometric realisation of the simplicial maps and the induced simplicial maps on

Farid Kenas

The Riemann Hypothesis, originally proposed by the eminent mathematician Bernard Riemann in 1859, remains one of the most profound challenges in number theory. It posits that all non-trivial zeros of the Riemann zeta function {\zeta}(s) are concentrated precisely along the critical line where the real part equals 1/2. In this paper, our aim is to present an

Junsu Kim, Yunhoe Ku, Jihyeon Kim, Junuk Cha

In the field of Class Incremental Object Detection (CIOD), creating models that can continuously learn like humans is a major challenge. Pseudo-labeling methods, although initially powerful, struggle with multi-scenario incremental learning due to their tendency to forget past knowledge. To overcome this, we introduce a new approach called Vision-Language Mo

Daniel Elsender, Matthew R. Bate

We present an implicit method for solving the diffusion equation for the evolution of the dust fraction in the terminal velocity approximation using dust-as-mixture smoothed particle hydrodynamics (SPH). The numerical scheme involves casting the dust diffusion equation into implicit form, rearranging into its resolvent cubic equation and solving analytically

Enoch Solomon, Abraham Woubie

The state-of-the-art face recognition systems are typically trained on a single computer, utilizing extensive image datasets collected from various number of users. However, these datasets often contain sensitive personal information that users may hesitate to disclose. To address potential privacy concerns, we explore the application of federated learning,

Giona Casiraghi, Georges Andres

Changes in the timescales at which complex systems evolve are essential to predicting critical transitions and catastrophic failures. Disentangling the timescales of the dynamics governing complex systems remains a key challenge. With this study, we introduce an integrated Bayesian framework based on temporal network models to address this challenge. We focu

Maria Waheed, Michael Milford, Xiaojun Zhai, Maria Fasli

Visual Place Recognition has been the subject of many endeavours utilizing different ensemble approaches to improve VPR performance. Ideas like multi-process fusion, Fly-Inspired Voting Units, SwitchHit or Switch-Fuse involve combining different VPR techniques together, utilizing different strategies. However, a major aspect often common to many of these str

Giulio Pecorella, Sergio Polidoro, Cecilia Vernia

We study a nonlinear partial differential equation that arises when introducing inertial effects in the Kuramoto model. Based on the known theory of degenerate Kolmogorov operators, we prove existence, uniqueness and a priori estimates of the solution to the relevant Cauchy problem. Moreover, a stable numerical operator, which is consistent with the degenera

Yasuyuki Ozeki

As a highly sensitive vibrational imaging method, stimulated Raman scattering (SRS) microscopy is finding various applications, while its theoretical treatment seems still under development. Here we present a theoretical estimation of spontaneous Raman signal and SRS signal from Raman scattering cross section, irrespective of the numerical aperture of the ob

Erik Ostrowski, Muhammad Shafique

When deploying neural networks in real-life situations, the size and computational effort are often the limiting factors. This is especially true in environments where big, expensive hardware is not affordable, like in embedded medical devices, where budgets are often tight. State-of-the-art proposed multiple different lightweight solutions for such use case

Kang Chuangchuang, Liu Guilai, Wang Zhuo, Yu Shizhuo

A left-Alia algebra is a vector space together with a bilinear map satisfying symmetric Jocobi identity. Motivated by invariant theory, we first construct a class of left-Alia algebras induced by twisted derivations. Then, we introduce the notion of Manin triples and bialgebras of left-Alia algebras. Via specific matched pairs of left-Alia algebras, we figur

Wei Zhou, Heike Adel, Hendrik Schuff, Ngoc Thang Vu

Attribution scores indicate the importance of different input parts and can, thus, explain model behaviour. Currently, prompt-based models are gaining popularity, i.a., due to their easier adaptability in low-resource settings. However, the quality of attribution scores extracted from prompt-based models has not been investigated yet. In this work, we addres

Blaise Delmotte, Florencio Balboa Usabiaga

Phoretic colloids self-propel thanks to surface flows generated in response to surface gradients (thermal, electrical, or chemical), that are self-induced and/or generated by other particles. Here we present a scalable and versatile framework to model chemical and hydrodynamic interactions in large suspensions of arbitrarily shaped phoretic particles, accoun

Wen Xia, Jorik Jooken, Jan Goedgebeur, Shenwei Huang

Given two graphs $H_1$ and $H_2$, a graph is $(H_1,H_2)$-free if it contains no induced subgraph isomorphic to $H_1$ nor $H_2$. A graph $G$ is $k$-vertex-critical if every proper induced subgraph of $G$ has chromatic number less than $k$, but $G$ has chromatic number $k$. The study of $k$-vertex-critical graphs for specific graph classes is an important topi

Haodong Tian, Ashish Patel, Stephen Burgess

Mendelian randomization is an instrumental variable method that utilizes genetic information to investigate the causal effect of a modifiable exposure on an outcome. In most cases, the exposure changes over time. Understanding the time-varying causal effect of the exposure can yield detailed insights into mechanistic effects and the potential impact of publi

Sangbin Lee, Jongheon Lee, Ada S. Y. Poon, Sanghoek Kim

Microwave ablation is a therapeutic procedure to eliminate abnormal tissue within a body selectively. There are two types of ablations; the thermal one aims to raise the temperature at the target, while the non-thermal one induces a temporarily high electric field at the target to disrupt cellular membrane integrity. This work identifies the fundamental boun

Kartik Chandra, Katherine M. Collins, Will Crichton, Tony Chen

Often, a good explanation for a program's unexpected behavior is a bug in the programmer's code. But sometimes, an even better explanation is a bug in the programmer's mental model of the language or API they are using. Instead of merely debugging our current code ("giving the programmer a fish"), what if our tools could directly debug our mental models ("te

Weichen Gu, Xiang Li

We prove an entropy version of van der Corput's difference theorem: the entropy of a sequence is equal to the entropy of its differences. This reveals a potential correspondence between the theory of uniform distribution mod 1 and entropy. As applications, we establish the corresponding entropy versions for several other results on uniform distribution.

Morten Nissov, Nikhil Khedekar, Kostas Alexis

Enabling autonomous robots to operate robustly in challenging environments is necessary in a future with increased autonomy. For many autonomous systems, estimation and odometry remains a single point of failure, from which it can often be difficult, if not impossible, to recover. As such robust odometry solutions are of key importance. In this work a method

Valérie Chavez-Demoulin, Linda Mhalla

In this work, we summarize the state-of-the-art methods in causal inference for extremes. In a non-exhaustive way, we start by describing an extremal approach to quantile treatment effect where the treatment has an impact on the tail of the outcome. Then, we delve into two primary causal structures for extremes, offering in-depth insights into their identifi

Shuaiyi Li, Yang Deng, Deng Cai, Hongyuan Lu

As the typical retraining paradigm is unacceptably time- and resource-consuming, researchers are turning to model editing to find an effective way that supports both consecutive and batch scenarios to edit the model behavior directly. Despite all these practical expectations, existing model editing methods fail to realize all of them. Furthermore, the memory

Ji Zhang, Yiran Ding, Zixin Liu

3D occupancy prediction based on multi-sensor fusion,crucial for a reliable autonomous driving system, enables fine-grained understanding of 3D scenes. Previous fusion-based 3D occupancy predictions relied on depth estimation for processing 2D image features. However, depth estimation is an ill-posed problem, hindering the accuracy and robustness of these me

Songpeng Pei, Marina Orio, Xiaowan Zhang

The old nova and intermediate polar (IP) GK Persei underwent one of its recurrent dwarf nova (DN) outbursts in 2018. We proposed monitoring it in UV and X-rays with the Neil Gehrels Swift Observatory, starting less than six days after the eruption, until 16 days after the eruption ended. For the first time we could follow the decay to minimum light UV and X-

Yushan Zhang, Bastian Wandt, Maria Magnusson, Michael Felsberg

Scene flow estimation is an essential ingredient for a variety of real-world applications, especially for autonomous agents, such as self-driving cars and robots. While recent scene flow estimation approaches achieve a reasonable accuracy, their applicability to real-world systems additionally benefits from a reliability measure. Aiming at improving accuracy

Yiding Liu, Jingjing Wang, Jiamin Luo, Tao Zeng

Aspect Sentiment Understanding (ASU) in interactive scenarios (e.g., Question-Answering and Dialogue) has attracted ever-more interest in recent years and achieved important progresses. However, existing studies on interactive ASU largely ignore the coreference issue for opinion targets (i.e., aspects), while this phenomenon is ubiquitous in interactive scen

Juan I. Pisula, Katarzyna Bozek

The first step in Multiple Instance Learning (MIL) algorithms for Whole Slide Image (WSI) classification consists of tiling the input image into smaller patches and computing their feature vectors produced by a pre-trained feature extractor model. Feature extractor models that were pre-trained with supervision on ImageNet have proven to transfer well to this

David Bradley-Williams, Pablo Cubides Kovacsics, Immanuel Halupczok

If a reduced bivariate polynomial is quasi-homogeneous, then its discriminant is a monomial. Over fields of characteristic $0$, we show that if one adds another simple condition, this becomes an equivalence. We also give a third equivalent condition that is stated geometrically.

Hongliang Jiang

We consider a family of Argyres-Douglas theories, which are 4D $\mathcal N=2$ strongly coupled superconformal field theories (SCFTs) but share many features with 4D $\mathcal N=4 $ super-Yang-Mills theories. In particular, the two central charges of these theories are the same, namely $a=c$. We derive a simple and illuminating formula for the Schur index of

K. J. Dzahini, F. Rinaldi, C. W. Royer, D. Zeffiro

Optimizing a function without using derivatives is a challenging paradigm, that precludes from using classical algorithms from nonlinear optimization, and may thus seem intractable other than by using heuristics. Nevertheless, the field of derivative-free optimization has succeeded in producing algorithms that do not rely on derivatives and yet are endowed w

Florian Euchner, Janina Sanzi, Marcus Henninger, Stephan ten Brink

Wireless channel models are a commonly used tool for the development of wireless telecommunication systems and standards. The currently prevailing geometry-based stochastic channel models (GSCMs) were manually specified for certain environments in a manual process requiring extensive domain knowledge, on the basis of channel measurement campaigns. By taking

Jiayang Jiang, Ming Zhang, Aosheng Gu, R. J. Dwayne Miller

We propose a quantum tomography (QT) approach to retrieve the temporally evolving reduced density matrix in elecotronic state basis, where the populations and coherence between ground state and excited state are reconstructed from the ultrafast electron diffraction signal. In order to showcase the capability of the proposed QT approach, we simulate the nucle

Mark L. Lewis, Shannon M. Tefft

Define the Ducci function $D: \mathbb{Z}_m^n \to \mathbb{Z}_m^n$ so \[D(x_1,x_2, ...,x_n)=(x_1+x_2 \;\text{mod} \; m, x_2+x_3 \; \text{mod} \; m, ..., x_n+x_1 \; \text{mod} \; m).\] Call $\{D^{\alpha}(\mathbf{u})\}_{\alpha=0}^{\infty}$ the Ducci sequence of $\mathbf{u}$. Because $\mathbb{Z}_m^n$ is finite, every Ducci sequence will enter a cycle. In this pap

Jingxiao Chen, Ziqin Gong, Minghuan Liu, Jun Wang

Many real-world problems can be formulated as a constrained Traveling Salesman Problem (TSP). However, the constraints are always complex and numerous, making the TSPs challenging to solve. When the number of complicated constraints grows, it is time-consuming for traditional heuristic algorithms to avoid illegitimate outcomes. Learning-based methods provide

Daniel A. Kiefer, Sylvain Mezil, Claire Prada

Guided wave dispersion is commonly assessed by Fourier analysis of the field along a line, resulting in frequency-wavenumber dispersion curves. In anisotropic plates, a point source can generate multiple dispersion branches pertaining to the same modal surface, which arise due to the angle between the power flux and the wave vector. We show that this phenome

Ayesha Tooba Khan, Deepak Joshi, Biswarup Mukherjee

Purpose: The purpose of this study was to investigate the psychophysical understanding of the slip stimulus. We emphasized that the perception of slip and its characteristics, such as slip distance and slip speed depend on the interaction between slip direction, slip distance as well as slip speed. Methods: We developed a novel slip induction device to simul

Amir Shakouri, Henk J. van Waarde, M. Kanat Camlibel

This paper studies sets of matrices induced by quadratic inequalities. In particular, the center and radius of a smallest ball containing the set, called a Chebyshev center and the Chebyshev radius, are studied. In addition, this work studies the diameter of the set, which is the farthest distance between any two elements of the set. Closed-form solutions ar

Bozhen Hu, Cheng Tan, Lirong Wu, Jiangbin Zheng

Protein representation learning plays a crucial role in understanding the structure and function of proteins, which are essential biomolecules involved in various biological processes. In recent years, deep learning has emerged as a powerful tool for protein modeling due to its ability to learn complex patterns and representations from large-scale protein da

Zihao Wang, Anji Liu, Haowei Lin, Jiaqi Li

We explore how iterative revising a chain of thoughts with the help of information retrieval significantly improves large language models' reasoning and generation ability in long-horizon generation tasks, while hugely mitigating hallucination. In particular, the proposed method -- *retrieval-augmented thoughts* (RAT) -- revises each thought step one by one

Emilie Mai Elkiær

We show that, for a countable discrete group $\Gamma$, property $(\mathrm{T}_{L^p})$ of Bader, Furman, Gelander and Monod is equivalent to the property that, whenever an $L^p$-representation of $\Gamma$ admits a net of almost invariant unit vectors, it has a non-zero invariant vector. Central in the proof is to show that the closure of the group of $\mathbb{

CMS Collaboration

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}$ = 13 TeV collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by Hidden Valley models with a new, confining force with a large 't Hooft coupling. In events with boo

Sebastian Borówka, Mateusz Mazelanik, Wojciech Wasilewski, Michał Parniak

The coupling of Rydberg vapour medium to both microwave and optical fields allows harnessing the merits of all-optical detection, e.g. weak disruption of the measured field and invulnerability to extremely strong fields, owing to the lack of a conventional antenna in the detector. However, the highest sensitivity in this approach is typically achieved by int

Silvia Santos, Lino Marques, Pedro Neto

The disposal and recycling of electronic waste (e-waste) is a global challenge. The disassembly of components is a crucial step towards an efficient recycling process, avoiding the destructive methods. Although most disassembly work is still done manually due to the diversity and complexity of components, there is a growing interest in developing automated m

Anne Tryphosa Kamatham, Kavita Sharma, Srikumar Venkataraman, Biswarup Mukherjee

Sonomyography (SMG) is a non-invasive technique that uses ultrasound imaging to detect the dynamic activity of muscles. Wearable SMG systems have recently gained popularity due to their potential as human-computer interfaces for their superior performance compared to conventional methods. This paper demonstrates real-time positional proportional control of m

Jinyang Li, Nan Huo, Yan Gao, Jiayi Shi

Interactive Data Analysis, the collaboration between humans and LLM agents, enables real-time data exploration for informed decision-making. The challenges and costs of collecting realistic interactive logs for data analysis hinder the quantitative evaluation of Large Language Model (LLM) agents in this task. To mitigate this issue, we introduce Tapilot-Cros

Miguel Neves, Laura Duarte, Pedro Neto

An effective human-robot collaborative process results in the reduction of the operator's workload, promoting a more efficient, productive, safer and less error-prone working environment. However, the implementation of collaborative robots in industry is still challenging. In this work, we compare manual and robot-assisted assembly processes to evaluate the

Matías I. Caruso, Javier Fernández, Cora Tori, Marcela Zuccalli

We study a type of forced discrete mechanical system $(Q,L_d,f_d)$ -- that we name of Routh type -- whose (discrete) time-flow preserves a symplectic structure on $Q\times Q$. That structure arises as the pullback via the forced discrete Legendre transform of the canonical symplectic structure on $T^*Q$ modified by a "magnetic term". One example of this type

Jiange Yang, Bei Liu, Jianlong Fu, Bocheng Pan

Robotic motor control necessitates the ability to predict the dynamics of environments and interaction objects. However, advanced self-supervised pre-trained visual representations in robotic motor control, leveraging large-scale egocentric videos, often focus solely on learning the static content features. This neglects the crucial temporal motion clues in

Sotaro Takeshita, Tommaso Green, Ines Reinig, Kai Eckert

Extensive efforts in the past have been directed toward the development of summarization datasets. However, a predominant number of these resources have been (semi)-automatically generated, typically through web data crawling, resulting in subpar resources for training and evaluating summarization systems, a quality compromise that is arguably due to the sub