October 2022 arXiv papers — page 79

Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, Ehsan Kamalloo

MIRACL (Multilingual Information Retrieval Across a Continuum of Languages) is a multilingual dataset we have built for the WSDM 2023 Cup challenge that focuses on ad hoc retrieval across 18 different languages, which collectively encompass over three billion native speakers around the world. These languages have diverse typologies, originate from many diffe

Édgar Roldán, Izaak Neri, Raphael Chetrite, Shamik Gupta

We review the theory of martingales as applied to stochastic thermodynamics and stochastic processes in physics more generally.

V. L. Martinez-Consentino, J. E. Amaro, P. R. Casale, I. Ruiz Simo

An extended superscaling analysis of quasielastic electron scattering data is proposed by parametrizing the scaling function as the sum of a symmetric function corresponding to the emission of a single particle plus a contribution from the phase space of two-particle emission. The phase space of two-particle emission (2p2h) is multiplied by a q-dependent par

Sören Arlt, Carlos Ruiz-Gonzalez, Mario Krenn

Entanglement is a crucial resource for quantum technologies ranging from quantum communication to quantum-enhanced measurements and computation. Finding experimental setups for these tasks is a conceptual challenge for human scientists due to the counterintuitive behavior of multiparticle interference and the enormously large combinatorial search space. Rece

Carlos Ruiz-Gonzalez, Sören Arlt, Jan Petermann, Sharareh Sayyad

Photons are the physical system of choice for performing experimental tests of the foundations of quantum mechanics. Furthermore, photonic quantum technology is a main player in the second quantum revolution, promising the development of better sensors, secure communications, and quantum-enhanced computation. These endeavors require generating specific quant

Bakytzhan Kurmanbek, Elina Robeva

In this paper we study the high-dimensional super-resolution imaging problem. Here we are given an image of a number of point sources of light whose locations and intensities are unknown. The image is pixelized and is blurred by a known point-spread function arising from the imaging device. We encode the unknown point sources and their intensities via a nonn

Jinchuan Cui, Xiaoya Li

Airplane refueling problem is a nonlinear unconstrained optimization problem with $n!$ feasible solutions. Given a fleet of $n$ airplanes with mid-air refueling technique, the question is to find the best refueling policy to make the last remaining airplane travel the farthest. In order to solve airplane refueling problem, we proposed the definition of seque

Edoardo Altamura, Scott T. Kay, Richard G. Bower, Matthieu Schaller

Recent high-resolution cosmological hydrodynamic simulations run with a variety of codes systematically predict large amounts of entropy in the intra-cluster medium at low redshift, leading to flat entropy profiles and a suppressed cool-core population. This prediction is at odds with X-ray observations of groups and clusters. We use a new implementation of

Harry Goodhew

The Bootstrap approach to calculating cosmological correlators relies on a well motivated ansatz. It is typical in the literature to assume that correlators are rational functions as this greatly increases our constraining power. However, this has only previously been demonstrated for some specific theories. In this paper we find a set of assumptions which w

Jeffrey M. Shainline, Bryce A. Primavera, Saeed Khan

Superconducting optoelectronic loop neurons are a class of circuits potentially conducive to networks for large-scale artificial cognition. These circuits employ superconducting components including single-photon detectors, Josephson junctions, and transformers to achieve neuromorphic functions. To date, all simulations of loop neurons have used first-princi

Daniela A. Wiepert, Bradley A. Malin, Joseph R. Duffy, Rene L. Utianski

Large, curated datasets are required to leverage speech-based tools in healthcare. These are costly to produce, resulting in increased interest in data sharing. As speech can potentially identify speakers (i.e., voiceprints), sharing recordings raises privacy concerns. We examine the re-identification risk for speech recordings, without reference to demograp

Louis Schatzki, Martin Larocca, Quynh T. Nguyen, Frederic Sauvage

Despite the great promise of quantum machine learning models, there are several challenges one must overcome before unlocking their full potential. For instance, models based on quantum neural networks (QNNs) can suffer from excessive local minima and barren plateaus in their training landscapes. Recently, the nascent field of geometric quantum machine learn

Joseph MacManus

We present an algorithm which decides whether a given quasiconvex residually finite subgroup $H$ of a hyperbolic group $G$ is associated with a splitting. The methods developed also provide algorithms for computing the number of filtered ends $\tilde e(G,H)$ of $H$ in $G$ under certain hypotheses, and give a new straightforward algorithm for computing the nu

Jugurta Montalvão

An approach is proposed to quantify, in bits of information, the actual relevance of analogies in analogy tests. The main component of this approach is a softaccuracy estimator that also yields entropy estimates with compensated biases. Experimental results obtained with pre-trained GloVe 300-D vectors and two public analogy test sets show that proximity hin

Talant Talipov

We calculate the Gromov-Hausdorff distance between vertex sets of regular polygons endowed with the round metric. We give a full answer for the case of n- and m-gons with m divisible by n. Also, we calculate all distances to 2-gons and 3-gons

Artem Finenko

We describe the development of machine-learned potentials of atmospheric gases with flexible monomers for molecular simulations. A recently suggested permutationally invariant polynomial neural network (PIP-NN) approach is utilized to represent the full-dimensional two-body component of the dimer energy. To ensure the asymptotic zero-interaction limit, a tai

Daniel A. P. Oliveira, David Martins de Matos

The computer vision community has seen a shift from convolutional-based to pure transformer architectures for both image and video tasks. Training a transformer from zero for these tasks usually requires a lot of data and computational resources. Video Swin Transformer (VST) is a pure-transformer model developed for video classification which achieves state-

Xue Han, Kang Xue, X. X. Yi

As a new quantum state, topological insulators have become the focus of condensed matter and material science. The open system research of topological insulators has aroused the interest of many researchers. Recently, many aspects, especially experimental aspects, have been developed rapidly, such as prediction and discovery of many novel quantum effects and

Theodore D. Drivas, Daniel Ginsberg, Hezekiah Grayer

We study the equilibrium temperature distribution in a model for strongly magnetized plasmas in dimension two and higher. Provided the magnetic field is sufficiently structured (integrable in the sense that it is fibered by co-dimension one invariant tori, on most of which the field lines ergodically wander) and the effective thermal diffusivity transverse t

Ivan Danilenko

The affine Grassmannian associated to a reductive group $\mathbf{G}$ is an affine analogue of the usual flag varieties. It is a rich source of Poisson varieties and their symplectic resolutions. These spaces are examples of conical symplectic resolutions dual to the Nakajima quiver varieties. We study the cohomological stable envelopes of D. Maulik and A. Ok

Lukasz A. Sterczewski, Jaroslaw Sotor

Optical solitary waves (solitons) that interact in a nonlinear system can bind and form a structure similar to a molecule. The rich dynamics of this process have created a demand for rapid spectral characterization to deepen the understanding of soliton physics with many practical implications. Here, we demonstrate stroboscopic, two-photon imaging of soliton

Alexander Smith Clark, Eric T. Johnson, Zhi Chen, Kiran Eiden

We describe pynucastro 2.0, an open source library for interactively creating and exploring astrophysical nuclear reaction networks. We demonstrate new methods for approximating rates and using detailed balance to create reverse rates, show how to build networks and determine whether they are appropriate for a particular science application, and discuss the

Martin Raszyk, David Basin, Srđan Krstić, Dmitriy Traytel

The relational calculus (RC) is a concise, declarative query language. However, existing RC query evaluation approaches are inefficient and often deviate from established algorithms based on finite tables used in database management systems. We devise a new translation of an arbitrary RC query into two safe-range queries, for which the finiteness of the quer

Christina M. Wölk

This document examines several applicable methods to ensure privacy of data gathered in the health care sector. To ensure a common understanding of the topic, the introduction explains the need for anonymization methods based on an example. Next, reasons for data collection are introduced in connection to the purpose to protect mentioned data, as well as cur

Harshan Baskar, Anirudh S Chakravarthy, Prateek Garg, Divyam Goel

In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing -- our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to faci

Miguel Beneitez, Jacob Page, Rich R. Kerswell

Elastic turbulence is a chaotic flow state observed in dilute polymer solutions in the absence of inertia. It was discovered experimentally in circular geometries and has long been thought to require a finite amplitude perturbation in parallel flows. Here we demonstrate, within the commonly-used Oldroyd-B and FENE-P models, that a self-sustaining chaotic sta

Seungyong Moon, JunYeong Lee, Hyun Oh Song

Our work focuses on training RL agents on multiple visually diverse environments to improve observational generalization performance. In prior methods, policy and value networks are separately optimized using a disjoint network architecture to avoid interference and obtain a more accurate value function. We identify that a value network in the multi-environm

Zahra Rahiminasab, Michael Yuhas, Arvind Easwaran

Out-of-distribution (OOD) detection, i.e., finding test samples derived from a different distribution than the training set, as well as reasoning about such samples (OOD reasoning), are necessary to ensure the safety of results generated by machine learning models. Recently there have been promising results for OOD detection in the latent space of variationa

Marco Landt-Hayen, Peer Kröger, Martin Claus, Willi Rath

Artificial neural networks (ANNs) are known to be powerful methods for many hard problems (e.g. image classification, speech recognition or time series prediction). However, these models tend to produce black-box results and are often difficult to interpret. Layer-wise relevance propagation (LRP) is a widely used technique to understand how ANN models come t

Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric

We consider Contextual Bandits with Concave Rewards (CBCR), a multi-objective bandit problem where the desired trade-off between the rewards is defined by a known concave objective function, and the reward vector depends on an observed stochastic context. We present the first algorithm with provably vanishing regret for CBCR without restrictions on the polic

Katrin Fässler, Tuomas Orponen

We consider unions of $SL(2)$ lines in $\mathbb{R}^{3}$. These are lines of the form $$L = (a,b,0) + \mathrm{span}(c,d,1),$$ where $ad - bc = 1$. We show that if $\mathcal{L}$ is a Kakeya set of $SL(2)$ lines, then the union $\cup \mathcal{L}$ has Hausdorff dimension $3$. This answers a question of Wang and Zahl. The $SL(2)$ lines can be identified with hori

William Mitchell, Abbie Natkin, Paige Robertson, Marika Sullivan

Gauss-Legendre quadrature and the trapezoidal rule are powerful tools for numerical integration of analytic functions. For nearly singular problems, however, these standard methods become unacceptably slow. We discuss and generalize some existing methods for improving on these schemes when the location of the nearby singularity is known. We conclude with an

Oleg Balabanov

This article proposes and analyzes several variants of the randomized Cholesky QR factorization of a matrix $X$. Instead of computing the R factor from $X^T X$, as is done by standard methods, we obtain it from a small, efficiently computable random sketch of $X$, thus saving computational cost and improving numerical stability. The proposed direct variant o

Yang Jiang, Qing-Guo Huang

Parity violation is expected to generate an asymmetry between the amplitude of left and right-handed gravitational-wave modes which leads to a circularly polarized stochastic gravitational-wave background (SGWB). Due to the three independent baselines in the LIGO-Virgo network, we focus on the amplitude difference in strain power characterized by Stokes' par

Tina Raissi, Wei Zhou, Simon Berger, Ralf Schlüter

In this work, we compare from-scratch sequence-level cross-entropy (full-sum) training of Hidden Markov Model (HMM) and Connectionist Temporal Classification (CTC) topologies for automatic speech recognition (ASR). Besides accuracy, we further analyze their capability for generating high-quality time alignment between the speech signal and the transcription,

Filippo Bonchi, Alessandro Di Giorgio, Alessio Santamaria

Rig categories with finite biproducts are categories with two monoidal products, where one is a biproduct and the other distributes over it. In this work we present tape diagrams, a sound and complete diagrammatic language for these categories, that can be intuitively thought as string diagrams of string diagrams. We test the effectiveness of our approach ag

Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren, Yuxin Sun

We study the problem of PAC learning a single neuron in the presence of Massart noise. Specifically, for a known activation function $f: \mathbb{R} \to \mathbb{R}$, the learner is given access to labeled examples $(\mathbf{x}, y) \in \mathbb{R}^d \times \mathbb{R}$, where the marginal distribution of $\mathbf{x}$ is arbitrary and the corresponding label $y$

Yangheng Zhao, Jun Wang, Xiaolong Li, Yue Hu

3D point cloud semantic segmentation is one of the fundamental tasks for 3D scene understanding and has been widely used in the metaverse applications. Many recent 3D semantic segmentation methods learn a single prototype (classifier weights) for each semantic class, and classify 3D points according to their nearest prototype. However, learning only one prot

Eman Abdullah AlOmar, Wajdi Aljedaani, Murtaza Tamjeed, Mohamed Wiem Mkaouer

In recent years, mobile accessibility has become an important trend with the goal of allowing all users the possibility of using any app without many limitations. User reviews include insights that are useful for app evolution. However, with the increase in the amount of received reviews, manually analyzing them is tedious and time-consuming, especially when

Xuan Yang, Quanjin Tao, Xiao Feng, Donghong Cai

Multimodal pre-training breaks down the modality barriers and allows the individual modalities to be mutually augmented with information, resulting in significant advances in representation learning. However, graph modality, as a very general and important form of data, cannot be easily interacted with other modalities because of its non-regular nature. In t

Jin-Hong Chen, Rong-Feng Shen, Shang-Fei Liu

During the inspiralling of a white dwarf (WD) into an intermediate-mass black hole (~ 10^{2-5} M_sun), both gravitational waves (GWs) and electromagnetic (EM) radiation are emitted. Once the eccentric orbit's pericenter radius approaches the tidal radius, the WD would be tidally stripped upon each pericenter passage. The accretion of these stripped mass woul

Piero Naldesi, Juan Polo, Peter D. Drummond, Vanja Dunjko

We discuss an interferometric scheme employing interference of bright solitons formed as specific bound states of attracting bosons on a lattice. We revisit the proposal of Castin and Weiss [Phys. Rev. Lett. vol. 102, 010403 (2009)] for using the scattering of a quantum matter-wave soliton on a barrier in order to create a coherent superposition state of the

Samuel Dooley, Rhea Sanjay Sukthanker, John P. Dickerson, Colin White

Face recognition systems are widely deployed in safety-critical applications, including law enforcement, yet they exhibit bias across a range of socio-demographic dimensions, such as gender and race. Conventional wisdom dictates that model biases arise from biased training data. As a consequence, previous works on bias mitigation largely focused on pre-proce

Joop Hendriks, Carmem M. Gilardoni, Chris Adambukulam, Arne Laucht

Progress with quantum technology has for a large part been realized with the nitrogen-vacancy centre in diamond. Part of its properties, however, are nonideal and this drives research into other spin-active crystal defects. Several of these come with much stronger energy scales for spin-orbit and hyperfine coupling, but how this affects their spin coherence

Sabine Tornow, Klaus Ziegler

We study a quantum walk of a single particle that is subject to stroboscopic projective measurements on a graph with two sites. This two-level system is the minimal model of a measurement induced quantum walk. The mean first detected transition and return time are computed on an IBM quantum computer as a function of the hopping matrix element between the sit

Tarun Kumar Yadav, Devashish Gosain, Amir Herzberg, Daniel Zappala

Popular instant messaging applications such as WhatsApp and Signal provide end-to-end encryption for billions of users. They rely on a centralized, application-specific server to distribute public keys and relay encrypted messages between the users. Therefore, they prevent passive attacks but are vulnerable to some active attacks. A malicious or hacked serve

Youssef Aserrar, Abdellatif Chahbi, Elhoucien Elqorachi

We determine the complex-valued solutions of the following functional equation \[f(xy)+\mu (y)f(\sigma (y)x) = 2f(x)g(y),\quad x,y\in S,\] where $S$ is a semigroup and $\sigma$ an automorphism, $\mu :S\rightarrow \mathbb{C}$ is a multiplicative function such that $\mu (x\sigma (x))=1$ for all $x\in S$.

D. A. Frizo, C. A. M. de Melo, L. G. Medeiros, Juliano C. S. Neves

Following a recent approach in which the gravitational field equations in curved spacetimes were presented in the Bopp--Podolsky electrodynamics, we obtained an approximate and spherically symmetric wormhole solution in this context. The calculations were carried out up to the linear approximation in both the spacetime geometry and the radial electric field.

Tiziano Dalmonte

We define a family of propositional constructive modal logics corresponding each to a different classical modal system. The logics are defined in the style of Wijesekera's constructive modal logic, and are both proof-theoretically and semantically motivated. On the one hand, they correspond to the single-succedent restriction of standard sequent calculi for

Thomas Bellitto, Nicolas Bousquet, Adam Kabela, Théo Pierron

A coloring of a digraph is a partition of its vertex set such that each class induces a digraph with no directed cycles. A digraph is $k$-chromatic if $k$ is the minimum number of classes in such partition, and a digraph is oriented if there is at most one arc between each pair of vertices. Clearly, the smallest $k$-chromatic digraph is the complete digraph

Maximilian M. G. Kuhr

Nowadays, most studies on the dynamic properties of annular gaps focus only on the force characteristics due to translational motions, while the tilt and moment coefficients are less well studied. Therefore, there is hardly any reliable experimental data for the additional coefficients that can be used for validation purpose. To improve this, a test rig firs

Kunbo Ding, Weijie Liu, Yuejian Fang, Weiquan Mao

Existing zero-shot cross-lingual transfer methods rely on parallel corpora or bilingual dictionaries, which are expensive and impractical for low-resource languages. To disengage from these dependencies, researchers have explored training multilingual models on English-only resources and transferring them to low-resource languages. However, its effect is lim

Kleanthis Karamvasis, Vassilia Karathanassi

We present a methodology based on interferometric synthetic aperture radar (InSAR) time series analysis that can provide surface (top 5 cm) soil moisture (SSM) estimations. The InSAR time series analysis consists of five processing steps. A co-registered Single Look Complex (SLC) SAR stack as well as meteorological information are required as input of the pr

José Ribeiro, Lucas Cardoso, Raíssa Silva, Vitor Cirilo

In recent years, XAI researchers have been formalizing proposals and developing new methods to explain black box models, with no general consensus in the community on which method to use to explain these models, with this choice being almost directly linked to the popularity of a specific method. Methods such as Ciu, Dalex, Eli5, Lofo, Shap and Skater emerge

Tomas Goldsack, Zhihao Zhang, Chenghua Lin, Carolina Scarton

Lay summarisation aims to jointly summarise and simplify a given text, thus making its content more comprehensible to non-experts. Automatic approaches for lay summarisation can provide significant value in broadening access to scientific literature, enabling a greater degree of both interdisciplinary knowledge sharing and public understanding when it comes

Jérôme Leroux

Petri nets are a classical model of concurrency widely used and studied in formal verification with many applications in modeling and analyzing hardware and software, data bases, and reactive systems. The reachability problem is central since many other problems reduce to reachability questions. The reachability problem is known to be decidable but its compl

Jieshuang Wang, Xinyu Li, Zigao Dai, Xuefeng Wu

Quasi-periodic oscillation (QPO) signals are discovered in some fast radio bursts (FRBs) such as FRB 20191221A, as well as in the X-ray burst associated with the galactic FRB from SGR 1935+2154. We revisit the intermediate-field FRB model where the radio waves are generated as fast-magnetosonic waves through magnetic reconnection near the light cylinder. The

Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis

While modern machine learning models rely on increasingly large training datasets, data is often limited in privacy-sensitive domains. Generative models trained with differential privacy (DP) on sensitive data can sidestep this challenge, providing access to synthetic data instead. We build on the recent success of diffusion models (DMs) and introduce Differ

Hongyu Zhao, Hao Tan, Hongyuan Mei

Adapter-tuning is a paradigm that transfers a pretrained language model to downstream tasks by adding and tuning a small number of new parameters. Previously proposed adapter architectures are all feed-forward neural networks. In this paper, we investigate the effectiveness of using tiny-attention -- i.e., attention with extremely small per-head dimensionali

Yuki Kubo, Ryo Yanagimoto, Hayato Futase, Mikio Nakano

This paper describes our dialogue robot system, OSbot, developed for Dialogue Robot Competition 2022. The dialogue flow is based on state transitions described manually and the transition conditions use the results of keyword extraction and sentiment analysis. The transitions can be easily viewed and edited by managing them on a spreadsheet. The keyword extr

G. A. Nigmatulin, O. B. Chaganova

The steadily high demand for cash contributes to the expansion of the network of Bank payment terminals. To optimize the amount of cash in payment terminals, it is necessary to minimize the cost of servicing them and ensure that there are no excess funds in the network. The purpose of this work is to create a cash management system in the network of payment

Irina Bolodurina, Georgii Nigmatulin, Denis Parfenov

The article proposes a new method for finding the triangle-triangle intersection in 3D space, based on the use of computer graphics algorithms -- cutting off segments on the plane when moving and rotating the beginning of the coordinate axes of space. This method is obtained by synthesis of two methods of cutting off segments on the plane -- Cohen-Sutherland

Zhoujin Tian, Chaozhuo Li, Shuo Ren, Zhiqiang Zuo

Bilingual lexicon induction induces the word translations by aligning independently trained word embeddings in two languages. Existing approaches generally focus on minimizing the distances between words in the aligned pairs, while suffering from low discriminative capability to distinguish the relative orders between positive and negative candidates. In add

Tegan Maharaj

Machine learning (ML) formalizes the problem of getting computers to learn from experience as optimization of performance according to some metric(s) on a set of data examples. This is in contrast to requiring behaviour specified in advance (e.g. by hard-coded rules). Formalization of this problem has enabled great progress in many applications with large re

Tobias Hecking, Swathy Muthukrishnan, Alexander Weinert

Solving parity games is a major building block for numerous applications in reactive program verification and synthesis. While they can be solved efficiently in practice, no known approach has a polynomial worst-case runtime complexity. We present a incomplete polynomial-time approach to determining the winning regions of parity games via graph neural networ

Runnan Chen, Xinge Zhu, Nenglun Chen, Wei Li

We investigate transductive zero-shot point cloud semantic segmentation, where the network is trained on seen objects and able to segment unseen objects. The 3D geometric elements are essential cues to imply a novel 3D object type. However, previous methods neglect the fine-grained relationship between the language and the 3D geometric elements. To this end,

Yong Wu, Shekhor Chanda, Mehrdad Hosseinzadeh, Zhi Liu

We consider a new problem of few-shot learning of compact models. Meta-learning is a popular approach for few-shot learning. Previous work in meta-learning typically assumes that the model architecture during meta-training is the same as the model architecture used for final deployment. In this paper, we challenge this basic assumption. For final deployment,

Xuyang Chen, Lin Zhao

Actor-critic methods have achieved significant success in many challenging applications. However, its finite-time convergence is still poorly understood in the most practical single-timescale form. Existing works on analyzing single-timescale actor-critic have been limited to i.i.d. sampling or tabular setting for simplicity. We investigate the more practica

Wenjing Liu, Shanpu Shen, Danny H. K. Tsang, Ranjan K. Mallik

Ambient backscatter communication (AmBC) leverages the existing ambient radio frequency (RF) environment to implement communication with battery-free devices. One critical challenge of AmBC systems is signal recovery because the transmitted information bits are embedded in the ambient RF signals and these are unknown and uncontrollable. To address this probl

Miquel Martí i Rabadán, Alessandro Pieropan, Hossein Azizpour, Atsuto Maki

We propose Dense FixMatch, a simple method for online semi-supervised learning of dense and structured prediction tasks combining pseudo-labeling and consistency regularization via strong data augmentation. We enable the application of FixMatch in semi-supervised learning problems beyond image classification by adding a matching operation on the pseudo-label

Maxime Allard, Simón C. Smith, Konstantinos Chatzilygeroudis, Bryan Lim

In real-world environments, robots need to be resilient to damages and robust to unforeseen scenarios. Quality-Diversity (QD) algorithms have been successfully used to make robots adapt to damages in seconds by leveraging a diverse set of learned skills. A high diversity of skills increases the chances of a robot to succeed at overcoming new situations since

Yibo Hu, Yu Lin, Erick Skorupa Parolin, Latifur Khan

Recent works in cyber deception study how to deter malicious intrusion by generating multiple fake versions of a critical document to impose costs on adversaries who need to identify the correct information. However, existing approaches are context-agnostic, resulting in sub-optimal and unvaried outputs. We propose a novel context-aware model, Fake Document

Aya Watanabe, Shinnosuke Takamichi, Yuki Saito, Detai Xin

In this paper, we propose a method for intermediating multiple speakers' attributes and diversifying their voice characteristics in ``speaker generation,'' an emerging task that aims to synthesize a nonexistent speaker's naturally sounding voice. The conventional TacoSpawn-based speaker generation method represents the distributions of speaker embeddings by

Yulong Qiao, Joonsuk Huh, Frank Grossmann

The full state vector of boson sampling is generated by passing S single photons through beam splitters of M modes. The initial Fock state is expressed withgeneralized coherent states, and an exact application of the unitary evolution becomes possible. Due to the favorable polynomial scaling in M , we can investigate Renyi entanglement entropies for moderate

Gonzalo Navarro

We consider the problem of computing the Maximal Exact Matches (MEMs) of a given pattern $P[1 .. m]$ on a large repetitive text collection $T[1 .. n]$, which is represented as a (hopefully much smaller) run-length context-free grammar of size $g_{rl}$. We show that the problem can be solved in time $O(m^2 \log^\epsilon n)$, for any constant $\epsilon > 0$, o

Jian-Yong Wang, Han Yu

Complex high-dimensional co-occurrence data are increasingly popular from a complex system of interacting physical, biological and social processes in discretely indexed modifiable areal units or continuously indexed locations of a study region for landscape-based mechanism. Modeling, predicting and interpreting complex co-occurrences are very general and fu

Teo Granger, Thomas M. Michelitsch, Michael Bestehorn, Alejandro P. Riascos

We study an epidemic model for a constant population by taking into account four compartments of the individuals characterizing their states of health. Each individual is in one of the compartments susceptible (S); incubated - infected yet not infectious (C), infected and infectious (I), and recovered - immune (R). An infection is 'visible' only when an indi

Luke Swanson, David Gagnon, Jennifer Scianna, John McCloskey

The ability for an educational game designer to understand their audience's play styles and resulting experience is an essential tool for improving their game's design. As a game is subjected to large-scale player testing, the designers require inexpensive, automated methods for categorizing patterns of player-game interactions. In this paper we present a si

Divyang G. Bhimani, Saikatul Haque

We study inhomogeneous heat equation with inverse square potential, namely, \[\partial_tu + \mathcal{L}_a u= \pm |\cdot|^{-b} |u|^{\alpha}u,\] where $\mathcal{L}_a=-\Delta + a |x|^{-2}.$ We establish some fixed-time decay estimate for $e^{-t\mathcal{L}_a}$ associated with inhomogeneous nonlinearity $|\cdot|^{-b}$ in Lebesgue spaces. We then develop local the

Lea Goetz

In computational histopathology algorithms now outperform humans on a range of tasks, but to date none are employed for automated diagnoses in the clinic. Before algorithms can be involved in such high-stakes decisions they need to "know when they don't know", i.e., they need to estimate their predictive uncertainty. This allows them to defer potentially err

Jeffrey Galkowski, Pierre Marchand, Jian Wang, Maciej Zworski

The scattering phase, defined as $ \log \det S ( \lambda ) / 2\pi i $ where $ S ( \lambda ) $ is the (unitary) scattering matrix, is the analogue of the counting function for eigenvalues when dealing with exterior domains and is closely related to Krein's spectral shift function. We revisit classical results on asymptotics of the scattering phase and point o

Joan Moragues, Luana M. Modafferi, Rodrigo Tenorio, David Keitel

Pulsars are rotating neutron stars that emit periodic electromagnetic radiation. While pulsars generally slow down as they lose energy, some also experience glitches: spontaneous increases of their rotational frequency. According to several models, these glitches can also lead to the emission of long-duration transient gravitational waves (GWs). We present d

David J. Gagnon, Ryan S. Baker, Sarah Gagnon, Luke Swanson

In this paper we use an existing history learning game with an active audience as a research platform for exploring how humor and "snarkiness" in the dialog script affect students' progression and attitudes about the game. We conducted a 2x2 randomized experiment with 11,804 anonymous 3rd-6th grade students. Using one-way ANOVA and Kruskall-Wallis tests, we

Thierry Valet, Roberto Raimondi

Starting from the Keldysh theory, for a general low energy $N$-band Hamiltonian in the clean limit, we perform a manifestly $\smash{U(1) \times SU(N)}$ gauge invariant semiclassical expansion. A generalized Berry curvature tensor is shown to control a redistribution of spectral weights. New expressions for certain physical quantities ensue, establishing the

Chun-Fu Chen, Shaohan Hu, Zhonghao Shi, Prateek Gulati

The recent rapid advances in machine learning technologies largely depend on the vast richness of data available today, in terms of both the quantity and the rich content contained within. For example, biometric data such as images and voices could reveal people's attributes like age, gender, sentiment, and origin, whereas location/motion data could be used

Raunak Kumar, Sarah Dean, Robert Kleinberg

Online convex optimization (OCO) is a widely used framework in online learning. In each round, the learner chooses a decision in a convex set and an adversary chooses a convex loss function, and then the learner suffers the loss associated with their current decision. However, in many applications the learner's loss depends not only on the current decision b

Jacob A. Siefert, Trevor J. Bird, Justin P. Koeln, Neera Jain

This paper presents identities for calculating over-approximated successor sets of discrete-time nonlinear systems using hybrid zonotopes. The proposed technique extends the state-update set construct, previously developed for linear hybrid systems, to nonlinear systems. Forward reachability of nonlinear systems can then be performed using only projection, i

Hector McKimm, Andi Q Wang, Murray Pollock, Christian P Robert

Enriching Brownian motion with regenerations from a fixed regeneration distribution $\mu$ at a particular regeneration rate $\kappa$ results in a Markov process that has a target distribution $\pi$ as its invariant distribution. For the purpose of Monte Carlo inference, implementing such a scheme requires firstly selection of regeneration distribution $\mu$,

Housheng Xie, Junhui Qiu, Yuan Dai, Yang Yang

As an essential processing step before the fusing of infrared and visible images, the performance of image registration determines whether the two images can be fused at correct spatial position. In the actual scenario, the varied imaging devices may lead to a change in perspective or time gap between shots, making significant non-rigid spatial relationship

Mathieu Giroux, Andrzej Pokraka

We present a loop-by-loop method for computing the differential equations of Feynman integrals using the recently developed dual form formalism. We give explicit prescriptions for the loop-by-loop fibration of multi-loop dual forms. Then, we test our formalism on a simple, but non-trivial, example: the two-loop three-mass elliptic sunrise family of integrals

Li-Ping Yang, Y. F. Fu, Z. Y. Xie, T. Xiang

We have proposed an efficient algorithm to calculate physical quantities in the translational invariant three-dimensional tensor networks, which is particularly relevant to the study of the three-dimensional classical statistical models and the (2+1)-dimensional quantum lattice models. In the context of a classical model, we determine the partition function

Rui Luo, Fei Liu, Wenhao Liang, Yuhong Zhang

In the field of intelligent education, knowledge tracing (KT) has attracted increasing attention, which estimates and traces students' mastery of knowledge concepts to provide high-quality education. In KT, there are natural graph structures among questions and knowledge concepts so some studies explored the application of graph neural networks (GNNs) to imp

Carys Herbert, Dirk Froebrich, Aleks Scholz

We present measurements of spot properties on 31 young stellar objects, based on multi-band data from the HOYS (Hunting Outbursting Young Stars) project. On average the analysis for each object is based on 270 data points during 80 days in at least 3 bands. All the young low-mass stars in our sample show periodic photometric variations. We determine spot tem

Qi Jia, Yizhu Liu, Siyu Ren, Kenny Q. Zhu

Abstractive dialogue summarization is to generate a concise and fluent summary covering the salient information in a dialogue among two or more interlocutors. It has attracted great attention in recent years based on the massive emergence of social communication platforms and an urgent requirement for efficient dialogue information understanding and digestio

Francesco Bigazzi, Tommaso Canneti, Aldo L. Cotrone

The divergence of the string partition function due to the exponential growth of states is a well-understood issue in flat spacetime. It can be interpreted as the appearance of tachyon modes above a certain temperature, known as the Hagedorn temperature $T_H$. In the literature, one can find some intuitions about its generalization to curved spacetimes, wher

Zhiwei Chen, Youjun Lu, Yuetong Zhao

A significant number of stellar binary black hole (sBBH) mergers may be lensed and detected by the third generation gravitational wave (GW) detectors. Their lensed host galaxies may be detectable, which thus helps to accurately localize these sources and provide a new approach to study the origin of sBBHs. In this paper, we investigate the detectability of t

E. A. Davydov, D. V. Fursaev, V. A. Tainov

A straightforward application of the variational principle to null strings meets difficulties since string's world-sheets are degenerate. It is known that the variational principle in this case can be formulted with the help of two-vector density on the string world-sheet which plays a role of Lagrange multipliers. It is shown that recently suggested stress-

Xiangyang Li, Bo Chen, HuiFeng Guo, Jingjie Li

Scoring a large number of candidates precisely in several milliseconds is vital for industrial pre-ranking systems. Existing pre-ranking systems primarily adopt the \textbf{two-tower} model since the ``user-item decoupling architecture'' paradigm is able to balance the \textit{efficiency} and \textit{effectiveness}. However, the cost of high efficiency is th

A. Jacobs, C. Andreoiu, J. Bergmann, T. Brunner

The performance of high-precision mass spectrometry of radioactive isotopes can often be hindered by large amounts of contamination, including molecular species, stemming from the production of the radioactive beam. In this paper, we report on the development of Collision-Induced Dissociation (CID) as a means of background reduction for experiments at TRIUMF

Guang Yang, W. N. Brandt, David M. Alexander, Médéric Boquien

Recent studies have revealed a strong relation between sample-averaged black-hole (BH) accretion rate (BHAR) and star formation rate (SFR) among bulge-dominated galaxies, i.e., "lockstep" BH-bulge growth, in the distant universe. This relation might be closely related to the BH-bulge mass correlation observed in the local universe. To understand further BH-b