May 2022 arXiv papers — page 145

Xin Chen, Niao He, Yifan Hu, Zikun Ye

We study a class of stochastic nonconvex optimization in the form of $\min_{x\in\mathcal{X}} F(x):=\mathbb{E}_\xi [f(\phi(x,\xi))]$, i.e., $F$ is a composition of a convex function $f$ and a random function $\phi$. Leveraging an (implicit) convex reformulation via a variable transformation $u=\mathbb{E}[\phi(x,\xi)]$, we develop stochastic gradient-based alg

Raoni F. da S. Teixeira, Rafael B. Januzi, Fabio A. Faria

Advances in image processing and analysis as well as machine learning techniques have contributed to the use of biometric recognition systems in daily people tasks. These tasks range from simple access to mobile devices to tagging friends in photos shared on social networks and complex financial operations on self-service devices for banking transactions. In

Qingyang Zhang

Chatterjee (2021) introduced an asymmetric correlation measure that has attracted much attention over the past year. In this paper, we derive the asymptotic distribution of the symmetric version of Chatterjee's correlation, and suggest a finite sample test for independence.

Antonio Patrón, Antonio Prados, Carlos A. Plata

The overdamped Brownian dynamics of a harmonic oscillator is a paradigmatic system in non-equilibrium statistical mechanics, which reliably models relevant stochastic systems such as colloidal particles submitted to optical confinement. In this work, optimal thermal protocols are tailored to minimise the connection time between equilibrium states of overdamp

Celine Guervilly

Stably-stratified layers may be present at the top of the electrically-conducting fluid layers of many planets either because the temperature gradient is locally subadiabatic or because a stable composition gradient is maintained by the segregation of chemical elements. Here we study the double-diffusive processes taking place in such a stable layer, conside

E. Arrighi, V. -H. Nguyen, M. Di Luca, G. Maffione

The superlattice obtained by aligning a monolayer graphene and boron nitride (BN) inherits from the hexagonal lattice a sixty degrees periodicity with the layer alignment. It implies that, in principle, the properties of the heterostructure must be identical for 0$^{\circ}$ and 60$^{\circ}$ of layer alignment. Here, we demonstrate, using dynamically rotatabl

Iñigo López-Riobóo Botana, Verónica Bolón-Canedo, Bertha Guijarro-Berdiñas, Amparo Alonso-Betanzos

There are many contexts in which dyadic data are present. Social networks are a well-known example. In these contexts, pairs of elements are linked building a network that reflects interactions. Explaining why these relationships are established is essential to obtain transparency, an increasingly important notion. These explanations are often presented usin

Manuel Krannich, Alexander Kupers

We study the Disc-structure space $S^{\rm Disc}_\partial(M)$ of a compact smooth manifold $M$. Informally speaking, this space measures the difference between $M$, together with its diffeomorphisms, and the diagram of ordered framed configuration spaces of $M$ with point-forgetting and point-splitting maps between them, together with its derived automorphism

Ronny Hug, Stefan Becker, Wolfgang Hübner, Michael Arens

Probabilistic models for sequential data are the basis for a variety of applications concerned with processing timely ordered information. The predominant approach in this domain is given by recurrent neural networks, implementing either an approximate Bayesian approach (e.g. Variational Autoencoders or Generative Adversarial Networks) or a regression-based

Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker

In this paper, we explore an improved framework to train a monoaural neural enhancement model for robust speech recognition. The designed training framework extends the existing mixture invariant training criterion to exploit both unpaired clean speech and real noisy data. It is found that the unpaired clean speech is crucial to improve quality of separated

Julia White, Noah Goodman, Robert Hawkins

Language use differs dramatically from context to context. To some degree, modern language models like GPT-3 are able to account for such variance by conditioning on a string of previous input text, or prompt. Yet prompting is ineffective when contexts are sparse, out-of-sample, or extra-textual; for instance, accounting for when and where the text was produ

Yujian Wu, Ted Westling

The ratio of the hazard functions of two populations or two strata of a single population plays an important role in time-to-event analysis. Cox regression is commonly used to estimate the hazard ratio under the assumption that it is constant in time, which is known as the proportional hazards assumption. However, this assumption is often violated in practic

K. Kyan, A. Monnai

Nonextensive statistics has attracted attention as a description of particle spectra in nuclear collisions at QCD energies. First, we construct the equation of state by incorporating Tsallis statistics based on the hadron resonance gas and parton gas models. Thermodynamic conditions are found to impose constraints on the $q$-parameter of Tsallis distribution

Anirudh Chiti, Anna Frebel, Alexander P. Ji, Mohammad K. Mardini

We present chemical abundances and velocities of five stars between 0.3 kpc to 1.1 kpc from the center of the Tucana II ultra-faint dwarf galaxy (UFD) from high-resolution Magellan/MIKE spectroscopy. We find that every star is deficient in metals (-3.6 < [Fe/H] < -1.9) and in neutron-capture elements as is characteristic of UFD stars, unambiguously confirmin

Joel Hass

This paper examines the relationship between the knotting of an embedded surface in $\R^3$ and the knotting of its fold curves, formed by the singular set of projection to a plane. The first result shows that every surface, no matter how knotted, can be isotoped so that its fold curves form an unlink. A second result defines a new invariant which gives a com

Tyler Chen, Eric Hallman

We introduce an algorithm for estimating the trace of a matrix function $f(\mathbf{A})$ using implicit products with a symmetric matrix $\mathbf{A}$. Existing methods for implicit trace estimation of a matrix function tend to treat matrix-vector products with $f(\mathbf{A})$ as a black-box to be computed by a Krylov subspace method. Like other recent algorit

Geovanny Briceño-Morales, Julio Chanamé

The improved astrometry precision of Gaia-eDR3 allows us to perform a detailed study of the Upper Scorpius OB association and revisit its spatial, kinematic, and age substructure. We achieve this by combining clustering techniques and complementing with age estimations based on Gaia photometry. Our census retrieves 3661 candidate members for Upper Scorpius w

Ling Huang, Su Ruan, Thierry Denoeux

The investigation of uncertainty is of major importance in risk-critical applications, such as medical image segmentation. Belief function theory, a formal framework for uncertainty analysis and multiple evidence fusion, has made significant contributions to medical image segmentation, especially since the development of deep learning. In this paper, we prov

Hooman Moradpour, Mohsen Javaherian, Ebrahim Namvar, Amir Hadi Ziaie

Relying on the quantum tunnelling concept and Maxwell-Boltzmann-Gibbs statistics, Gamow shows that the star-burning process happens at temperatures comparable to a critical value, called the Gamow temperature ({\tt T}) and less than the prediction of the classical framework. In order to highlight the role of the equipartition theorem in the Gamow argument, a

Paul M. Alsing, Christopher C. Tison, James Schneeloch, Richard J. Birrittella

We present marginal cumulative distribution functions (CDF) for density matrices $ρ$ of fixed purity $\tfrac{1}{N}\leμ_N(ρ)=\textrm{Tr}[ρ^2]\le 1$ for arbitrary dimension $N$. We give closed form analytic formulas for the cases $N=2$ (trivial), $N=3$ and $N=4$, and present a prescription for CDFs of higher arbitrary dimensions. These formulas allows one to u

William Kuszmaul, Shyam Narayanan

The \emph{$ p$-processor cup game} is a classic and widely studied scheduling problem that captures the setting in which a $p$-processor machine must assign tasks to processors over time in order to ensure that no individual task ever falls too far behind. The problem is formalized as a multi-round game in which two players, a filler (who assigns work to tas

Xianhang Li, Huiyu Wang, Chen Wei, Jieru Mei

Image pre-training, the current de-facto paradigm for a wide range of visual tasks, is generally less favored in the field of video recognition. By contrast, a common strategy is to directly train with spatiotemporal convolutional neural networks (CNNs) from scratch. Nonetheless, interestingly, by taking a closer look at these from-scratch learned CNNs, we n

Alexandros Rekkas, Peter R. Rijnbeek, David M. Kent, Ewout W. Steyerberg

Objective: To compare different risk-based methods for optimal prediction of treatment effects. Methods: We simulated RCT data using diverse assumptions for the average treatment effect, a baseline prognostic index of risk (PI), the shape of its interaction with treatment (none, linear, quadratic or non-monotonic), and the magnitude of treatment-related harm

Maximiliano Cristiá, Gianfranco Rossi

In this paper we show how prescritive type checking and constraint solving can be combined to increase automation during software verification. We do so by defining a type system and implementing a typechecker for {log} (read `setlog'), a Constraint Logic Programming (CLP) language and satisfiability solver based on set theory. Hence, we proceed as follows:

Marco de Cesare, Roberto Oliveri

We obtain approximate analytical solutions of the Einstein equations close to the trapping horizon for a dynamical spherically symmetric black hole in the presence of a minimally coupled self-interacting scalar field. This is made possible by a new parametrization of the metric, in which the displacement from the horizon as well as its expansion rate feature

Santanu Acharjee, Kabindra Goswami

In this paper, theorem 3.2 and theorem 4.1 of Özçağ and Eysen [S. Özçağ and A.E. Eysen, Almost Menger property in bitopological spaces, Ukrainian Math. J., {\bf 68}, No 6, 950-958 (2016)] are proven to be incorrect. An example is provided to disprove them and thus, correct versions of the theorems are restated.

Kazem Ardaneh, Remi Meyer, Mostafa Hassan, Remo Giust

The creation of high energy density ($\gtrsim10^6$ joules per cm$^3$) over-critical plasmas in a large volume has essential applications in the study of warm dense matter, being present in the hot cores of stars and planets. It was recently shown that femtosecond Bessel beams enable creating over-critical plasmas inside sapphire with sub-wavelength radius an

Hao-Jui Kuan, Kostas D. Kokkotas

The excitation of $f$-mode in a neutron star member of coalescing binaries accelerates the merger course, and thereby introduces a phase shift in the gravitational waveform. Emphasising on the tidal phase shift by aligned, rotating stars, we provide an accurate, yet economical, method to generate $f$-mode-involved, pre-merger waveforms using realistic spin-m

A. Cavaillès, P. Boucher, L. Daudet, I. Carron

Reconfigurable linear optical networks are a key component for the development of optical quantum information processing platforms in the NISQ era and beyond. We report the implementation of such a device based on an innovative design that uses the mode mixing of a multimode fiber in combination with the programmable wavefront shaping of a SLM. The capabilit

Mingda Chen, Jingfei Du, Ramakanth Pasunuru, Todor Mihaylov

Self-supervised pretraining has made few-shot learning possible for many NLP tasks. But the pretraining objectives are not typically adapted specifically for in-context few-shot learning. In this paper, we propose to use self-supervision in an intermediate training stage between pretraining and downstream few-shot usage with the goal to teach the model to pe

Yangmu Li, A. Sapkota, P. M. Lozano, Zengyi Du

The interpretation of how superconductivity disappears in cuprates at large hole doping has been controversial. To address this issue, we present an experimental study of single-crystal and thin film samples of La$_{2-x}$Sr$_x$CuO$_4$ (LSCO) with $x\ge0.25$. In particular, measurements of bulk susceptibility on LSCO crystals with $x=0.25$ indicate an onset o

Jinheung Kim, Soojin Lee, Prasenjit Sanyal, Jeonghyeon Song

The recent measurement of the $W$ boson mass by the CDF collaboration adds an anomaly to the long-standing discrepancy in the muon anomalous magnetic moment, $Δa_μ$. Although type-X in the two-Higgs-doublet model provides an attractive solution to $Δa_μ$ through a light pseudoscalar $A$, the model confronts the exotic Higgs decays of $h\to AA$ and the lepton

Daniel Farid, Han Aung, Daisuke Nagai, Arya Farahi

We present Classification of Cluster GAlaxy MEmbers (C$^2$-GaMe), a classification algorithm based on a suite of machine learning models that differentiates galaxies into orbiting, infalling, and background (interloper) populations, using phase space information as input. We train and test C$^2$-GaMe with the galaxies from UniverseMachine mock catalog based

Rob Verheyen

Normalizing flows are a class of generative models that enable exact likelihood evaluation. While these models have already found various applications in particle physics, normalizing flows are not flexible enough to model many of the peripheral features of collision events. Using the framework of Nielsen et al. (2020), we introduce several surjective and st

Shyam Balaji, Guillem Domenech, Joseph Silk

The primordial spectrum of fluctuations may present a large peak as a result of enhancing features during inflation. This may include, but is not limited to, bumps in the inflaton&#39;s potential, phases of ultra-slow-roll or turns in multi-field space. However, in many models, inflation does not end immediately after the enhancing feature and it is likely t

Michael G. Jones, David J. Sand, Michele Bellazzini, Kristine Spekkens

We discuss five blue stellar systems in the direction of the Virgo cluster, analogous to the enigmatic object SECCO 1 (AGC 226067). These objects were identified based on their optical and UV morphology and followed up with HI observations with the VLA (and GBT), MUSE/VLT optical spectroscopy, and HST imaging. These new data indicate that one system is a dis

Barbara Roessle, Matthias Nießner

Erroneous feature matches have severe impact on subsequent camera pose estimation and often require additional, time-costly measures, like RANSAC, for outlier rejection. Our method tackles this challenge by addressing feature matching and pose optimization jointly. To this end, we propose a graph attention network to predict image correspondences along with

Zhehan Qin, Zhong-Zhi Xianyu

Massive particles produced during the cosmic inflation can imprint in the primordial non-Gaussianities as characteristic oscillating functions of various momentum ratios, known as cosmological collider signals. We initiate a study of the phase of the oscillating signals which can be unambiguously defined and measured. The phase can provide useful new informa

Ore Gottlieb, Serena Moseley, Teresita Ramirez-Aguilar, Ariadna Murguia-Berthier

Short $γ$-ray burst (sGRB) jets form in the aftermath of a neutron star merger, drill through disk winds and dynamical ejecta, and extend over four to five orders of magnitude in distance before breaking out of the ejecta. We present the first 3D general-relativistic magnetohydrodynamic sGRB simulations to span this enormous scale separation. They feature th

Sophia Lilleengen, Michael S. Petersen, Denis Erkal, Jorge Peñarrubia

It has recently been shown that the Large Magellanic Cloud (LMC) has a substantial effect on the Milky Way&#39;s stellar halo and stellar streams. Here, we explore how deformations of the Milky Way and LMC&#39;s dark matter haloes affect stellar streams, and whether these effects are observable. In particular, we focus on the Orphan-Chenab (OC) stream which

Shyam Balaji, P. S. Bhupal Dev, Joseph Silk, Yongchao Zhang

We derive improved stellar luminosity limits on a generic light CP-even scalar field $S$ mixing with the Standard Model (SM) Higgs boson from the supernova SN1987A, the Sun, red giants (RGs) and white dwarfs (WDs). For the first time, we include the geometric effects for the decay and absorption of $S$ particles in the stellar interior. For SN1987A and the S

Shih-Yang Su, Timur Bagautdinov, Helge Rhodin

Deep learning greatly improved the realism of animatable human models by learning geometry and appearance from collections of 3D scans, template meshes, and multi-view imagery. High-resolution models enable photo-realistic avatars but at the cost of requiring studio settings not available to end users. Our goal is to create avatars directly from raw images w

Heribertus Bayu Hartanto, Rene Poncelet, Andrei Popescu, Simone Zoia

We compute theoretical predictions for the production of a W-boson in association with a bottom-quark pair at hadron colliders at next-to-next-to-leading order (NNLO) in QCD, including the leptonic decay of the W-boson, while treating the bottom quark as massless. This calculation constitutes the very first $2 \to 3$ process with a massive external particle

Xiaoyu Lei

This article presents an efficient algorithm to generate a discrete uniform distribution on a set of $p$ elements using a biased random source for $p$ prime. The algorithm generalizes Von Neumann&#39;s method and improves computational efficiency of Dijkstra&#39;s method. In addition, the algorithm is extended to generate discrete uniform distribution on any

Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman

In the future, powerful AI systems may be deployed in high-stakes settings, where a single failure could be catastrophic. One technique for improving AI safety in high-stakes settings is adversarial training, which uses an adversary to generate examples to train on in order to achieve better worst-case performance. In this work, we used a safe language gener

Charles Schwartz

Working strictly within the physics theories of Special and General Relativity, I have produced a series of studies developing a consistent mathematical description of tachyons, using both classical and quantum frameworks for particles and fields. The most important choices throughout this work concern the question of which habits from the study of ordinary

Fabio Cavaliere, Matteo Carrega, Giulio De Filippis, Vittorio Cataudella

We discuss whether, and under which conditions, it is possible to realize a heat engine simply by dynamically modulating the couplings between the quantum working medium and thermal reservoirs. For that purpose, we consider the paradigmatic model of a quantum harmonic oscillator, exposed to a minimal modulation, that is, a monochromatic driving of the coupli

Zoran Kostić, Alex Angus, Zhengye Yang, Zhuoxu Duan

Traffic intersections are the most suitable locations for the deployment of computing, communications, and intelligence services for smart cities of the future. The abundance of data to be collected and processed, in combination with privacy and security concerns, motivates the use of the edge-computing paradigm which aligns well with physical intersections

Sayantani Bhattacharyya, Parthajit Biswas, Anirban Dinda, Nilay Kundu

We consider diffeomorphism invariant theories of gravity with arbitrary higher derivative terms in the Lagrangian as corrections to the leading two derivative theory of Einstein&#39;s general relativity. We construct a proof of the zeroth law of black hole thermodynamics in such theories. We assume that a stationary black hole solution in an arbitrary higher

Xinyu Gao, Xidong Mu, Wenqiang Yi, Yuanwei Liu

A novel reconfigurable intelligent surface-aided multi-robot network is proposed, where multiple mobile robots are served by an access point (AP) through non-orthogonal multiple access (NOMA). The goal is to maximize the sum-rate of whole trajectories for the multi-robot system by jointly optimizing trajectories and NOMA decoding orders of robots, phase-shif

James M. Shook

Let $\pi=(d_{1},\ldots,d_{n})$ be a non-increasing degree sequence with even $n$. In 1974, Kundu showed that if $\mathcal{D}_{k}(\pi)=(d_{1}-k,\ldots,d_{n}-k)$ is graphic, then some realization of $\pi$ has a $k$-factor. For $r\leq 2$, Busch et al. and later Seacrest for $r\leq 4$ showed that if $r\leq k$ and $\mathcal{D}_{k}(\pi)$ is graphic, then there is

Jinze Yu, Jiaming Liu, Xiaobao Wei, Haoyi Zhou

Recently, DEtection TRansformer (DETR), an end-to-end object detection pipeline, has achieved promising performance. However, it requires large-scale labeled data and suffers from domain shift, especially when no labeled data is available in the target domain. To solve this problem, we propose an end-to-end cross-domain detection Transformer based on the mea

Long Feng, Tiefeng Jiang, Xiaoyun Li, Binghui Liu

For a set of dependent random variables, without stationary or the strong mixing assumptions, we derive the asymptotic independence between their sums and maxima. Then we apply this result to high-dimensional testing problems, where we combine the sum-type and max-type tests and propose a novel test procedure for the one-sample mean test, the two-sample mean

Luca Caloni, Martina Gerbino, Massimiliano Lattanzi, Luca Visinelli

We constrain the coupling of thermally-produced axion-like particles (here axions) with photons and gluons, using data from the cosmic microwave background (CMB) spectra and baryon acoustic oscillations. The axion possesses an explicit soft breaking mass term and it is produced thermally in the early Universe from either axion-photon or axion-gluon processes

Jonathan Wei Zhong Lau, Koon Siang Gan, Rainer Dumke, Luigi Amico

We study a multi-functional device for cold atoms consisting of a three-terminal ring circuit pierced by a synthetic magnetic flux, where the ring can be continuous or discretized. The flux controls the atomic current through the ring via the Aharonov-Bohm effect. Our device shows a flux-induced transition of reflections from an Andreev-like negative density

Spyridon Pougkakiotis, Dionysios S. Kalogerias

In this paper we analyze a zeroth-order proximal stochastic gradient method suitable for the minimization of weakly convex stochastic optimization problems. We consider nonsmooth and nonlinear stochastic composite problems, for which (sub-)gradient information might be unavailable. The proposed algorithm utilizes the well-known Gaussian smoothing technique,

Thomas Place, Marc Zeitoun

Group languages are regular languages recognized by finite groups, or equivalently by finite automata in which each letter induces a permutation on the set of states. We investigate the separation problem for this class of languages: given two arbitrary regular languages as input, we show how to decide if there exists a group language containing the first on

Vili Heinonen, Abel J. Abraham, Jonasz Słomka, Keaton J. Burns

Pattern-forming nonequilibrium systems are ubiquitous in nature, from driven quantum matter and biological life forms to atmospheric and interstellar gases. Identifying universal aspects of their far-from-equilibrium dynamics and statistics poses major conceptual and practical challenges due to the absence of energy and momentum conservation laws. Here, we e

Elena Arabadzhiyska, Cara Tursun, Hans-Peter Seidel, Piotr Didyk

Eye-tracking technology is an integral component of new display devices such as virtual and augmented reality headsets. Applications of gaze information range from new interaction techniques exploiting eye patterns to gaze-contingent digital content creation. However, system latency is still a significant issue in many of these applications because it breaks

Adam B. Langeveld, Nikku Madhusudhan, Samuel H. C. Cabot

The alkali metal sodium (Na) is one of the most commonly detected chemical species in the upper atmospheres of giant exoplanets. In this work we conducted a homogeneous survey of Na in a diverse sample of ten highly irradiated giant exoplanets using high-resolution transmission spectroscopy. Our sample includes nine planets with previous Na detections and on

Adrien Gourgout, Maxime Leroux, Jean-Loup Smirr, Maxime Massoudzadegan

The ultra-quantum limit is achieved when a magnetic field confines an electron gas in its lowest spin-polarised Landau level. Here we show that in this limit, electron doped ZrTe$_5$ shows a metal-insulator transition followed by a sign change of the Hall and Seebeck effects at low temperature. We attribute this transition to a magnetic freeze-out of charge

Yichong Huang, Xiaocheng Feng, Xinwei Geng, Bing Qin

Although all-in-one-model multilingual neural machine translation (multilingual NMT) has achieved remarkable progress, the convergence inconsistency in the joint training is ignored, i.e., different language pairs reaching convergence in different epochs. This leads to the trained MNMT model over-fitting low-resource language translations while under-fitting

A. A. Saharian, R. M. Avagyan, E. R. Bezerra de Mello, V. Kh. Kotanjyan

For general number of spatial dimensions we investigate the cosmological dynamics driven by a cosmological constant and by a source with barotropic equation of state. It is assumed that for both those sources the energy density can be either positive or negative. Exact solutions of the cosmological equations are provided for flat models. For models with curv

Olaf Müller

We review three examples of functors from Lorentzian categories and their applications in finiteness results, singularity theorems and boundary constructions. The third example is a novel functor from the category of ordered measure spaces to the category of Lorentzian pre-length spaces in the sense of Kunzinger-Sämann.

Pasquale Lafiosca, Ip-Shing Fan, Nicolas P. Avdelidis

Dents on the aircraft skin are frequent and may easily go undetected during airworthiness checks, as their inspection process is tedious and extremely subject to human factors and environmental conditions. Nowadays, 3D scanning technologies are being proposed for more reliable, human-independent measurements, yet the process of inspection and reporting remai

Patrick Jentsch, Chiu Fan Lee

Active matter is not only relevant to living matter and diverse nonequilibrium systems, but also constitutes a fertile ground for novel physics. Indeed, dynamic renormalization group (DRG) analyses have uncovered many new universality classes (UCs) in polar active fluids - an archetype of active matter systems. However, due to the inherent technical difficul

Jingyan Wang, Ashwin Pananjady

We consider the problem of sequential evaluation, in which an evaluator observes candidates in a sequence and assigns scores to these candidates in an online, irrevocable fashion. Motivated by the psychology literature that has studied sequential bias in such settings -- namely, dependencies between the evaluation outcome and the order in which the candidate

Aaron Hertzmann

This paper proposes a framework for computational modeling of artistic painting algorithms, inspired by human creative practices. Based on examples from expert artists and from the author&#39;s own experience, the paper argues that creative processes often involve two important components: vague, high-level goals (e.g., &#34;make a good painting&#34;), and e

Kalina P. Slavkova, Julie C. DiCarlo, Viraj Wadhwa, Chengyue Wu

The purpose of this work is to implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data. The ConvDecoder neural network was trained with a physics-based regularization term incorporating the spoiled gradient echo equation that describes variable-flip angle (VF

Damiano Brigo

We present the two new notions of projection of a stochastic differential equation (SDE) onto a submanifold, as developed in Armstrong, Brigo e Rossi Ferrucci (2019, 2018): the Ito-vector and Ito-jet projections. This allows one to systematically and optimally develop low dimensional approximations to high dimensional SDEs using differential geometric techni

Lucas Kania, Ernst Wit

Invariant prediction uses the prediction stability of causal relationships across different environments to identify causal variables. Conversely, using causal variables gives prediction guarantees even in out-of-sample data settings. In this paper, we investigate the identification of causal-like models from in-sample data that ensure out-of-sample risk gua

Ryan Pederson, Bhupalee Kalita, Kieron Burke

Over the past decade machine learning has made significant advances in approximating density functionals, but whether this signals the end of human-designed functionals remains to be seen. Ryan Pederson, Bhupalee Kalita and Kieron Burke discuss the rise of machine learning for functional design.

Ankan Ganguly, Kavita Ramanan

Consider an interacting particle system indexed by the vertices of a (possibly random) locally finite graph whose vertices and edges are equipped with marks representing parameters of the model such as the environment and initial conditions. Each particle takes values in a countable state space and evolves according to a pure jump process whose jump intensit

Francesco Pelosin

In this short paper, we propose a baseline (off-the-shelf) for Continual Learning of Computer Vision problems, by leveraging the power of pretrained models. By doing so, we devise a simple approach achieving strong performance for most of the common benchmarks. Our approach is fast since requires no parameters updates and has minimal memory requirements (ord

P. Panayotaros, R. M. Vargas-Magaña

We study free surface water waves in a 2-D symmetric triangular channel with sides that have a 45o slope. We develop models for small amplitude nonlinear waves, extending earlier studies that have considered the linearized problem. We see that a combination of heuristic small amplitude expansions lead to a relatively simple system that we then use to study i

Gefei Cai, Xinyi Li

In this paper, we construct and then prove the up-to constants uniqueness of the natural measure on several random fractals, namely the SLE cut points, SLE boundary touching points, CLE pivotal points and the CLE carpet/gasket. As an application, we also show the equivalence between our natural measures defined in this paper (i.e. CLE pivotal and gasket meas

Kangqiang Li, Bingqi Liu, Yang Yang, Li Wang

In this paper, we construct a parameter estimation framework for robust low-rank tensor regression based on a truncation method and Huber loss, specifically focusing on models with random noise having only finite second-order moments. Through a robust gradient descent method, our proposed Huber-type estimator is theoretically optimal in two aspects: (1) its

Wei Yuan, Ling-Jie Zhou, Kaijie Yang, Yi-Fan Zhao

A quantum anomalous Hall (QAH) insulator is a topological state of matter, in which the interior is insulating but electrical current flows along the edges of the sample, in either clockwise (right-handed) or counter-clockwise (left-handed) direction dictated by the spontaneous magnetization orientation. Such chiral edge current (CEC) eliminates any backscat

Aaron Barrett, Jordan A. Brown, Margaret Anne Smith, Andrew Woodward

Subclinical leaflet thrombosis (SLT) is a potentially serious complication of aortic valve replacement with a bioprosthetic valve in which blood clots form on the replacement valve. SLT is associated with increased risk of transient ischemic attacks and strokes and can progress to clinical leaflet thrombosis. SLT following aortic valve replacement also may b

E. Jespers, A. Van Antwerpen, L. Vendramin

We study relations between different notions of nilpotency in the context of skew braces and applications to the structure of solutions to the Yang-Baxter equation. In particular, we consider annihilator nilpotent skew braces, an important class that turns out to be a brace-theoretic analog to the class of nilpotent groups. In this vein, several well-known t

Xavier Bekaert, Nicolas Boulanger, Andrea Campoleoni, Marco Chiodaroli

Higher Spin Gravity refers to extensions of gravity including at least one field of spin greater than two. These extensions are expected to provide manageable models of quantum gravity thanks to the infinite-dimensional (higher spin) gauge symmetry constraining them. One of the key aspects of Higher Spin Gravity/Symmetry is the range and diversity of topics

Roswitha Hofer, Gerhard Larcher

Mordechay Levin has constructed a number $α$ which is normal in base 2, and such that the sequence $\left\{2^n α\right\}_{n=0,1,2,\ldots}$ has very small discrepancy $D_N$. Indeed we have $N\cdot D_N = \mathcal{O} \left(\left(\log N\right)^2\right)$. That means, that $α$ is normal of extremely high quality. In this paper we show that this estimate is best po

Chaojun Li, Shi Qiu

This study proposes a recursive and easy-to-implement algorithm to compute the score and Hessian matrix in general regime-switching models. We use simulation to compare the asymptotic variance estimates constructed from the Hessian matrix and the outer product of the score. The results favor the latter.

Sally Dawson, Duarte Fontes, Samuel Homiller, Matthew Sullivan

The Standard Model effective field theory (SMEFT) is the tool of choice for studying deviations of Higgs couplings from the Standard Model predictions. The SMEFT is an expansion in an infinite tower of higher dimension operators, which is typically truncated at dimension-6. We consider the effective theory including dimension-8 operators and examine the matc

Wei Liu, Eduard Bykov, Sergey Taskaev, Mikhail Bogush

We are witnessing a great transition towards a society powered by renewable energies to meet the ever-stringent climate target. Hydrogen, as an energy carrier, will play a key role in building a climate-neutral society. Although liquid hydrogen is essential for hydrogen storage and transportation, liquefying hydrogen is costly with the conventional methods b

F. Acernese, M. Agathos, A. Ain, S. Albanesi

The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave signals in the past few years, alongside the two LIGO instruments. First, during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817) and then during the full

Mike Kosek, Hendrik Cech, Vaibhav Bajpai, Jörg Ott

Low-Earth Orbit satellites have gained momentum to provide Internet connectivity, augmenting those in the long-established geostationary orbits. At the same time, QUIC has been developed as the new transport protocol for the web. While QUIC traffic is fully encrypted, intermediaries such as performance enhancing proxies (PEPs) - in the past essential for Int

Yunzheng Su, Lei Jiang, Jie Cao

In recent years, with the development of computing resources and LiDAR, point cloud semantic segmentation has attracted many researchers. For the sparsity of point clouds, although there is already a way to deal with sparse convolution, multi-scale features are not considered. In this letter, we propose a feature extraction module based on multi-scale sparse

Ermis Mitsou, Jaiyul Yoo

In recent years new types of coordinate transformations have appeared in cosmology on top of the standard gauge transformations, such as the dilatations and special conformal transformations, or the ones leading to (conformal) Fermi coordinates. Some of these can remove effects that are invariant under the standard gauge transformations and also affect asymp

Junyi Li, Tianyi Tang, Jian-Yun Nie, Ji-Rong Wen

Pretrained language models (PLMs) have made remarkable progress in text generation tasks via fine-tuning. While, it is challenging to fine-tune PLMs in a data-scarce situation. Therefore, it is non-trivial to develop a general and lightweight model that can adapt to various text generation tasks based on PLMs. To fulfill this purpose, the recent prompt-based

Heinz-Jürgen Schmidt, Johannes Richter

We present a generalization of the Luttinger-Tisza-Lyons-Kaplan (LTLK) theory of classical ground states of Bravais lattices with Heisenberg coupling to non-Bravais lattices. It consists of adding certain Lagrange parameters to the diagonal of the Fourier transformed coupling matrix analogous to the theory of the general ground state problem already publishe

Valentin A. Skoutnev

We extend the scaling relations of stably stratified turbulence from the geophysical regime of unity Prandtl number to the astrophysical regime of extremely small Prandtl number applicable to stably stratified regions of stars and gas giants. A transition to a new turbulent regime is found to occur when the Prandtl number drops below the inverse of the buoya

Ian F. Putnam, Rodrigo Treviño

In [LT16], Kathryn Lindsey and the second author constructed a translation surface from a bi-infinite Bratteli diagram. We continue an investigation into these surfaces. The construction given in [LT16] was essentially combinatorial. Here, we provide explicit links between the path space of the Bratteli diagram and the surface, including various intermediate

Darian Tomašević, Peter Peer, Vitomir Štruc

Current state-of-the-art segmentation techniques for ocular images are critically dependent on large-scale annotated datasets, which are labor-intensive to gather and often raise privacy concerns. In this paper, we present a novel framework, called BiOcularGAN, capable of generating synthetic large-scale datasets of photorealistic (visible light and near-inf

Tobias Jawecki

The accumulated quadrature weights of Gaussian quadrature formulae constitute bounds on the integral over the intervals between the quadrature nodes. Classical results in this concern date back to works of Chebyshev, Markov and Stieltjes and are referred to as Separation Theorem of Chebyshev-Markov-Stieltjes (CMS Theorem). Similar separation theorems hold tr

Shima Salar Hosseini, Paeiz Azmi, Nader Mokari

In this letter, we propose reliable covert communications with the aim of minimizing age of information (AoI) in the time-varying channels. We named the time duration that channel state information (CSI) is valid as a new metric, as age of channel variation (AoC). To find reliable covert communication in a fresh manner in dynamic environments, this work cons

Lukas Westhofen, Christian Neurohr, Martin Butz, Maike Scholtes

Knowledge representation and reasoning has a long history of examining how knowledge can be formalized, interpreted, and semantically analyzed by machines. In the area of automated vehicles, recent advances suggest the ability to formalize and leverage relevant knowledge as a key enabler in handling the inherently open and complex context of the traffic worl

Sucharita Giri, Jean Christophe Tremblay, Gopal Dixit

Metal-corroles are macrocycle organic molecules with numerous practical applications. In particular, copper corroles exhibit an interesting saddled geometry, which has attracted significant attention from theoreticians and experimentalists over the years. The present work is dedicated to understand the effect of structural saddling in a copper corrole on pot

Zhendong Yang, Zhe Li, Mingqi Shao, Dachuan Shi

Knowledge distillation has been applied to various tasks successfully. The current distillation algorithm usually improves students&#39; performance by imitating the output of the teacher. This paper shows that teachers can also improve students&#39; representation power by guiding students&#39; feature recovery. From this point of view, we propose Masked Ge

Kyle Chard, Yadu Babuji, Anna Woodard, Ben Clifford

Parsl is a parallel programming library for Python that aims to make it easy to specify parallelism in programs and to realize that parallelism on arbitrary parallel and distributed computing systems. Parsl relies on developers annotating Python functions-wrapping either Python or external applications-to indicate that these functions may be executed concurr