July 2022 arXiv papers — page 56

Nicolas {El Maalouly}, Raphael Steiner, Lasse Wulf

Given an integer $k$ and a graph where every edge is colored either red or blue, the goal of the exact matching problem is to find a perfect matching with the property that exactly $k$ of its edges are red. Soon after Papadimitriou and Yannakakis (JACM 1982) introduced the problem, a randomized polynomial-time algorithm solving the problem was described by M

Qiang Wang, Shaohuai Shi, Kaiyong Zhao, Xiaowen Chu

Recent advanced studies have spent considerable human efforts on optimizing network architectures for stereo matching but hardly achieved both high accuracy and fast inference speed. To ease the workload in network design, neural architecture search (NAS) has been applied with great success to various sparse prediction tasks, such as image classification and

Anders Johansen, Thomas Ronnet, Martin Schiller, Zhengbin Deng

We present a series of papers dedicated to modelling the accretion and differentiation of rocky planets that form by pebble accretion within the lifetime of the protoplanetary disc. In this first paper, we focus on how the accreted ice determines the distribution of iron between the mantle (oxidized FeO and FeO$_{1.5}$) and the core (metallic Fe and FeS). We

Gyeong Hwan Jang, Sung Jin Kim, Mi Jin Lee, Seung-Woo Son

A pandemic, the worldwide spread of a disease, can threaten human beings from the social as well as biological perspectives and paralyze existing living habits. To stave off the more devastating disaster and return to a normal life, people make tremendous efforts at multiscale levels from individual to worldwide: paying attention to hand hygiene, developing

J. Sadeghi, S. Noori Gashti, F. Darabi

In this paper, we study a hybrid combination of Einstein-Hilbert action with curvature scalar $R$, and a function $f(\mathcal{R})$ in Palatini gravity within the context of inflationary scenario, from the Swampland conjecture point of view. This hybrid model has been paid attention in recent cosmological studies, and its applications have been widely studied

Jianfeng Huang, Chenyang Li, Yimin Lin, Shiguo Lian

It is hard to collect enough flaw images for training deep learning network in industrial production. Therefore, existing industrial anomaly detection methods prefer to use CNN-based unsupervised detection and localization network to achieve this task. However, these methods always fail when there are varieties happened in new signals since traditional end-t

Martin J. Gander, Hui Zhang

Schwarz methods use a decomposition of the computational domain into subdomains and need to put boundary conditions on the subdomain boundaries. In domain truncation one restricts the unbounded domain to a bounded computational domain and also needs to put boundary conditions on the computational domain boundaries. It turns out to be fruitful to think of the

Aijin Li, Gen Li, Lei Sun, Xintao Wang

Blind face restoration usually encounters with diverse scale face inputs, especially in the real world. However, most of the current works support specific scale faces, which limits its application ability in real-world scenarios. In this work, we propose a novel scale-aware blind face restoration framework, named FaceFormer, which formulates facial feature

Stefano Ponzoni, Felix Paßlack, Matija Stupar, David Maximilian Janas

We have studied the energy dispersion of the Dirac bands of the topological insulator Bi2Se3 at large parallel momenta using a setup for laser-based time-resolved momentum microscopy with 6 eV probe-photons. Using this setup, we can probe the manifold of unoccupied states up to higher intermediate-state energies in a wide momentum window. We observe a strong

Gulcin Dinc Yalcin, Frank E. Curtis

Algorithms for solving nonconvex, nonsmooth, finite-sum optimization problems are proposed and tested. In particular, the algorithms are proposed and tested in the context of an optimization problem formulation arising in semi-supervised machine learning. The common feature of all algorithms is that they employ an incremental quasi-Newton (IQN) strategy, spe

Martin Hils, Rosario Mennuni

We exhibit a theory where definable types lack the amalgamation property.

HaeChun Chung, JooYong Shim, Jong-Kook Kim

Multiple modalities for certain information provide a variety of perspectives on that information, which can improve the understanding of the information. Thus, it may be crucial to generate data of different modality from the existing data to enhance the understanding. In this paper, we investigate the cross-modal audio-to-image generation problem and propo

Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann

Diffusion models have emerged as one of the most promising frameworks for deep generative modeling. In this work, we explore the potential of non-uniform diffusion models. We show that non-uniform diffusion leads to multi-scale diffusion models which have similar structure to this of multi-scale normalizing flows. We experimentally find that in the same or l

Christian Aarset, Andreas Habring, Martin Holler, Mario Mitter

In this work, a method for unsupervised energy disaggregation in private households equipped with smart meters is proposed. This method aims to classify power consumption as active or passive, granting the ability to report on the residents' activity and presence without direct interaction. This lays the foundation for applications like non-intrusive health

Sangkeum Lee, Sarvar Hussain Nengroo, Hojun Jin, Yoonmee Doh

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time was obtained from 900 households of single apartments. To detect outliers and missing values in smart meter data, a deep learning model, the autoencoder, consisting of a graph convolutional network and

Zheng Chen, Ziwei Yang, Lingwei Zhu, Guang Shi

Defining and separating cancer subtypes is essential for facilitating personalized therapy modality and prognosis of patients. The definition of subtypes has been constantly recalibrated as a result of our deepened understanding. During this recalibration, researchers often rely on clustering of cancer data to provide an intuitive visual reference that could

Yannick Couzinié

We consider the multicolour East model, a model of glass forming liquids closely related to the East model on $\mathbb{Z}^d$. The state space ${(G\cup \{\star\})}^{\mathbb{Z}^d}$ consists of $|G|\le 2^d$ different vacancy types and the neutral state $\star$. To each $h\in G$ we associate unique facilitation mechanisms ${\{c_x^{h}\}}_{x\in \mathbb{Z}^d}$ that

J. Lerendegui Marco, V. Babiano-Suárez, J. Balibrea-Correa, L. Caballero

GN-Vision is a novel dual $\gamma$-ray and neutron imaging system, which aims at simultaneously obtaining information about the spatial origin of $\gamma$-ray and neutron sources. The proposed device is based on two position sensitive detection planes and exploits the Compton imaging technique for the imaging of $\gamma$-rays. In addition, spatial distributi

Henrik J. Munch

We study Feynman integrals in the framework of Gel'fand-Kapranov-Zelevinsky (GKZ) hypergeometric systems. The latter defines a class of functions wherein Feynman integrals arise as special cases, for any number of loops and kinematic scales. Utilizing the GKZ system and its relation to $D$-module theory, we propose a novel method for obtaining differential e

Kristina Schaefer, Joachim Weickert

The central limit theorem suggests Gaussian convolution as a generic blur model for images. Since Gaussian convolution is equivalent to homogeneous diffusion filtering, one way to deblur such images is to diffuse them backwards in time. However, backward diffusion is highly ill-posed. Thus, it requires stabilisation in the model as well as highly sophisticat

Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni, Nicu Sebe

3D LiDAR semantic segmentation is fundamental for autonomous driving. Several Unsupervised Domain Adaptation (UDA) methods for point cloud data have been recently proposed to improve model generalization for different sensors and environments. Researchers working on UDA problems in the image domain have shown that sample mixing can mitigate domain shift. We

Shuyi Mao, Xinpeng Li, Junyao Chen, Xiaojiang Peng

The paper describes our proposed methodology for the six basic expression classification track of Affective Behavior Analysis in-the-wild (ABAW) Competition 2022. In Learing from Synthetic Data(LSD) task, facial expression recognition (FER) methods aim to learn the representation of expression from the artificially generated data and generalise to real data.

Kevin Kamm, Stefano Pagliarani, Andrea Pascucci

In this paper, we show how the It\^o-stochastic Magnus expansion can be used to efficiently solve stochastic partial differential equations (SPDE) with two space variables numerically. To this end, we will first discretize the SPDE in space only by utilizing finite difference methods and vectorize the resulting equation exploiting its sparsity. As a benchmar

Yusuke Hosoya, Masanori Suganuma, Takayuki Okatani

Open-set object detection (OSOD), a task involving the detection of unknown objects while accurately detecting known objects, has recently gained attention. However, we identify a fundamental issue with the problem formulation employed in current OSOD studies. Inherent to object detection is knowing "what to detect," which contradicts the idea of identifying

Edoardo Remelli, Timur Bagautdinov, Shunsuke Saito, Tomas Simon

Photorealistic telepresence requires both high-fidelity body modeling and faithful driving to enable dynamically synthesized appearance that is indistinguishable from reality. In this work, we propose an end-to-end framework that addresses two core challenges in modeling and driving full-body avatars of real people. One challenge is driving an avatar while s

Shakul Awasthi, Sreedhar B. Dutta

We employ an appropriate perturbative scheme in the large viscous regime to study oscillating states in driven Langevin systems. We explicitly determine oscillating state distribution of under-damped Brownian particle subjected to thermal, viscous and potential drives to linear order in anharmonic perturbation. We also evaluate various non-equilibrium observ

Abbas Taherpour, Shaban Ghalandarzadeh, Parastoo Malakooti Rad, Parvin Safari

In this paper, we further study the theory of Intuitionistic fuzzy submodules and we will define intuitionistic fuzzy primary submodule with the help of the definition of a radical submodule, and we also study the properties of these submodules. Furthermore, homomorphic image and pre-image of intuitionistic fuzzy primary submodule are investigated.

Ricardo Bigolin Lanfredi, Joyce D. Schroeder, Tolga Tasdizen

Convolutional neural networks (CNNs) have been successfully applied to chest x-ray (CXR) images. Moreover, annotated bounding boxes have been shown to improve the interpretability of a CNN in terms of localizing abnormalities. However, only a few relatively small CXR datasets containing bounding boxes are available, and collecting them is very costly. Opport

Alvaro Corral, Montserrat García del Muro

Using demographic data of high spatial resolution for a region in the south of Europe, we study the population over fixed-size spatial cells. We find that, counterintuitively, the distribution of the number of inhabitants per cell increases its variability when the size of the cells is increased. Nevertheless, the shape of the distributions is kept constant,

Samir Jain, Ayan Seal, Aparajita Ojha

Wireless Capsule Endoscopy is one of the most advanced non-invasive methods for the examination of gastrointestinal tracts. An intelligent computer-aided diagnostic system for detecting gastrointestinal abnormalities like polyp, bleeding, inflammation, etc. is highly exigent in wireless capsule endoscopy image analysis. Abnormalities greatly differ in their

Francesco Quinzan, Cecilia Casolo, Krikamol Muandet, Yucen Luo

Notions of counterfactual invariance (CI) have proven essential for predictors that are fair, robust, and generalizable in the real world. We propose graphical criteria that yield a sufficient condition for a predictor to be counterfactually invariant in terms of a conditional independence in the observational distribution. In order to learn such predictors,

Qinying Liu, Zilei Wang

In this work, we consider the problem of cross-domain 3D action recognition in the open-set setting, which has been rarely explored before. Specifically, there is a source domain and a target domain that contain the skeleton sequences with different styles and categories, and our purpose is to cluster the target data by utilizing the labeled source data and

Hao Liu, Jiancheng An, Wangyang Xu, Xing Jia

Reconfigurable intelligent surface (RIS) has recently emerged as a promising technology enabling next-generation wireless networks. In this letter, we develop an improved index modulation (IM) scheme by utilizing RIS to convey information. Specifically, we study an RIS-aided multiple-input single-output (MISO) system, in which the information bits are convey

Can Firtina, Kamlesh Pillai, Gurpreet S. Kalsi, Bharathwaj Suresh

Profile hidden Markov models (pHMMs) are widely employed in various bioinformatics applications to identify similarities between biological sequences, such as DNA or protein sequences. In pHMMs, sequences are represented as graph structures. These probabilities are subsequently used to compute the similarity score between a sequence and a pHMM graph. The Bau

G. La Mura, J. Becerra Gonzalez, G. Chiaro, S. Ciroi

The relativistic jets produced by some Active Galactic Nuclei (AGNs) are among the most efficient persistent sources of non-thermal radiation and represent an ideal laboratory for studying high-energy interactions. In particular, when the relativistic jet propagates along the observer's line of sight, the beaming effect produces dominant signatures in the ob

Cristiano Saltori, Evgeny Krivosheev, Stéphane Lathuilière, Nicu Sebe

3D point cloud semantic segmentation is fundamental for autonomous driving. Most approaches in the literature neglect an important aspect, i.e., how to deal with domain shift when handling dynamic scenes. This can significantly hinder the navigation capabilities of self-driving vehicles. This paper advances the state of the art in this research field. Our fi

Saptarshi Roy Chowdhury, Swarupananda Pradhan

We generalize Grover algorithm with two arbitrary phases in a density matrix set up. We give exact analytic expressions for the success probability after arbitrary number of iteration of the generalized Grover operator as a function of number of iterations, two phase angles ({\alpha}, \{beta}) and parameter {\xi} introduced in the off diagonal terms of the d

Ilaria Carleo, Paolo Giacobbe, Gloria Guilluy, Patricio E. Cubillos

Detections of molecules in the atmosphere of gas giant exoplanets allow us to investigate the physico-chemical properties of the atmospheres. Their inferred chemical composition is used as tracer of planet formation and evolution mechanisms. Currently, an increasing number of detections is showing a possible rich chemistry of the hotter gaseous planets, but

G. Guilluy, P. Giacobbe, I. Carleo, P. E. Cubillos

The field of exo-atmospheric characterisation is progressing at an extraordinary pace. Atmospheric observations are now available for tens of exoplanets, mainly hot and warm inflated gas giants, and new molecular species continue to be detected revealing a richer atmospheric composition than previously expected. Thanks to its warm equilibrium temperature (96

Huabin Liu, Weixian Lv, John See, Weiyao Lin

A primary challenge faced in few-shot action recognition is inadequate video data for training. To address this issue, current methods in this field mainly focus on devising algorithms at the feature level while little attention is paid to processing input video data. Moreover, existing frame sampling strategies may omit critical action information in tempor

Georg C. Hofstätter, Jonas Knoerr

Characterizations of all continuous, additive and $\mathrm{GL}(n)$-equivariant endomorphisms of the space of convex functions on a Euclidean space $\mathbb{R}^n$, of the subspace of convex functions that are finite in a neighborhood of the origin, and of finite convex functions are established. Moreover, all continuous, additive, monotone endomorphisms of th

Rafael Vazquez, Jing Zhang, Jie Qi, Miroslav Krstic

Recently, the problem of boundary stabilization and estimation for unstable linear constant-coefficient reaction-diffusion equation on n-balls (in particular, disks and spheres) has been solved by means of the backstepping method. However, the extension of this result to spatially-varying coefficients is far from trivial. Some early success has been achieved

Bingrong Huang

In this paper, we prove the smooth cubic moments vanish for the Hecke--Maass cusp forms, which gives a new case of the random wave conjecture. In fact, we can prove a polynomial decay for the smooth cubic moments, while for the smooth second moment (i.e. QUE) no rate of decay is known unconditionally for general Hecke--Maass cusp forms. The proof bases on va

Kamalendu Ghosh, Victor Lefevre, Oscar Lopez-Pamies

This paper presents the derivation of the homogenized equations that describe the macroscopic mechanical response of elastomers filled with liquid inclusions in the setting of small quasistatic deformations. The derivation is carried out for materials with periodic microstructure by means of a two-scale asymptotic analysis. The focus is on the non-dissipativ

Qian Wu, Xurong Chen

In this work, we consider the muonic LiH as a new stage of the $\mu$ catalyzed fusion. We calculate the bound states of the muonic LiH and LiH$^+$ and their wave functions based on the three and four body approximation. In order to solve the Schr$\ddot{\rm o}$dinger equation, we apply the Gaussian expansion method which gives us both the eigen energies and t

Nicolás Cuello, François Ménard, Daniel J. Price

We review the role of stellar flybys and encounters in shaping planet-forming discs around young stars, based on the published literature on this topic in the last 30 years. Since most stars $\leq~2$ Myr old harbour protoplanetary discs, tidal perturbations affect planet formation. First, we examine the probability of experiencing flybys or encounters: More

Julien Baste, Dimitrios M. Thilikos

Given a graph $G$, we define ${\bf bcg}(G)$ as the minimum $k$ for which $G$ can be contracted to the uniformly triangulated grid $\Gamma_{k}$. A graph class ${\cal G}$ has the SQG${\bf C}$ property if every graph $G\in{\cal G}$ has treewidth $\mathcal{O}({\bf bcg}(G)^{c})$ for some $1\leq c<2$. The SQG${\bf C}$ property is important for algorithm design as

Saswat Das, Rakshit Naidu

Given the progressive nature of the world today, fairness is a very important social aspect in various areas, and it has long been studied with the advent of technology. To the best of our knowledge, methods of quantifying fairness errors and fairness in privacy threat models have been absent. To this end, in this short paper, we examine notions of fairness

Matteo Farnesi Camellone, Filip Dvořák, Mykhailo Vorokhta, Andrii Tovt

Single-atom catalysts represent an essential and ever-growing family of heterogeneous catalysts. Recent studies indicate that besides the valuable catalytic properties provided by single-atom active sites, the presence of single-atom sites on the catalyst substrates may significantly influence the population of supported metal nanoparticles coexisting with m

Siyang Li, Yifan Xu, Huanyu Wu, Dongrui Wu

Facial affect analysis remains a challenging task with its setting transitioned from lab-controlled to in-the-wild situations. In this paper, we present novel frameworks to handle the two challenges in the 4th Affective Behavior Analysis In-The-Wild (ABAW) competition: i) Multi-Task-Learning (MTL) Challenge and ii) Learning from Synthetic Data (LSD) Challeng

Longshen Ou, Xiangming Gu, Ye Wang

Automatic speech recognition (ASR) has progressed significantly in recent years due to the emergence of large-scale datasets and the self-supervised learning (SSL) paradigm. However, as its counterpart problem in the singing domain, the development of automatic lyric transcription (ALT) suffers from limited data and degraded intelligibility of sung lyrics. T

Rakshit Naidu, Navid Kagalwalla

Causal questions often permeate in our day-to-day activities. With causal reasoning and counterfactual intuition, privacy threats can not only be alleviated but also prevented. In this paper, we discuss what is causal and counterfactual reasoning and how this can be applied in the field of privacy threat modelling (PTM). We believe that the future of PTM rel

Xabier Rey Barreiro, Alejandro F. Villaverde

The structural identifiability and the observability of a model determine the possibility of inferring its parameters and states by observing its outputs. These properties should be analysed before attempting to calibrate a model. Unfortunately, such \textit{a priori} analysis can be challenging, since it requires symbolic calculations that often have a high

Yansong Gao, Jianrong Yao, Lihui Pang, Wei Yang

To improve the modeling resilience of silicon strong physical unclonable functions (PUFs), in particular, the APUFs, that yield a very large number of challenge response pairs (CRPs), a number of composited APUF variants such as XOR-APUF, interpose-PUF (iPUF), feed-forward APUF (FF-APUF),and OAX-APUF have been devised. When examining their security in terms

Xiong-Hui Cao, Qu-Zhi Li, Han-Qing Zheng

The hyperbolic version of Roy-Steiner equation describing low energy $\pi N$ scatterings, with larger analyticity domain in the complex $s$ plane is solved. The numerical results on phase shifts of low partial waves are in agreement with that of Hoferichter et al. [Phys. Rept. 625 (2016) 1]. A subthreshold pole in $S_{11}$ channel is found located at $\sqrt{

Mattia Alberto Ubertini, Jan Smrek, Angelo Rosa

Current theories on the conformation and dynamics of unknotted and non-concatenated ring polymers in melt conditions describe each ring as a tree-like double-folded object. While evidence from simulations supports this picture on a single ring level, other works show pairs of rings also thread each other - a feature overlooked in the tree theories. Here we r

V. G. Klochkova, V. E. Panchuk

In the optical spectra of the cold post-AGB supergiant GSC 04050$-$02366, obtained with the 6-meter BTA telescope with a spectral resolution of R$\ge$60000 on arbitrary dates over 2019$\div$2021, a radial velocity variability is found. Heliocentric Vr based on the positional measurements of numerous absorptions varies from date to date with a standard deviat

Julian Schön, Raghavendra Selvan, Jens Petersen

Generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) play an increasingly important role in medical image analysis. The latent spaces of these models often show semantically meaningful directions corresponding to human-interpretable image transformations. However, until now, their exploration for medical images

Jie Yan, Yunlei Lu, Liting Chen, Si Qin

This paper investigates a critical resource allocation problem in the first party cloud: scheduling containers to machines. There are tens of services and each service runs a set of homogeneous containers with dynamic resource usage; containers of a service are scheduled daily in a batch fashion. This problem can be naturally formulated as Stochastic Bin Pac

Marcin Anholcer, Bartłomiej Bosek, Jarosław Grytczuk, Grzegorz Gutowski

A majority coloring of a directed graph is a vertex coloring in which each vertex has the same color as at most half of its out-neighbors. In this note we simplify some proof techniques and generalize previously known results on various generalizations of majority coloring. In particular, our unified and simplified approach works for paintability - an on-lin

Hezekiah Grayer

This work examines the dynamics of density patches in the 2D zero-diffusivity Boussinesq system modified such that momentum is in a large Prandtl number balance. We establish the global well-posedness of this system for compactly supported and bounded initial densities, and then examine the regularity of the evolving boundary of patch solutions. For $k \in \

Jürgen Seiler, Susanne Schöll, Wolfgang Schnurrer, André Kaup

A problem often arising in video communication is the reconstruction of missing or distorted areas in a video sequence. Such holes of unavailable pixels may be caused for example by transmission errors of coded video data or undesired objects like logos. In order to close the holes given neighboring available content, a signal extrapolation has to be perform

Luca Ciotti

Recently, it has been suggested that the phenomenology of flat rotation curves observed at large radii in the equatorial plane of disk galaxies can be explained as a manifestation of General Relativity instead of the effect of Dark Matter halos. In this paper, by using the well known weak field, low velocity gravitomagnetic formulation of GR, the expected ro

Liliang Chen, Jiaqi Li, Han Huang, Yandong Guo

We propose CrossHuman, a novel method that learns cross-guidance from parametric human model and multi-frame RGB images to achieve high-quality 3D human reconstruction. To recover geometry details and texture even in invisible regions, we design a reconstruction pipeline combined with tracking-based methods and tracking-free methods. Given a monocular RGB se

Chris Fields, Karl Friston, James F. Glazebrook, Michael Levin

We show how any system with morphological degrees of freedom and locally limited free energy will, under the constraints of the free energy principle, evolve toward a neuromorphic morphology that supports hierarchical computations in which each level of the hierarchy enacts a coarse-graining of its inputs, and dually a fine-graining of its outputs. Such hier

Thomas Deppisch, Sebastià V. Amengual Garí, Paul Calamia, Jens Ahrens

Psychoacoustic experiments have shown that directional properties of the direct sound, salient reflections, and the late reverberation of an acoustic room response can have a distinct influence on the auditory perception of a given room. Spatial room impulse responses (SRIRs) capture those properties and thus are used for direction-dependent room acoustic an

Daiki Takeuchi, Yasunori Ohishi, Daisuke Niizumi, Noboru Harada

The amount of audio data available on public websites is growing rapidly, and an efficient mechanism for accessing the desired data is necessary. We propose a content-based audio retrieval method that can retrieve a target audio that is similar to but slightly different from the query audio by introducing auxiliary textual information which describes the dif

Anthony J Guttmann, Iwan Jensen, Aleksander L Owczarek

We have studied self-avoiding walks contained within an $L \times L$ square whose end-points can lie anywhere within, or on, the boundaries of the square. We prove that such walks behave, asymptotically, as walks crossing a square (WCAS), being those walks whose end-points lie at the south-east and north-west corners of the square. We provide numerical data,

Alexander Evako

This article provides a brief overview of the main results in the field of contractible digital spaces and contractible transformations of digital spaces and contains new results. We introduce new types of contractible digital spaces such as the cone and the double cone. Based on this, we introduce new contractible transformations that covert the digital spa

Jürgen Seiler, Thomas Richter, André Kaup

The prediction step is a very important part of hybrid video codecs. In this contribution, a novel spatio-temporal prediction algorithm is introduced. For this, the prediction is carried out in two steps. Firstly, a preliminary temporal prediction is conducted by motion compensation. Afterwards, spatial refinement is carried out for incorporating spatial red

Maryam Abdolali, Nicolas Gillis

Subspace clustering is the classical problem of clustering a collection of data samples that approximately lie around several low-dimensional subspaces. The current state-of-the-art approaches for this problem are based on the self-expressive model which represents the samples as linear combination of other samples. However, these approaches require sufficie

Jürgen Seiler, Haricharan Lakshman, André Kaup

Within the scope of this contribution we propose a novel efficient spatio-temporal prediction algorithm for video coding. The algorithm operates in two stages. First, motion compensation is performed on the block to be predicted in order to exploit temporal correlations. Afterwards, in order to exploit spatial correlations, this preliminary estimate is spati

Giacomo Lucertini, Stefano Pagliarani, Andrea Pascucci

In this paper we prove strong well-posedness for a system of stochastic differential equations driven by a degenerate diffusion satisfying a weak-type H\"ormander condition, assuming H\"older regularity assumptions on the drift coefficient. This framework encompasses, as particular cases, stochastic Langevin systems of kinetic SDEs. The drift coefficient of

Kyung-Min Jin, Gun-Hee Lee, Seong-Whan Lee

Although many approaches for multi-human pose estimation in videos have shown profound results, they require densely annotated data which entails excessive man labor. Furthermore, there exists occlusion and motion blur that inevitably lead to poor estimation performance. To address these problems, we propose a method that leverages an attention mask for occl

Jürgen Seiler, Katrin Meisinger, André Kaup

This paper describes a very efficient algorithm for image signal extrapolation. It can be used for various applications in image and video communication, e.g. the concealment of data corrupted by transmission errors or prediction in video coding. The extrapolation is performed on a limited number of known samples and extends the signal beyond these samples.

Frédéric Prost

We discuss some issues to the inheritance of crypto assets. We propose a distributed, privacy preserving, protocol to establish a consensus on the death of the owner of crypto assets: the Tales From the Crypt Protocol. Until the actual death of the owner no link can be made between public information and the corresponding crypto assets. This protocol is gene

S Breteaux, F Nier

In this article we reconsider the problem of the propagation of waves in a random medium in a kinetic regime. The final aim of this program would be the understanding of the conditions which allow to derive a kinetic or radiative transfer equation. Although it is not reached for the moment, accurate and somehow surprising number estimates in the Fock space s

Nicolas Lemoine

In a 1969 article, A. Dress described the prime ideals of the Burnside ring of a finite group G and the inclusion relations between them. One may ask whether similar results exist for the Burnside ring of a saturated fusion system F on a finite p-group S. The present paper answers positively, providing a typology for the prime ideals of A(F) and for those of

Conghui Hu, Gim Hee Lee

Current supervised cross-domain image retrieval methods can achieve excellent performance. However, the cost of data collection and labeling imposes an intractable barrier to practical deployment in real applications. In this paper, we investigate the unsupervised cross-domain image retrieval task, where class labels and pairing annotations are no longer a p

Wen Wen, Lu Zhou, Zhenjun Zhang, Hui-jun Li

The system of Bose-Fermi superfluid mixture offers a playground to explore rich macroscopic quantum phenomena. In a recent experiment of Yao {\it et al.} [Phys. Rev. Lett. {\bf 117}, 145301 (2016)], $^{41}$K-$^{6}$Li superfluid mixture is implemented. Coupled quantized vortices are generated via rotating the superfluid mixture, and a few unconventional behav

Kexiang Yang, Ercai Chen, Zijie Lin, Xiaoyao Zhou

Let $f_{i},i=1,2$ be continuous bundle random dynamical systems over an ergodic compact metric system $(\Omega,\mathcal{F},\mathbb{P},\vartheta)$. Assume that ${\bf a}=(a_{1},a_{2})\in\mathbb{R}^{2}$ with $a_{1}>0$ and $a_{2}\geq0$, $f_{2}$ is a factor of $f_{1}$ with a factor map $\Pi:\Omega\times X_{1}\rightarrow\Omega\times X_{2}$. We define the ${\bf a}$

Fernando Gómez-Ortiz, Pablo García-Fernández, Juan M. López, Javier Junquera

We study the emergence of Berezinskii-Kosterlitz-Thouless (BKT) phases in (PbTiO$_3$)$_3$/(SrTiO$_3$)$_3$ superlattices by means of second-principles simulations. Beyond a threshold tensile epitaxial strain of $\epsilon = 0.25 \%$ the local dipole moments within the superlattices are confined to the film-plane, and thus the polarization can be effectively co

E. Osinga, R. J. van Weeren, F. Andrade-Santos, L. Rudnick

It has been well established that galaxy clusters have magnetic fields. The exact properties and origin of these magnetic fields are still uncertain even though these fields play a key role in many astrophysical processes. Various attempts have been made to derive the magnetic field strength and structure of nearby galaxy clusters using Faraday rotation of e

Yanan Chang, Yi Wu, Xiangyu Miao, Jiahe Wang

Facial valence/arousal, expression and action unit are related tasks in facial affective analysis. However, the tasks only have limited performance in the wild due to the various collected conditions. The 4th competition on affective behavior analysis in the wild (ABAW) provided images with valence/arousal, expression and action unit labels. In this paper, w

Eugenio Lippiello, Giuseppe Petrillo, Lucilla de Arcangelis

The identification of the transmission parameters of a virus is fundamental to identify the optimal public health strategy. These parameters can present significant changes over time caused by genetic mutations or viral recombination, making their continuous monitoring fundamental. Here we present a method, suitable for this task, which uses as unique inform

Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull

Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environments. Agent-based models (ABMs) are an increasingly popular simulation paradigm that can represent the heterogeneity of contact interactions with granular detail and agency of individ

Or Wertheim, Dan R. Suissa, Ronen I. Brafman

To enable robots to achieve high level objectives, engineers typically write scripts that apply existing specialized skills, such as navigation, object detection and manipulation to achieve these goals. Writing good scripts is challenging since they must intelligently balance the inherent stochasticity of a physical robot's actions and sensors, and the limit

Stalin Muñoz Gutiérrez, Gerald Steinbauer-Wagner

Long-term autonomy of robotic systems implicitly requires dependable platforms that are able to naturally handle hardware and software faults, problems in behaviors, or lack of knowledge. Model-based dependable platforms additionally require the application of rigorous methodologies during the system development, including the use of correct-by-construction

Andrea Gatti, Viviana Mascardi

Automating a factory where robots are involved is neither trivial nor cheap. Engineering the factory automation process in such a way that return of interest is maximized and risk for workers and equipment is minimized, is hence of paramount importance. Simulation can be a game changer in this scenario but requires advanced programming skills that domain exp

Manfried Faber

In the model of topological particles we have four types of topologically stable dual Dirac monopoles with soft core and finite mass. We discuss the steps how to get a Dirac equation for these particles. We show for the free and the interacting case that we arrive at the Dirac equation in the limit, where the soft solitons approach singular dual Dirac monopo

Timotheos Souroulla, Alberto Hata, Ahmad Terra, Özer Özkahraman

The number of mobile robots with constrained computing resources that need to execute complex machine learning models has been increasing during the past decade. Commonly, these robots rely on edge infrastructure accessible over wireless communication to execute heavy computational complex tasks. However, the edge might become unavailable and, consequently,

Wenjie Pei, Xin Feng, Canmiao Fu, Qiong Cao

The key challenge of sequence representation learning is to capture the long-range temporal dependencies. Typical methods for supervised sequence representation learning are built upon recurrent neural networks to capture temporal dependencies. One potential limitation of these methods is that they only model one-order information interactions explicitly bet

Yaniel Carreno, Yvan Petillot, Ronald P. A. Petrick

In real-world applications, the ability to reason about incomplete knowledge, sensing, temporal notions, and numeric constraints is vital. While several AI planners are capable of dealing with some of these requirements, they are mostly limited to problems with specific types of constraints. This paper presents a new planning approach that combines contingen

Debora C. Engelmann, Angelo Ferrando, Alison R. Panisson, Davide Ancona

This paper presents a Runtime Verification (RV) approach for Multi-Agent Systems (MAS) using the JaCaMo framework. Our objective is to bring a layer of security to the MAS. This layer is capable of controlling events during the execution of the system without needing a specific implementation in the behaviour of each agent to recognise the events. MAS have b

Rodica Condurache, Catalin Dima, Madalina Jitaru, Youssouf Oualhadj

Careful rational synthesis was defined in (Condurache et al. 2021) as a quantitative extension of Fisman et al.'s rational synthesis (Fisman et al. 2010), as a model of multi-agent systems in which agents are interacting in a graph arena in a turn-based fashion. There is one common resource, and each action may decrease or increase the resource. Each agent h

Dara MacConville, Marie Farrell, Matt Luckcuck, Rosemary Monahan

Software verification is an important tool in establishing the reliability of critical systems. One potential area of application is in the field of robotics, as robots take on more tasks in both day-to-day areas and highly specialised domains. Robots are usually given a plan to follow, if there are errors in this plan the robot will not perform reliably. Th

Chia-Chi Chuang, Donglin Yang, Chuan Wen, Yang Gao

Imitation learning is a widely used policy learning method that enables intelligent agents to acquire complex skills from expert demonstrations. The input to the imitation learning algorithm is usually composed of both the current observation and historical observations since the most recent observation might not contain enough information. This is especiall

Pratik D. Patel, Akariti Sharma, Bharathiganesh Devanarayanan, Paramita Dutta

We report various phase transitions in half-Heusler TbPtBi compound using Density Functional Theory (DFT). Specifically, inclusion of spin-orbit coupling (SOC) leads to band inversion resulting in transition from the metallic to the topological semimetallic phase. However, in presence of SOC, there is a phase transition from the topological semimetal to the

Michel Van den Bergh

Non-commutative crepant resolutions (NCCRs) are non-commutative analogues of the usual crepant resolutions that appear in algebraic geometry. In this paper we survey some results around NCCRs.

Olivia Monjon, Jérôme Scherer, Florence Sterck

We prove that localization functors of crossed modules of groups do not always admit fiberwise (or relative) versions. To do so we characterize the existence of a fiberwise localization by a certain normality condition and compute explicit examples and counter-examples. In fact, some nullification functors do not behave well and we also prove that the fiber