October 2022 arXiv papers — page 4

Maximilian Ramgraber, Ricardo Baptista, Dennis McLaughlin, Youssef Marzouk

Smoothing is a specialized form of Bayesian inference for state-space models that characterizes the posterior distribution of a collection of states given an associated sequence of observations. Ramgraber et al. (2023) proposes a general framework for transport-based ensemble smoothing, which includes linear Kalman-type smoothers as special cases. Here, we b

Anand Sivaramakrishnan, Peter Tuthill, James P. Lloyd, Alexandra Z. Greenbaum

The James Webb Space Telescope's Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 \micron~wavelengths, and a bright limit of $\simeq 4$ magnitudes in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers un

B. Biswas, E. E. O. Ishida, J. Peloton, A. Moller

We describe the fast transient classification algorithm in the center of the kilonova (KN) science module currently implemented in the Fink broker and report classification results based on simulated catalogs and real data from the ZTF alert stream. We used noiseless, homogeneously sampled simulations to construct a basis of principal components (PCs). All l

Xiaochuang Han, Sachin Kumar, Yulia Tsvetkov

Despite the growing success of diffusion models in continuous-valued domains (e.g., images), similar efforts for discrete domains such as text have yet to match the performance of autoregressive language models. In this work, we present SSD-LM -- a diffusion-based language model with two key design choices. First, SSD-LM is semi-autoregressive, iteratively g

P. Console Camprini, F. Leone, C. Massimi, A. Musumarra

Fast neutron detection is often based on the neutron-proton elastic scattering reaction: the ionization caused by recoil protons in a hydrogenous material constitutes the basic information for the design and development of a class of neutron detectors. Although experimental techniques have continuously improved, proton-recoil track imaging remains still at t

Yuan Lian, Mark I. Richardson

We present a new planetary global circulation model, planetMPAS, based on the state-of-the-art NCAR MPAS General Circulation Model. Taking advantage of the cross compatibility between WRF and MPAS, planetMPAS includes most of the planetWRF physics parameterization schemes for terrestrial planets such as Mars and Titan. PlanetMPAS also includes a set of physi

Yaroslav Alekseev, Edward A. Hirsch

The (extended) Binary Value Principle (eBVP: $\sum_{i=1}^n x_i2^{i-1} = -k$ for $k>0$ and $x^2_i=x_i$) has received a lot of attention recently, several lower bounds have been proved for it (Alekseev et al 2020, Alekseev 2021, Part and Tzameret 2021). Also it has been shown (Alekseev et al 2020) that the probabilistically verifiable Ideal Proof System (IPS)

Zeyu Zhang, Dylan Valente, Yuliang Shi, Dil K. Limbu

The advent of pi-stacked layered metal-organic frameworks (MOFs) opened up new horizons for designing compact MOF-based devices as they offer unique electrical conductivity on top of permanent porosity and exceptionally high surface area. By taking advantage of the modular nature of these electrically conductive (EC) MOFs, an unlimited number of materials ca

Qiaoqiao Hua, Chunhua Wang, Jing Yang

In the present paper, we consider the Chern-Simons-Schr\"{o}dinger system \begin{equation} \left\{ \begin{aligned} &-\varepsilon^{2}\Delta u+V(x)u+(A_{0}+A_{1}^{2}+A_{2}^{2})u=|u|^{p-2}u,\,\,\,\,x\in \mathbb{R}^2,\\ &\partial_1 A_0 = A_2 u^2,\ \partial_{2}A_{0}=-A_{1}u^{2},\\ &\partial_{1}A_{2}-\partial_{2}A_{1}=-\frac{1}{2}|u|^{2},\ \partial_{1}A_{1}+\parti

Yifan Zhang, Haowei He, Zhiquan Tan, Yang Yuan

In the current landscape of explanation methodologies, most predominant approaches, such as SHAP and LIME, employ removal-based techniques to evaluate the impact of individual features by simulating various scenarios with specific features omitted. Nonetheless, these methods primarily emphasize efficiency in the original context, often resulting in general i

Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro

Group convolutional neural networks are a useful tool for utilizing symmetries known to be in a signal; however, they require that the signal is defined on the group itself. Existing approaches either work directly with group signals, or they impose a lifting step with heuristics to compute the convolution which can be computationally costly. Taking an algeb

Vincent Grondin, Jean-Michel Fortin, François Pomerleau, Philippe Giguère

Tree perception is an essential building block toward autonomous forestry operations. Current developments generally consider input data from lidar sensors to solve forest navigation, tree detection and diameter estimation problems. Whereas cameras paired with deep learning algorithms usually address species classification or forest anomaly detection. In eit

R. Garioud, F. Šimkovic, R. Rossi, G. Spada

We introduce a spin-symmetry-broken extension of the connected determinant algorithm [Phys. Rev. Lett. 119, 045701 (2017)]. The resulting systematic perturbative expansions around an antiferromagnetic state allow for numerically exact calculations directly inside a magnetically ordered phase. We show new precise results for the magnetic phase diagram and the

Zhoujian Cao, Xiaokai He, Zhi-Chao Zhao

It is well known that energy fluxes will produce gravitational wave memory. The gravitational wave memory produced by background including cosmic microwave background (CMB), cosmic neutrino background (C$\nu$B), and gravitational wave background is investigated in this work. We construct a theory relating the gravitational wave memory strength to the energy

Nico Daheim, David Thulke, Christian Dugast, Hermann Ney

In this work, we present a model for document-grounded response generation in dialog that is decomposed into two components according to Bayes theorem. One component is a traditional ungrounded response generation model and the other component models the reconstruction of the grounding document based on the dialog context and generated response. We propose d

Maxim N. Demchenko

We consider a certain ultrahyperbolic equation in a Euclidean space being a generalization of Klein-Gordon-Fock equation. The behavior of solutions at points tending to infinity along timelike directions is studied. We examine the issue of existence of solutions possessing given asymptotic properties at infinity.

Bao Zhao, Junrui Liang

In the studies of piezoelectric energy harvesting (PEH) systems, literature has shown that circuit advancement has a significant effect on the enhancement of energy harvesting capability in resonance. On the other hand, some recent studies using the phase-variable (PV) synchronized switch technologies have found that the advanced circuit solutions can also b

Emanuele La Malfa, Matthew Wicker, Marta Kwiatkowska

Large Language Models (LLMs) have been reported to have strong performance on natural language processing tasks. However, performance metrics such as accuracy do not measure the quality of the model in terms of its ability to robustly represent complex linguistic structures. In this paper, focusing on the ability of language models to represent syntax, we pr

Chancellor Johnstone, Eugene Ndiaye

It is common in machine learning to estimate a response $y$ given covariate information $x$. However, these predictions alone do not quantify any uncertainty associated with said predictions. One way to overcome this deficiency is with conformal inference methods, which construct a set containing the unobserved response $y$ with a prescribed probability. Unf

Andrew Burgess, Edward Linscott, David D. O'Regan

A new DFT+U type corrective functional is derived from first principles to enforce the flat plane condition on localized subspaces, thus dispensing with the need for an ad hoc derivation from the Hubbard model. The newly derived functional as given by equation 5 yields relative errors below 0.6% in the total energy of the dissociated s-block dimers as well a

Yuxiang Wang, Yuyang Zhao, Xiaoliang Xu, Yue Wu

Given a graph $G$, a query node $q$, and an integer $k$, community search (CS) seeks a cohesive subgraph (measured by community models such as $k$-core or $k$-truss) from $G$ that contains $q$. It is difficult for ordinary users with less knowledge of graphs' complexity to set an appropriate $k$. Even if we define quite a large $k$, the community size return

Simone Rossetti, Damiano Zappia, Marta Sanzari, Marco Schaerf

Weakly Supervised Semantic Segmentation (WSSS) research has explored many directions to improve the typical pipeline CNN plus class activation maps (CAM) plus refinements, given the image-class label as the only supervision. Though the gap with the fully supervised methods is reduced, further abating the spread seems unlikely within this framework. On the ot

Suhyeon Lee, Kwangsoo Cho, Seungjoo Kim

A honeypot, which is a kind of deception strategy, has been widely used for at least 20 years to mitigate cyber threats. Decision-makers have believed that honeypot strategies are intuitive and effective, since honeypots have successfully protected systems from Denial-of-Service (DoS) attacks to Advanced Persistent Threats (APT) in real-world cases. Nonethel

Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta

Generalization is an important attribute of machine learning models, particularly for those that are to be deployed in a medical context, where unreliable predictions can have real world consequences. While the failure of models to generalize across datasets is typically attributed to a mismatch in the data distributions, performance gaps are often a consequ

Saleem Ayaz Khan, Ondřej Šipr, Jiří Vackář, Ján Minár

SiAlON is a prominent example of systems suitable as hosts for creating materials for light-emitting diodes (LEDs). In this work, the electronic structure of a series of semiordered and disordered SiAlON systems is investigated by means of ab initio calculations, using the FLAPW and Green function KKR methods. Finite temperature effects are included by avera

N. A. Abdulov, A. V. Kotikov, A. V. Lipatov

A new type of parametrization for parton distribution functions in a proton, based on their $Q^2$-evolution at large and small $x$ values, is constructed. In our analysis, the valence and nonsinglet parts obey the Gross-Llewellyn-Smith and Gottfried sum rules, respectively. For the singlet quark and gluon densities momentum conservation is taken into account

A. Banerjee, B. Sutradhar

In library and information science, document storage and user-specific document retrieval are the main aspects of digital library services. To preserve the cultural heritage, documents, and literature, we need a common platform where all types of documents are available in a specific format. Our proposed software tool, ADCT can handle a bulk amount of data a

Georgios Petros Katsoulis, Matthew Benjamin Peters, Agapi Emmanouilidou

We employ a recently developed three-dimensional semiclassical model to identify nondipole effects in triple ionization of Ne driven by infrared laser pulses at intensities where electron-electron correlation prevails. This model fully accounts for the Coulomb interaction of each electron with the core and avoids artificial autoionization by employing effect

Junlong Tong, Liping Xie, Wankou Yang, Kanjian Zhang

Time series forecasting is crucial for many fields, such as disaster warning, weather prediction, and energy consumption. The Transformer-based models are considered to have revolutionized the field of sequence modeling. However, the complex temporal patterns of the time series hinder the model from mining reliable temporal dependencies. Furthermore, the aut

Adar Kahana, Enrui Zhang, Somdatta Goswami, George EM Karniadakis

The discovery of fast numerical solvers prompted a clear and rapid shift towards iterative techniques in many applications, especially in computational mechanics, due to the increased necessity for solving very large linear systems. Most numerical solvers are highly dependent on the problem geometry and discretization, facing issues when any of these propert

Antoon H. Boode

Recently, we have introduced and modified two graph-decomposition theorems based on a new graph product, motivated by applications in the context of synchronising periodic real-time processes. This vertex-removing synchronised product (VRSP), is based on modifications of the well-known Cartesian product and is closely related to the synchronised product due

John Musgrave, Temesguen Messay-Kebede, David Kapp, Anca Ralescu

Latent Semantic Analysis is a method of matrix decomposition used for discovering topics and topic weights in natural language documents. This study uses Latent Semantic Analysis to analyze the composition of binaries of malicious programs. The semantic representation of the term frequency vector representation yields a set of topics, each topic being a comp

Deniz Soyuer, Benno Neuenschwander, Ravit Helled

Uranus and Neptune exhibit fast surface zonal winds that can reach up to few hundred meters per second. Previous studies on zonal gravitational harmonics and Ohmic dissipation constraints suggest that the wind speeds diminish rapidly in relatively shallow depths within the planets. Through a case-by-case comparison between the missing dynamical gravitational

Emily A. Baker, Sauro Manenti, Alessandro Reali, Giancarlo Sangalli

Groundwater flow modeling is commonly used to calculate groundwater heads, estimate groundwater flow paths and travel times, and provide insights into solute transport processes within an aquifer. However, the values of input parameters that drive groundwater flow models are often highly uncertain due to subsurface heterogeneity and geologic complexity in co

Marzieh Peyravi, Samira Nazifkar, Francisco S. N. Lobo, Kurosh Javidan

In this work, we obtain exact thick brane models in $4+1$ dimensions generated by higher order field theory kinks, inspired by specific potentials for $\phi^{10}$ and $\phi^{18}$ models. We verify that the geodesic equation along the fifth dimension confirms the confining effects of the scalar field on the brane for all of these models. These models provide

Kai Liu, Xincao Xu, Penglin Dai, Biwen Chen

Recent advances in sensing technologies, wireless communications, and computing paradigms drive the evolution of vehicles in becoming an intelligent and electronic consumer products. This paper investigates enabling digital twins in vehicular edge computing (DT-VEC) via cooperative sensing and uploading, and makes the first attempt to achieve the quality-cos

Yue Zhang, Xing Ji, Kun Xu

This paper extends the high-order compact gas-kinetic scheme (CGKS) to compressible flow simulations on a rotating coordinate frame. The kinetic equation with the inclusion of centrifugal and Coriolis acceleration is used in the construction of the scheme. With the updates of both cell averaged conservative variables and their gradients in the rotating and s

Reda Chhaibi, Ibrahim Ekren, Eunjung Noh, Lu Vy

We solve a generalized Kyle model type problem using Monge-Kantorovich duality and backward stochastic partial differential equations. First, we show that the the generalized Kyle model with dynamic information can be recast into a terminal optimization problem with distributional constraints. Therefore, the theory of optimal transport between spaces of uneq

Qiao Huang, Jean-Claude Zambrini

We are describing relations between Schr\"odinger's variational problem and Onsager's approach to nonequilibrium statistical mechanics. Although the second work on reciprocal relations and detailed balance has been published in the same year (1931) as the first one, the impact of Schr\"odinger's idea has not yet been considered in the classical context of On

Chi Hong Chow

We prove in full generality that the $T$-equivariant quantum cohomology of any flag variety $G/P$ is isomorphic to the coordinate ring of a stratum of the Peterson scheme associated to the Langlands dual group scheme $G^{\vee}$. This result was discovered by Dale Peterson but remains unpublished. Our isomorphism is constructed using Yun-Zhu's isomorphism and

Spyridon Mouselinos, Mateusz Malinowski, Henryk Michalewski

Recently, high-performing code generation systems based on large language models have surfaced. They are trained on massive corpora containing much more natural text than actual executable computer code. This work shows that current code generation systems exhibit undesired biases inherited from their large language model backbones, which can reduce the qual

Leandro Parada, Eduardo Candela, Luis Marques, Panagiotis Angeloudis

Manoeuvring in the presence of emergency vehicles is still a major issue for vehicle autonomy systems. Most studies that address this topic are based on rule-based methods, which cannot cover all possible scenarios that can take place in autonomous traffic. Multi-Agent Proximal Policy Optimisation (MAPPO) has recently emerged as a powerful method for autonom

Alex Buchel

We study stability of the Dynamical Fixed Points (DFPs) of the cascading gauge theory at strong coupling in de Sitter space-time. We compute the spectra of the perturbative fluctuations and identify stable/unstable DFPs, characterized by the ratio of the strong coupling scale $\Lambda$ of the gauge theory and the Hubble constant $H$ of the background space-t

Konstantin Osetrin, Altair Filippov, Ilya Kirnos, Evgeny Osetrin

Exact solutions for Shapovalov wave spacetimes of type I in the scalar-tensor theory of gravity of Brans-Dicke are constructed. Shapovalov's wave spacetimes describe gravitational-wave models that allow the separation of wave variables in privileged coordinate systems. In contrast to the general theory of relativity, the vacuum field equations of the Brans-D

Yanzhu Guo, Chloé Clavel, Moussa Kamal Eddine, Michalis Vazirgiannis

The topic of summarization evaluation has recently attracted a surge of attention due to the rapid development of abstractive summarization systems. However, the formulation of the task is rather ambiguous, neither the linguistic nor the natural language processing community has succeeded in giving a mutually agreed-upon definition. Due to this lack of well-

Chongnan Ye, Meng Chen, Qisheng Jiang, Chundong Wang

Persistent memory (pmem) products bring the persistence domain up to the memory level. Intel recently introduced the eADR feature that guarantees to flush data buffered in CPU cache to pmem on a power outage, thereby making the CPU cache a transient persistence domain. Researchers have explored how to enable the atomic durability for applications' in-pmem da

Dipkamal Bhusal, Rosalyn Shin, Ajay Ashok Shewale, Monish Kumar Manikya Veerabhadran

Interpretability, trustworthiness, and usability are key considerations in high-stake security applications, especially when utilizing deep learning models. While these models are known for their high accuracy, they behave as black boxes in which identifying important features and factors that led to a classification or a prediction is difficult. This can le

Jan-Willem van Ittersum, Adrien Sauvaget

We study the area Siegel-Veech constants of components of strata of abelian differentials with even or odd spin parity. We prove that these constants may be computed using either: (I) quasimodular forms, or (II) intersection theory. These results refine the main theorems of arXiv:1606.04065 and arXiv:1901.01785 which described the area Siegel-Veech constants

Tamás Solymosi

We characterize the assignment games which admit a population monotonic allocation scheme (PMAS) in terms of efficiently verifiable structural properties of the nonnegative matrix that induces the game. We prove that an assignment game is PMAS-admissible if and only if the positive elements of the underlying nonnegative matrix form orthogonal submatrices of

Victoria Lee, Kaushik Bhattacharya

Liquid crystal elastomers are rubber-like solids with liquid crystalline mesogens (stiff, rod-like molecules) incorporated either into the main chain or as a side chain of the polymer. These solids display a range of unusual thermo-mechanical properties as a result of the coupling between the entropic elasticity of rubber and the orientational phase transiti

António Girão, Shoham Letzter

We prove that there exists a constant $c > 0$ such that the vertices of every strongly $c \cdot kt$-connected tournament can be partitioned into $t$ parts, each of which induces a strongly $k$-connected tournament. This is clearly tight up to a constant factor, and it confirms a conjecture of K\"uhn, Osthus and Townsend (2016).

Souvik Bera, Tanay Pathak

The analytic continuations (ACs) of the double variable Horn $H_1$ and $H_5$ functions have been derived for the first time using the automated symbolic $\textit{Mathematica}$ package $\texttt{Olsson.wl}$. The use of Pfaff-Euler transformations have been emphasised to derive AC to cover regions which are otherwise not possible. The corresponding region of co

Andrei Kudriashov, Ian Babich, Razmik A. Hovhannisyan, Andrey G. Shishkin

Typically, topological superconductivity is reachable via proximity effect by a direct deposition of superconductor (S) on top of a topological insulator (TI) surface. Here we observed and analyzed the double critical current in the Josephson junctions based on the topological insulator in the fabricated planar Superconducting Quantum Interference Device. By

Yanick Schraner

Reinforcement learning (rl) is a popular paradigm for sequential decision making problems. The past decade's advances in rl have led to breakthroughs in many challenging domains such as video games, board games, robotics, and chip design. The sample inefficiency of deep reinforcement learning methods is a significant obstacle when applying rl to real-world p

Yuya Yamamoto, Juhan Nam, Hiroko Terasawa

In this paper, we focus on singing techniques within the scope of music information retrieval research. We investigate how singers use singing techniques using real-world recordings of famous solo singers in Japanese popular music songs (J-POP). First, we built a new dataset of singing techniques. The dataset consists of 168 commercial J-POP songs, and each

Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen

Controllable and realistic traffic simulation is critical for developing and verifying autonomous vehicles. Typical heuristic-based traffic models offer flexible control to make vehicles follow specific trajectories and traffic rules. On the other hand, data-driven approaches generate realistic and human-like behaviors, improving transfer from simulated to r

Shachar Carmeli, Bastiaan Cnossen, Maxime Ramzi, Lior Yanovski

We develop a theory of generalized characters of local systems in $\infty$-categories, which extends classical character theory for group representations and, in particular, the induced character formula. A key aspect of our approach is that we utilize the interaction between traces and their categorifications. We apply this theory to reprove and refine vari

Rubén M. Cabezón, Carlos Abia, Inma Domínguez, Domingo García-Senz

In this work, we study whether the engulfment of a brown dwarf (BD) by a solar-like main-sequence (MS) star can significantly alter the structure of the star and the Li content on its surface. We perform 3D Smoothed Particle Hydrodynamics simulations of the engulfment of a BD with masses 0.01 and 0.019 Msun, onto an MS star of 1 Msun and solar composition, i

Tie Hu, Shengqi Wang, Yunxuan Wei, Liqing Wen

Metalenses, featuring ultra-compactness and CMOS compatibility, are limited by the compromise between the diameter, numerical aperture, and working waveband. To address this problem, we propose and numerically demonstrate a centimeter-scale metasurface-refractive hybrid metalens working in the band of 440 - 700 nm. Revisiting the general Snell law, we presen

Zhuo Liu, Wang Xu

Deng-Ning-Wang-Zhou showed that a Hermitian holomorphic vector bundle is Griffiths semi-positive if it satisfies the optimal $L^2$-extension condition. As a generalization, we present a quantitative characterization of Griffiths positivity in terms of certain $L^2$-extension conditions. We also show that a $\mathbb{R}$-valued measurable function is pluriharm

Atif Khan, Conor Lawless, Amy E Vincent, Satish Pilla

Mitochondrial diseases are currently untreatable due to our limited understanding of their pathology. We study the expression of various mitochondrial proteins in skeletal myofibres (SM) in order to discover processes involved in mitochondrial pathology using Imaging Mass Cytometry (IMC). IMC produces high dimensional multichannel pseudo-images representing

Debesh Bhattacharjee, Prasad Subramanian, Teresa Nieves-Chinchilla, Angelos Vourlidas

We use in-situ data from the Wind spacecraft to survey the amplitude of turbulent fluctuations in the proton density and total magnetic field inside a large sample of near-Earth magnetic clouds (MCs) associated with coronal mass ejections (CMEs) from the Sun. We find that the most probable value of the modulation index for proton density fluctuations ($\delt

Simon Barthelmé, Nicolas Tremblay, Pierre-Olivier Amblard

Discrete Determinantal Point Processes (DPPs) have a wide array of potential applications for subsampling datasets. They are however held back in some cases by the high cost of sampling. In the worst-case scenario, the sampling cost scales as O(n^3) where n is the number of elements of the ground set. A popular workaround to this prohibitive cost is to sampl

Mohammadreza Alimohammadi, Ilia Markov, Elias Frantar, Dan Alistarh

Data-parallel distributed training of deep neural networks (DNN) has gained very widespread adoption, but can still experience communication bottlenecks. To address this issue, entire families of compression mechanisms have been developed, including quantization, sparsification, and low-rank approximation, some of which are seeing significant practical adopt

Milan Milenkovic

This paper describes the design, implementation, and user evaluation of an IoT project focused on monitoring and management of user comfort and energy usage in office buildings. The objective is to depict an instructive use case and to illustrate experiences with all major phases of designing and running a fairly complex IoT system. The design part includes

Yong Zuo, Mingyang Yue, Mingchen Zhang, Sixian Li

Low earth orbit (LEO) satellite has been considered as a potential supplement for the terrestrial Internet of Things (IoT). In this paper, we consider grant-free non-orthogonal random access (GF-NORA) in orthogonal frequency division multiplexing (OFDM) system to increase access capacity and reduce access latency for LEO satellite-IoT. We focus on the joint

Haris Shahzad, Stefan Hickel, Davide Modesti

We present pore-resolved direction numerical simulations (DNS) of turbulent flows grazing over perforated plates, that closely resemble the acoustic liners found on aircraft engines. Our DNS explore a large parameter space including the effects of porosity, thickness, and viscous-scaled diameter of the perforated plates, at friction Reynolds numbers $Re_\tau

Nauman Ahad, Mark A. Davenport, Yao Xie

Detecting change points sequentially in a streaming setting, especially when both the mean and the variance of the signal can change, is often a challenging task. A key difficulty in this context often involves setting an appropriate detection threshold, which for many standard change statistics may need to be tuned depending on the pre-change and post-chang

Ruizhi Huang

We show that except two special cases, the sphere bundle of a vector bundle over a simply connected $4$-manifold splits after looping. In particular, this implies that though there are infinitely many inequivalent sphere bundles of a given rank over a $4$-manifold, the loop spaces of their total manifolds are all homotopy equivalent.

Michael J. Wilensky, Fraser Kennedy, Philip Bull, Joshua S. Dillon

We present a Bayesian jackknife test for assessing the probability that a data set contains biased subsets, and, if so, which of the subsets are likely to be biased. The test can be used to assess the presence and likely source of statistical tension between different measurements of the same quantities in an automated manner. Under certain broadly applicabl

Peter Gibson, Nicolau Saldanha, Carlos Tomei

We present higher dimensional versions of the classical results of Euler and Fuss, both of which are special cases of the celebrated Poncelet porism. Our results concern polytopes, specifically simplices, parallelotopes and cross polytopes, inscribed in a given ellipsoid and circumscribed to another. The statements and proofs use the language of linear algeb

Kun Song, Jian Cong, Xinsheng Wang, Yongmao Zhang

In current two-stage neural text-to-speech (TTS) paradigm, it is ideal to have a universal neural vocoder, once trained, which is robust to imperfect mel-spectrogram predicted from the acoustic model. To this end, we propose Robust MelGAN vocoder by solving the original multi-band MelGAN's metallic sound problem and increasing its generalization ability. Spe

P. B. Changala, H. Gupta, J. Cernicharo, J. R. Pardo

We report the detection of magnesium dicarbide, MgC$_2$, in the laboratory at centimeter wavelengths and assign $^{24}$MgC$_2$, $^{25}$MgC$_2$, and $^{26}$MgC$_2$ to 14 unidentified lines in the radio spectrum of the circumstellar envelope of the evolved carbon star IRC+10216. The structure of MgC$_2$ is found to be T-shaped with a highly ionic bond between

Maarten J. van den Broek, Daniel van den Berg, Benjamin Sanderse, Jan-Willem van Wingerden

Dynamic induction control is a wind farm flow control strategy that utilises wind turbine thrust variations to accelerate breakdown of the aerodynamic wake and improve downstream turbine performance. However, when floating wind turbines are considered, additional dynamics and challenges appear that make optimal control difficult. In this work, we propose an

Selin Aviyente, Alejandro Frangi, Erik Meijering, Arrate Muñoz-Barrutia

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological imaging, digital pathology, molecular imaging, microscopy, and associated computational imaging, image

Nora Brambilla, Hee Sok Chung, Antonio Vairo, Xiang-Peng Wang

Under some assumptions on the hierarchy of relevant energy scales, we compute the nonrelativistic QCD (NRQCD) long-distance matrix elements (LDMEs) for inclusive production of $J/\psi$, $\psi(2S)$, and $\Upsilon$ states based on the potential NRQCD (pNRQCD) effective field theory. Based on the pNRQCD formalism, we obtain expressions for the LDMEs in terms of

Mallikarjun BR, Ayush Tewari, Xingang Pan, Mohamed Elgharib

3D generative models of objects enable photorealistic image synthesis with 3D control. Existing methods model the scene as a global scene representation, ignoring the compositional aspect of the scene. Compositional reasoning can enable a wide variety of editing applications, in addition to enabling generalizable 3D reasoning. In this paper, we present a com

Abdesamed Benbedra, Said Meskine, Abdelkader Boukortt, Roland Hayn

The spontaneous polarization of wurtzite III-V nitrides XN (X=Al, Ga, In) and II-VI oxides YO (Y=Be, Zn) is investigated via first-principles computational methods. The modern treatment defines this quantity as the polarization difference between the investigated system and an appropriate reference state. We demonstrate that the trigonal structure can be use

Grigory Sokolov, Valentin S. Spivak, Alexander G. Tartakovsky

Oftentimes in practice, the observed process changes statistical properties at an unknown point in time and the duration of a change is substantially finite, in which case one says that the change is intermittent or transient. We provide an overview of existing approaches for intermittent change detection and advocate in favor of a particular setting driven

Lukas Fehring, Jonas Hanselle, Alexander Tornede

It is well known that different algorithms perform differently well on an instance of an algorithmic problem, motivating algorithm selection (AS): Given an instance of an algorithmic problem, which is the most suitable algorithm to solve it? As such, the AS problem has received considerable attention resulting in various approaches - many of which either sol

Vineeth Venugopal, Sumit Pai, Elsa Olivetti

This paper introduces MatKG, a novel graph database of key concepts in material science spanning the traditional material-structure-property-processing paradigm. MatKG is autonomously generated through transformer-based, large language models and generates pseudo ontological schema through statistical co-occurrence mapping. At present, MatKG contains over 2

Junyuan Wu, Xincao Xu, Chuzhao Li, Hao Zhang

With the development of sensing technologies, vehicle-to-everything (V2X) communications, edge computing paradigm, vehicular cyber-physical systems (VCPS) are emerging as the most fundamental platform for realizing future intelligent transportation systems (ITSs). In particular, the construction of logical views at the edge nodes based on heterogeneous infor

Akira Shinkyu

We propose a new testing procedure of heteroskedasticity in high-dimensional linear regression, where the number of covariates can be larger than the sample size. Our testing procedure is based on residuals of the Lasso. We demonstrate that our test statistic has asymptotic normality under the null hypothesis of homoskedasticity. Simulation results show that

Ünal Ege Gaznepoglu, Anna Leschanowsky, Nils Peters

We introduce a novel method to improve the performance of the VoicePrivacy Challenge 2022 baseline B1 variants. Among the known deficiencies of x-vector-based anonymization systems is the insufficient disentangling of the input features. In particular, the fundamental frequency (F0) trajectories, which are used for voice synthesis without any modifications.

Sourjya Banerjee

Let $A$ be a commutative Noetherian ring of characteristic $p>0$, such that $\dim(A)=d$. Let $P$ be a projective $A[T_1,...,T_n]$-module of rank $d$. We show that $P$ is cancellative if and only if $P/<T_1,...,T_n>P$ is cancellative. We deduce some applications. In one of the interesting consequences, we show that the Bass-Quillen conjecture has an affirmati

Xiaolong Zhang, Maurizio Carbone, Andrew D. Bragg

The equation for the fluid velocity gradient along a Lagrangian trajectory immediately follows from the Navier-Stokes equation. However, such an equation involves two terms that cannot be determined from the velocity gradient along the chosen Lagrangian path: the pressure Hessian and the viscous Laplacian. A recent model handles these unclosed terms using a

Hala Shamseddine, Safa Otoum, Azzam Mourad

Autism Spectrum Disorder (ASD) is a neuro-developmental syndrome resulting from alterations in the embryological brain before birth. This disorder distinguishes its patients by special socially restricted and repetitive behavior in addition to specific behavioral traits. Hence, this would possibly deteriorate their social behavior among other individuals, as

Hannes Saffrich, Peter Thiemann

Session types provide a principled approach to typed communication protocols that guarantee type safety and protocol fidelity. Formalizations of session-typed communication are typically based on process calculi, concurrent lambda calculi, or linear logic. An alternative model based on context-sensitive typing and typestate has not received much attention du

Malte Brinch, Thomas R. Greve, John R. Weaver, Gabriel Brammer

We conduct a systematic search for protocluster candidates at $z \geq 6$ in the COSMOS field using the recently released COSMOS2020 source catalog. We select galaxies using a number of selection criteria to obtain a sample of galaxies that have a high probability of being inside a given redshift bin. We then apply overdensity analysis to the bins using two d

Yong Cheng

Effectively inseparable pairs and their properties play an important role in the meta-mathematics of arithmetic and incompleteness. Different notions are introduced and shown in the literature to be equivalent to effective inseparability. We give a much simpler proof of these equivalences using the strong double recursion theorem. Then we prove some results

Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano, Mattia Panettiere

Categorization of business processes is an important part of auditing. Large amounts of transnational data in auditing can be represented as transactions between financial accounts using weighted bipartite graphs. We view such bipartite graphs as many-valued formal contexts, which we use to obtain explainable categorization of these business processes in ter

Harri Hakula, Helmut Harbrecht, Vesa Kaarnioja, Frances Y. Kuo

We consider uncertainty quantification for the Poisson problem subject to domain uncertainty. For the stochastic parameterization of the random domain, we use the model recently introduced by Kaarnioja, Kuo, and Sloan (SIAM J. Numer. Anal., 2020) in which a countably infinite number of independent random variables enter the random field as periodic functions

Nicolas Peschken, Michał Hanasz, Thorsten Naab, Dominik Wóltański

Feeding with gas in streams is predicted to be an important galaxy growth mechanism. Using an idealised setup, we study the impact of stream feeding (with 10$^7$ M$_{\odot}$ Myr$^{-1}$ rate) on the star formation and outflows of disc galaxies with $\sim$10$^{11}$ M$_{\odot}$ baryonic mass. The magneto-hydrodynamical simulations are carried out with the PIERN

Robin Scheibler, Youna Ji, Soo-Whan Chung, Jaeuk Byun

We propose DiffSep, a new single channel source separation method based on score-matching of a stochastic differential equation (SDE). We craft a tailored continuous time diffusion-mixing process starting from the separated sources and converging to a Gaussian distribution centered on their mixture. This formulation lets us apply the machinery of score-based

Jingyu Li, Wei Liu, Zhaoyang Zhang, Jiong Wang

DNN-based speaker verification (SV) models demonstrate significant performance at relatively high computation costs. Model compression can be applied to reduce the model size for lower resource consumption. The present study exploits weight quantization to compress two widely-used SV models, namely ECAPA-TDNN and ResNet. Experimental results on VoxCeleb show

Iain Haughton, Edgar Sucar, Andre Mouton, Edward Johns

Neural fields can be trained from scratch to represent the shape and appearance of 3D scenes efficiently. It has also been shown that they can densely map correlated properties such as semantics, via sparse interactions from a human labeller. In this work, we show that a robot can densely annotate a scene with arbitrary discrete or continuous physical proper

Dan Xie

This paper gives a classification of rank one 5d $\mathcal{N}=1$ and 6d $(1,0)$ SCFTs. The idea is to compactify 5d theory on $S^1$ and 6d theory on $T^2$ to get effective 4d $\mathcal{N}=2$ theory. These compactified theories all have a 4d $\mathcal{N}=2$ Coulomb branch whose solution can be described by mixed Hodge module (MHM). In the rank one case every

Elias Frantar, Saleh Ashkboos, Torsten Hoefler, Dan Alistarh

Generative Pre-trained Transformer models, known as GPT or OPT, set themselves apart through breakthrough performance across complex language modelling tasks, but also by their extremely high computational and storage costs. Specifically, due to their massive size, even inference for large, highly-accurate GPT models may require multiple performant GPUs, whi

Shipeng Yan, Lanqing Hong, Hang Xu, Jianhua Han

Vision-language pre-training (VLP) has attracted increasing attention recently. With a large amount of image-text pairs, VLP models trained with contrastive loss have achieved impressive performance in various tasks, especially the zero-shot generalization on downstream datasets. In practical applications, however, massive data are usually collected in a str

Aritra Banik, Prahlad Narasimhan Kasthurirangan, Venkatesh Raman

In this paper, we study two popular variants of Graph Coloring -- Dominator Coloring and CD Coloring. In both problems, we are given a graph $G$ and a natural number $\ell$ as input and the goal is to properly color the vertices with at most $\ell$ colors with specific constraints. In Dominator Coloring, we require for each $v \in V(G)$, a color $c$ such tha