Paper explores using EEG for better speaker identification, even in noisy environments.
arXiv research
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Method identifies causal drivers from background features.
PCA++ improves robustness to background noise in contrastive learning.
Enhances machine learning with background knowledge through feature generation.
New algorithm improves interpretability in sequence classification.
We introduce the technique combining the features of integration schemes for SDYM equations and multidimensional dispersionless integrable equations to get SDYM equations on the conformally self-dual background. Generating differential form is defined, the dressing scheme is developed. Some special cases and reductions…
Automatically detecting sound units of humpback whales in complex time-varying background noises is a current challenge for scientists. In this paper, we explore the applicability of Convolution Neural Network (CNN) method for this task. In the evaluation stage, we present 6 bi-class classification experimentations of …
Proposes FSM-IRL to learn invariant network representations considering feature and structural shifts.
We consider the first order formalism in string theory, providing a new off-shell description of the nontrivial backgrounds around an "infinite metric". The OPE of the vertex operators, corresponding to the background fields in some "twistor representation", and conditions of conformal invariance results in the quadrat…
Given the lack of evidence for new particle discoveries at the Large Hadron Collider (LHC), it is critical to broaden the search program. A variety of model-independent searches have been proposed, adding sensitivity to unexpected signals. There are generally two types of such searches: those that rely heavily on simul…
TPM improves medical image segmentation by separating foreground and background.
ICAM creates interpretable feature attribution maps for brain images.
Last layer retraining improves robustness to spurious correlations without high computational costs.
Investment and insurance decisions are studied in a model with nonlinear portfolio frictions and background risk.
String backgrounds yield simplified Hull-Strominger system solutions.
Variational autoencoders are powerful algorithms for identifying dominant latent structure in a single dataset. In many applications, however, we are interested in modeling latent structure and variation that are enriched in a target dataset compared to some background---e.g. enriched in patients compared to the genera…
The paper analyzes Teukolsky equations on Kerr backgrounds, proving boundedness and decay of solutions.
We consider bosonic supersymmetric backgrounds of ten-dimensional conformal supergravity. Up to local conformal isometry, we classify the maximally supersymmetric backgrounds, determine their conformal symmetry superalgebras and show how they arise as near-horizon geometries of certain half-BPS backgrounds or as a plan…
Principal component analysis (PCA) is widely used for feature extraction and dimensionality reduction, with documented merits in diverse tasks involving high-dimensional data. Standard PCA copes with one dataset at a time, but it is challenged when it comes to analyzing multiple datasets jointly. In certain data scienc…
This work examines a semi-blind single-channel source separation problem. Our specific aim is to separate one source whose local structure is approximately known, from another a priori unspecified background source, given only a single linear combination of the two sources. We propose a separation technique based on lo…
Electron Cryo-Tomography (ECT) allows 3D visualization of subcellular structures at the submolecular resolution in close to the native state. However, due to the high degree of structural complexity and imaging limits, the automatic segmentation of cellular components from ECT images is very difficult. To complement an…
Derives path-integrals for superstrings on curved backgrounds using string geometry theory.
Derives path integrals for perturbative strings on various backgrounds.
In this paper, we present a technique for unsupervised learning of visual representations. Specifically, we train a model for foreground and background classification task, in the process of which it learns visual representations. Foreground and background patches for training come af- ter mining for such patches from …
We describe the construction of a Lie superalgebra associated to an arbitrary supersymmetric M-theory background, and discuss some examples. We prove that for backgrounds with more than 24 supercharges, the bosonic subalgebra acts locally transitively. In particular, we prove that backgrounds with more than 24 supersym…
SepVAE separates patient-specific patterns from healthy ones using contrastive VAE.
New framework uses background knowledge to speed up causal discovery.
Applications of machine learning tools to problems of physical interest are often criticized for producing sensitivity at the expense of transparency. To address this concern, we explore a data planing procedure for identifying combinations of variables -- aided by physical intuition -- that can discriminate signal fro…
SRTC model for background/foreground separation with missing pixels.
Paper proposes a novel RRL framework that learns from images and incorporates expert knowledge.
Study optimal reinsurance for insurers with a reinsurer's default risk.
We extend the Falceto-Zambon version of Marsden-Ratiu Poisson reduction to Poisson quasi-Nijenhuis structures with background on manifolds. We define gauge transformations of Poisson quasi-Nijenhuis structures with background, study some of their properties and show that they are compatible with reduction procedure. We…
Motivated by the search for new gravity duals to M2 branes with supersymmetry --- equivalently, M-theory backgrounds with Killing superalgebra for --- we classify homogeneous M-theory backgrounds with symmetry Lie algebra for . We f…
We explore all warped backgrounds with the most general allowed fluxes that preserve more than 16 supersymmetries in - and -dimensional supergravities. After imposing the assumption that either the internal space is compact without boundary or the isometry algebra of the back…
Generative Adversarial Networks generate PXD background noise efficiently.
We prove that supersymmetry backgrounds of (1,0) and (2,0) six-dimensional supergravity theories preserving more than one half of the supersymmetry are locally homogeneous. As a byproduct we also establish that the Killing spinors of such a background generate a Lie superalgebra.
This note focuses on some properties and uses of filtered deformations in the context of D=11 supergravity. We define the concept of abstract symbol and give a strong version of the Reconstruction Theorem, namely a bijective correspondence from the space of highly supersymmetric supergravity backgrounds to the space of…
The paper examines how background risk affects portfolio selection and optimal reinsurance design.
In this paper we study homogeneous backgrounds of type IIB supergravity where the underlying geometry is that of a symmetric space. We determine which ten-dimensional lorentzian symmetric spaces (up to local isometry) admit such backgrounds and in about two thirds of the cases we determine fully their moduli space.
The task of determining a speaker's native language based only on his speeches in a second language is known as Native Language Identification or NLI. Due to its increasing applications in various domains of speech signal processing, this has emerged as an important research area in recent times. In this paper we have …
Defines Killing spinors and bosonic backgrounds in 5D supergravity.
Lecture notes on kernel functions and Random Fourier Features.
We present two different families of eleven-dimensional manifolds that admit non-restricted extensions of the isometry algebras to geometric superalgebras. Both families admit points for which the superalgebra extends to a super Lie algebra; on the one hand, a family of , supergravity backgrounds a…
New method simplifies causal inference with tiered background knowledge.
Study evaluates saliency maps on artificial data with different backgrounds.
Researchers prove a nonlinear gluing theorem for gravitational fields near static backgrounds.
We construct rigid supersymmetric gauge theories on Riemannian five-manifolds. We follow a holographic approach, realizing the manifold as the conformal boundary of a six-dimensional bulk supergravity solution. This leads to a systematic classification of five-dimensional supersymmetric backgrounds with gravity duals. …
We define the Poisson quasi-Nijenhuis structures with background on Lie algebroids and we prove that to any generalized complex structure on a Courant algebroid which is the double of a Lie algebroid is associated such a structure. We prove that any Lie algebroid with a Poisson quasi-Nijenhuis structure with background…