A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
FineFool attacks deep models by focusing on object contours, improving attack performance.
We develop mask iterative hard thresholding algorithms (mask IHT and mask DORE) for sparse image reconstruction of objects with known contour. The measurements follow a noisy underdetermined linear model common in the compressive sampling literature. Assuming that the contour of the object that we wish to reconstruct i…
Metrics stabilize persistent homology in data analysis.
Describing shapes by suitable measures in object segmentation, as proposed in [24], allows to combine the advantages of the representations as parametrized contours and indicator functions. The pseudo-Riemannian structure of optimal transport can be used to model shapes in ways similar as with contours, while the Kanto…
A new method for analyzing shapes using FDA techniques.
Combines geometric and topological info for complex object boundaries.
Study of curves and surfaces from single-direction projections.
Defines surfaces with specific contour patterns.
We introduce an algorithm to locate contours of functions that are expensive to evaluate. The problem of locating contours arises in many applications, including classification, constrained optimization, and performance analysis of mechanical and dynamical systems (reliability, probability of failure, stability, etc.).…
A contour integral method recently proposed by Weideman [IMA J. Numer. Anal., to appear] for integrating semi-discrete advection-diffusion PDEs, is extended for application to some of the important equations of mathematical finance. Using estimates for the numerical range of the spatial operator, optimal contour parame…
New method improves combinatorial optimization by overcoming inefficient sampling.
Investigate the local geometry of smooth surfaces in 4-space via contact with 2-planes and apparent contours.
In this paper we consider planar sections and visual contours of co-dimension one affine immersions. The main theorem says that the third order Taylor expansion of the difference between the visual contour and planar section functions is exactly the cubic form. We also consider parameterizations on two dimensional affi…
Paper proposes a new Wasserstein distance for mixtures of radially contoured distributions.
The paper studies curves in surfaces using flow-spines and apparent contours.
Deep convolutional neural networks have become a key element in the recent breakthrough of salient object detection. However, existing CNN-based methods are based on either patch-wise (region-wise) training and inference or fully convolutional networks. Methods in the former category are generally time-consuming due to…
The fundamental frequency (F0) contour of speech is a key aspect to represent speech prosody that finds use in speech and spoken language analysis such as voice conversion and speech synthesis as well as speaker and language identification. This work proposes new methods to estimate the F0 contour of speech using deep …
IrisNet tracks tongue contours in ultrasound videos using deep learning.
PFs and iPFs learn principal manifolds for efficient density estimation.
The contour map of estimation error of Expected Shortfall (ES) is constructed. It allows one to quantitatively determine the sample size (the length of the time series) required by the optimization under ES of large institutional portfolios for a given size of the portfolio, at a given confidence level and a given esti…
ICSGLD improves efficiency in posterior sampling for big data.
We present a new implementation of anisotropic mean curvature flow for contour recognition. Our procedure couples the mean curvature flow of planar closed smooth curves, with an external field from a potential of point-wise charges. This coupling constrains the motion when the curve matches a picture placed as backgrou…
The paper finds surfaces closest to being flat that span a given contour.
New method uses contours of segmented images for X-ray classification.
Completeness of the eigenfunctions of a quantum mechanical system is crucial for its probability interpretation. By using the method of contour integral we give properly normalized eigenfunctions for both discrete and continuum spectrum of the Morse potential, and explicitly prove the completeness relation. As an appli…
Proposes a new network to improve nuclei segmentation in histopathology images.
Improved image learning using elliptically contoured tensor-variate distributions.
In this paper we present a new method for motion tracking of tumors in liver ultrasound image sequences. Our algorithm has two main steps. In the first step, we apply mean shift algorithm with multiple features to estimate the center of the target in each frame. Target in the first frame is defined using an ellipse. Ed…
Optimizes learning Hilbert-Schmidt operators between Sobolev spaces.
New methods improve accuracy in predicting complex systems.
Study electric field and potential of torus knots, focusing on z-axis.
The paper explores three methods to assign a metric to shape spaces.
The contour maps of the error of historical resp. parametric estimates for large random portfolios optimized under the risk measure Expected Shortfall (ES) are constructed. Similar maps for the sensitivity of the portfolio weights to small changes in the returns as well as the VaR of the ES-optimized portfolio are also…
Study on Gaussian random fields' singularities on manifolds.
The paper tightens bounds on distances between Reeb graphs.
Bayesian optimization (BO) is a global optimization strategy designed to find the minimum of an expensive black-box function, typically defined on a compact subset of , by using a Gaussian process (GP) as a surrogate model for the objective. Although currently available acquisition functions address this…
We present an approach for polarimetric Synthetic Aperture Radar (SAR) image region boundary detection based on the use of B-Spline active contours and a new model for polarimetric SAR data: the GHP distribution. In order to detect the boundary of a region, initial B-Spline curves are specified, either automatically or…
Study improves tongue contour recognition in ultrasound images using transfer learning.
It is proposed a new code for contours of plane images. This code was applied for optical character recognition of printed and handwritten characters. One can apply it to recognition of any visual images.
Wilson loops in supersymmetric Yang-Mills theory correspond at strong coupling to extremal surfaces in . We study a class of extremal surfaces known as special Legendrian submanifolds. The "hemisphere" corresponding to the circular Wilson loop is an example of a special Legendrian submanifold, and w…
We consider a complex Plateau problem for strongly pseudoconvex contours in non Kähler manifolds. A positive solution in the case of manifolds carrying a pluriclosed Hermitian metric forms is given. For the general case we propose a conjecture.
Wavelet features improve image clustering and segmentation accuracy.
A new algorithm efficiently partitions images without seeds or thresholds.
We determine the precise bifurcation diagrams of the apparent contours of generic crosscaps, which contain the information of bifurcations with respect to the images of the singular sets of crosscaps: crosscap points and double point curves. Especially, three different kinds of equivalences play key roles.
New formulas for surface curvature when tangent vector points in asymptotic directions.
A new algorithm flattens multi-modal distributions for better deep learning.
Method learns symmetries in curves without augmentation.
Entropy-based GP adaptive design improves failure probability estimation.