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Gaussian processes with multidimensional distribution inputs via optimal transport and Hilbertian embedding
Electronic journal of statistics. 2020. Vol. 14. No. 2. P. 2742–2772.
In this work, we propose a way to construct Gaussian processes indexed by multidimensional distributions. More precisely, we tackle the problem of defining positive definite kernels between multivariate distributions via notions of optimal transport and appealing to Hilbert space embeddings. Besides presenting a characterization of radial positive definite and strictly positive definite kernels on general Hilbert spaces, we investigate the statistical properties of our theoretical and empirical kernels, focusing in particular on consistency as well as the special case of Gaussian distributions. A wide set of applications is presented, both using simulations and implementation with real data.
Alshanskaia E., Portnova G., Liaukovich K. et al., Frontiers in Neuroscience 2024 Vol. 18
Added: September 7, 2026
Зуенко Д. О., Trofimova E., Хайдарова И., IEEE Access 2026 Vol. 14 P. 121339–121357
Oil spill segmentation in Synthetic Aperture Radar (SAR) images is limited by noisy annotations in publicly available datasets and by architectural choices that interact with label quality in opposing directions. First, we introduce a manually refined version of the Deep-SAR Oil Spill (SOS) dataset, in which 36.25% of masks are corrected for false positives, missed ...
Added: September 7, 2026
Kucheryavyy P., Математические заметки 2026 Т. 2026 № 120 С. 380–401
В работе изучаются перестановки, возникающие при упорядочивании по возрастанию дробных долей произведений элементов фиксированной целочисленной последовательности на вещественный параметр. Исследуется количество различных перестановок, которые можно получить таким образом при изменении этого параметра от нуля до единицы. ...
Added: September 7, 2026
Неверов В. Д., Красавин А. В., Vagov A. et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 113 P. 1–6
We develop a neural network approach to solve the self-consistent Bogoliubov-de Gennes equations in strongly disordered s-wave superconductors. The method accurately reproduces inhomogeneous gap distributions and generalizes to system sizes far larger than those used in training. It reduces computational scaling from O(N6 ) to O(N2), enabling quantitative analysis of percolation phenomena and the superconductor-insulator ...
Added: September 5, 2026
Sheshukova M., Durmus A., Khusainov M. et al., Statistics 2026 P. 1–25
In this paper, we consider the problem of Gaussian approximation for the online linear regression task. We derive the corresponding rates for the setting of a constant stepsize and study the explicit dependence of the convergence rate on the problem dimension d and quantities related to the design matrix. When the number of iterations n is known in advance, ...
Added: September 4, 2026
Proceedings of Machine Learning Research , 2026.
Added: September 4, 2026
Осипов Д.В., Математический сборник 2026 Т. 217 № 9 С. 130–146
Изучаются законы взаимности, связанные с комплексными линейными расслоениями на расслоениях на ориентируемые окружности. В частности, доказывается следующий закон взаимности. Пусть B – комплексное многообразие и πi:Mi→B – расслоение на ориентируемые окружности, где индекс i пробегает конечное множество. Пусть Li и Ni – комплексные линейные расслоения на каждом многообразии Mi. Закон взаимности утверждает, что сумма всех элементов (πi)∗(c1(Li)∪c1(Ni)), где (πi)∗ – ...
Added: September 3, 2026
Khodadoust J., Kulikova S., Khodadoust F., Biomedical Signal Processing and Control 2027 Vol. 129 P. 111284–111284
Acute ischemic stroke (AIS) analysis from two-dimensional (2D) clinical imaging is hindered by uncontrolled slice tilt and geometric inconsistencies that violate the assumptions of pose-agnostic deep learning (DL) models. This paper proposes a unified geometry-aware, frequency-domain framework for tilted slice localization and ischemic stroke segmentation that explicitly decouples pose estimation from lesion analysis. The method ...
Added: September 2, 2026
IEEE, 2026.
On behalf of the Organizing Committee, it is my great pleasure to extend a warm
welcome to all participants of the Fourth International IEEE Conference on
Distributed Computing and High-Performance Computing (DCHPC 2026), held
in Tehran from May 10–11, 2026. This conference is jointly organized by the
School of Computer Science at the Institute for Research in Fundamental
Sciences (IPM) ...
Added: September 2, 2026
Basalaev A., Rarovskii A., Journal of Singularities 2026 Vol. 30 P. 61–80
Saito theory associates to an isolated singularity rich structure that plays an important role in mirror symmetry. In this note we construct Saito theory for A and D type Landau-Ginzburg orbifolds. Namely, for the pairs (f,G), where f defines an isolated singularity of A and D type and G is a group of symmetries of ...
Added: September 1, 2026
Rybakov M., Shkatov D., Journal of Logic and Computation 2026 Vol. 36 No. 6 Article exag026
We prove Pi-1-1-hardness, and thus lack of recursive axiomatizability, of constant-domain modal predicate logics defined by a class of Dedekind complete linear Kripke frames containing a frame with an infinitely increasing chain of worlds. The result holds even for the language with one unary predicate letter, one propositional letter, and two individual variables. ...
Added: September 1, 2026
Селянин Ф. И., Moscow Mathematical Journal 2026 Vol. 26 No. 2 P. 167–187
Minkowski mixed volume of n subpolytopes D1,…,Dn of a polytope P⊂Rn clearly does not exceed the normalized volume n!Vol(P). Equality holds if and only if the subpolytopes are interlaced, i.e., each proper face F⊊P intersects at least dim(F)+1 of the polytopes Di. Efficiently computing mixed volumes for more general collections of subpolytopes is crucial for estimating the complexity of numerically solving polynomial systems.
Motivated by relaxing the bound dim(F)+1 to dim(F), we ...
Added: August 31, 2026
Kazaryan M., Dunin-Barkowski P., Bychkov B. et al., International Mathematics Research Notices 2026 Vol. 14 Article rnag146
We prove a recent conjecture of the fourth named author with P. Norbury that states a system of universal polynomial relations among the kappa classes on the moduli spaces of algebraic curves. The proof involves localization and materialization analysis of the spin Gromov–Witten theory of the projective line and is dictated by Z 2 -equivariant ...
Added: August 31, 2026
Ramazyan T., Hushchyn M., Derkach D., , in: ECAI 2024. 27th European Conference on Artificial Intelligence, October 19 – 24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024).: IOS Press, 2024. P. 2394–2401.
We propose a new uncertainty estimator for gradient-free optimisation of black-box simulators using deep generative surrogate models. Optimisation of these simulators is especially challenging for stochastic simulators and higher dimensions. To address these issues, we utilise a deep generative surrogate approach to model the black box response for the entire parameter space. We then leverage ...
Added: December 1, 2024
Kurochkin S. V., Rodina V., Экономический журнал Высшей школы экономики 2024 Т. 28 № 3 С. 412–426
One of the key techniques in the fixed-income portfolio management is immunization which involves a managed change in the portfolio value under interest rate fluctuations given a similar pattern in a portfolio of liabilities. Since the classic work by Redington, scholars have developed a variety of immunization models. Yet, these models are built on restrictive ...
Added: October 17, 2024
Erlygin L., Zholobov V., Baklanova V. et al., , in: 2023 IEEE International Conference on Data Mining Workshops (ICDMW) 1–4 December 2023, Shanghai, China.: Shanghai: IEEE Computer Society, 2023. P. 1247–1258.
Machine learning models play a vital role in time series forecasting. These models, however, often overlook an important element: point uncertainty estimates. Incorporating these estimates is crucial for effective risk management, informed model selection, and decision-making.To address this issue, our research introduces a method for uncertainty estimation. We employ a surrogate Gaussian process regression model. ...
Added: March 20, 2024
Kelbert M., Сухов Ю. М., Известия Саратовского университета. Новая серия. Серия: Математика. Механика. Информатика 2023 Vol. 23 No. 4 P. 422–434
We present a number of low and upper bounds for L\эevy – ´Prokhorov, Wasserstein, Frechet, and Hellinger distances between ´ probability distributions of the same or different dimensions. The weighted (or context-sensitive) total variance and Hellinger distances are introduced. The upper and low bounds for these weighted metrics are proved. The low bounds for the ...
Added: October 29, 2023
Kelbert M., Analytics 2023 Vol. 2 No. 1 P. 225–245
We present a number of upper and lower bounds for the total variation distances between
the most popular probability distributions. In particular, some estimates of the total variation
distances in the cases of multivariate Gaussian distributions, Poisson distributions, binomial distributions,
between a binomial and a Poisson distribution, and also in the case of negative binomial
distributions are given. Next, ...
Added: March 1, 2023
Chigarev V., Kazakov A., Пиковский А., Chaos 2020 Vol. 30 No. 7 Article 073114
We consider several examples of dynamical systems demonstrating overlapping attractor and repeller. These systems are constructed via introducing controllable dissipation to prototypic models with chaotic dynamics (Anosov cat map, Chirikov standard map, and incompressible three-dimensional flow of the ABC-type on a three-torus) and ergodic non-chaotic behavior (skew-shift map). We employ the Kantorovich–Rubinstein–Wasserstein distance to characterize the ...
Added: October 31, 2020
A. I. Zhdanov, V. I. Piterbarg, Theory Probability and its Applications 2018 Vol. 63 No. 1 P. 1–21
Let $\mathbf{\boldsymbol{\xi}}(t)=(\xi_{1}(t),\ldots,\xi_{d}(t))$ be a Gaussian zero mean stationary a.s. continuous vector process. Let $g\colon{\mathbb{R}}^{d}\to {\mathbb{R}}$ be a homogeneous function of positive degree. We study probabilities of high extrema of the Gaussian chaos process $g(\mathbf{\boldsymbol{\xi}}(t))$. Important examples are products of Gaussian processes, $\prod_{i=1}^{d}\xi_{i}(t)$, and quadratic forms $\sum_{i,j=1}^{d}a_{ij}\xi_{i}(t)\xi_{j}(t)$. Methods of our studies include the Laplace saddle point ...
Added: November 14, 2019
A. I. Zhdanov., Theory Probability and its Applications 2015 Vol. 60 No. 3 P. 520–527
Let $(X(t),Y(t))$, $t\ge0$, be a zero-mean stationary Gaussian vector process with a covariance functions for components $r_i(t)$ satisfying Pickand's condition $r_i(t)=1-c_i|t|^{\alpha_i}(1+o(1))$, $t\to 0$, $c_i>0$, $0<\alpha_i\le2$, $i=1,2.$ Let $r_i(t)<1$, $i=1,2$, $t>0.$ Assuming that $r\equiv {\bf E}\,X(t)Y(t)\in(-1,1)$ and $\lim_{t,s\rightarrow0}({\bf E}\,X(t)Y(s)-r)/|t-s|^{\min(\alpha_1,\alpha_2)}$ exists, we study the behavior of probability ${\bf P}(\max_{t\in\lbrack0,p]}X(t)Y(t)>u)$ as $u\rightarrow\infty$ for any $p$. In particular, we ...
Added: November 14, 2019
Zhdanov A., Piterbarg V.I., Extremes 2015 Vol. 18 No. 1 P. 99–108
Let X(t), Y(t), t ≥ 0, be two independent zero-mean stationary Gaussian
processes, whose covariance functions are such that ri (t) = 1 − |t|^{a_{i}} + o(|t|^{a_{i}})
as t → 0, with 0 < a_{i} ≤ 2, i = 1, 2 and both of the functions are less than one
for non-zero t . We derive for any p ...
Added: November 14, 2019
Pusev R., Назаров А. И., Записки научных семинаров ПОМИ РАН 2009 Т. 364 С. 166–199
We find the exact small ball asymptotics under weighted L_2-norm for a wide class of Gaussian processes which generate boundary-value problems for ordinary differential equations. Sharp constants in the asymptotics are derived for a number of processes connected with special functions. ...
Added: January 28, 2019
Galliani P., Dezfouli A., Bonilla E. et al., , in: Proceedings of Machine Learning Research. 2017. Volume 54: Artificial Intelligence and StatisticsVol. 54: Artificial Intelligence and Statistics.: [б.и.], 2017. P. 353–361.
We develop an automated variational inference method for Bayesian structured prediction problems with Gaussian process (GP) priors and linear-chain likelihoods. Our approach does not need to know the details of the structured likelihood model and can scale up to a large number of observations. Furthermore, we show that the required expected likelihood term and its ...
Added: December 10, 2018