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Hardy and Littlewood's approximate functional equation for quadratic Weyl sums (theta sums) provides, by iterative application, a powerful tool for the asymptotic analysis of such sums. The classical Jacobi theta function, on the other…

Number Theory · Mathematics 2015-02-27 Francesco Cellarosi , Jens Marklof

We study existence and regularity of weak solutions to a nonlinear parabolic Dirichlet problem $\partial_{t}u - \rho_{\lambda}(x)u\Delta u = \rho_{\lambda}(x)g_{0}(x)u$ on the half line $(0,\infty)$. We find weak solutions from $L^p\ (p <…

Analysis of PDEs · Mathematics 2025-03-19 William Porteous , Irene M. Gamba , Kun Huang

We derive rates of convergence for limit theorems that reveal the intricate structure of the phase transitions in a mean-field version of the Blume-Emery-Griffith model. The theorems consist of scaling limits for the total spin. The model…

Probability · Mathematics 2015-06-15 Peter Eichelsbacher , Bastian Martschink

We construct counterexamples for the partial data inverse problem for the fractional conductivity equation in all dimensions on general bounded open sets. In particular, we show that for any bounded domain $\Omega \subset \mathbb{R}^n$ and…

Analysis of PDEs · Mathematics 2024-09-10 Jesse Railo , Philipp Zimmermann

Counterfactual examples are an appealing class of post-hoc explanations for machine learning models. Given input $x$ of class $y_1$, its counterfactual is a contrastive example $x^\prime$ of another class $y_0$. Current approaches primarily…

Machine Learning · Computer Science 2022-05-17 Xiaoting Shao , Kristian Kersting

This paper is concerned with quasi-linear parabolic equations driven by an additive forcing $\xi \in C^{\alpha-2}$, in the full sub-critical regime $\alpha \in (0,1)$. We are inspired by Hairer's regularity structures, however we work with…

Analysis of PDEs · Mathematics 2024-03-28 Felix Otto , Jonas Sauer , Scott Smith , Hendrik Weber

The work presents integral solutions of the fractional subdiffusion equation by an integral method, as an alternative approach to the solutions employing hypergeometric functions. The integral solution suggests a preliminary defined profile…

Mathematical Physics · Physics 2011-03-09 Jordan Hristov

Variational regularisation is the primary method for solving inverse problems, and recently there has been considerable work leveraging deeply learned regularisation for enhanced performance. However, few results exist addressing the…

Optimization and Control · Mathematics 2024-06-18 Zakhar Shumaylov , Jeremy Budd , Subhadip Mukherjee , Carola-Bibiane Schönlieb

The main part of this contribution to the special issue of EJM-B/Fluids dedicated to Patrick Huerre outlines the problem of the subcritical transition to turbulence in wall-bounded flows in its historical perspective with emphasis on plane…

Fluid Dynamics · Physics 2015-06-19 Paul Manneville

We examine the transition from trivial to non-trivial phases in a Su-Schrieffer-Heeger model subjected to disorder in a quasi-periodic environment. We analytically determine the phase boundary, and characterize the localization of normal…

Statistical Mechanics · Physics 2025-12-09 Sayan Sircar

We show that one can perform causal inference in a natural way for continuous-time scenarios using tools from stochastic analysis. This provides new alternatives to the positivity condition for inverse probability weighting. The probability…

Statistics Theory · Mathematics 2013-04-23 Kjetil Røysland

We study elliptic and parabolic problems governed by the singular elliptic operators \begin{align*} \mathcal L=y^{\alpha_1}\mbox{Tr }\left(QD^2_xu\right)+2y^{\frac{\alpha_1+\alpha_2}{2}}q\cdot \nabla_xD_y+\gamma y^{\alpha_2}…

Analysis of PDEs · Mathematics 2024-05-17 Giorgio Metafune , Luigi Negro , Chiara Spina

Normalizing flows are a powerful tool for generative modelling, density estimation and posterior reconstruction in Bayesian inverse problems. In this paper, we introduce proximal residual flows, a new architecture of normalizing flows.…

Machine Learning · Computer Science 2023-05-19 Johannes Hertrich

We study nonparametric regression under covariate shift with structured data, where a small amount of labeled target data is supplemented by a large labeled source dataset. In many real-world settings, the covariates in the target domain…

Statistics Theory · Mathematics 2025-07-02 Yuyao Wang , Nabarun Deb , Debarghya Mukherjee

This paper presents regularity results and associated high-order numerical methods for one-dimensional Fractional-Laplacian boundary-value problems. On the basis of a factorization of solutions as a product of a certain edge-singular weight…

Numerical Analysis · Mathematics 2017-05-09 Gabriel Acosta , Juan Pablo Borthagaray , Oscar Bruno , Martín Maas

Consider a free boundary problem of compressible-incompressible two-phase flows with surface tension and phase transition in bounded domains $\Omega_{t +}, \Omega_{t -} \subset \mathbb{R}^N$, $N \ge 2$, where the domains are separated by a…

Analysis of PDEs · Mathematics 2021-01-26 Keiichi Watanabe

We study the survival/extinction phase transition for contact processes with quenched disorder. The disorder is given by a locally finite random graph with vertices indexed by the integers that is assumed to be invariant under index shifts…

Probability · Mathematics 2025-08-06 Benedikt Jahnel , Lukas Lüchtrath , Christian Mönch

The crossover among two or more types of diffusive processes represents a vibrant theme in nonequilibrium statistical physics. In this work we propose two models to generate crossovers among different L\'evy processes: in the first model we…

Statistical Mechanics · Physics 2020-09-15 Maike A. F. dos Santos , Fernando D. Nobre , Evaldo M. F. Curado

Overfitting is a well-known issue in machine learning that occurs when a model struggles to generalize its predictions to new, unseen data beyond the scope of its training set. Traditional techniques to mitigate overfitting include early…

Machine Learning · Computer Science 2025-12-09 Flavio Giorgi , Fabiano Veglianti , Fabrizio Silvestri , Gabriele Tolomei

A phase-field model that allows for quantitative simulations of low-speed eutectic and peritectic solidification under typical experimental conditions is developed. Its cornerstone is a smooth free-energy functional, designed so that the…

Materials Science · Physics 2009-11-11 R. Folch , M. Plapp