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We prove that under certain stability and smoothing properties of the semi-groups generated by the partial differential equations that we consider, manifolds left invariant by these flows persist under $C^1$ perturbation. In particular, we…

Analysis of PDEs · Mathematics 2025-10-20 Don A. Jones , Steve Shkoller

Persistent homology is a fundamental tool in Topological Data Analysis. The associated algebraic structure is the persistence module, a sequence of vector spaces connected by linear maps. Persistence modules admit a complete and…

Algebraic Topology · Mathematics 2026-02-13 R. Gonzalez-Diaz , M. Soriano-Trigueros , A. Torras-Casas

We show that computing the interleaving distance between two multi-graded persistence modules is NP-hard. More precisely, we show that deciding whether two modules are $1$-interleaved is NP-complete, already for bigraded, interval…

Computational Geometry · Computer Science 2019-10-10 Håvard Bakke Bjerkevik , Magnus Bakke Botnan , Michael Kerber

Motivated both by theoretical and practical considerations in topological data analysis, we generalize the $p$-Wasserstein distance on barcodes to multiparameter persistence modules. For each $p\in [1,\infty]$, we in fact introduce two such…

Algebraic Topology · Mathematics 2021-11-12 Håvard Bakke Bjerkevik , Michael Lesnick

Persistent homology is a popular method for computing topological features of (metric) data. Standard approaches based on the \v{C}ech or Rips filtration are stable under small perturbations of the data, but highly sensitive to outliers.…

Algebraic Topology · Mathematics 2026-02-27 Pepijn Roos Hoefgeest , Lucas Slot

In this paper, we consider one-to-one matchings between two disjoint groups of agents. Each agent has a preference over a subset of the agents in the other group, and these preferences may contain ties. Strong stability is one of the…

Computer Science and Game Theory · Computer Science 2024-01-08 Naoyuki Kamiyama

We develop some aspects of the homological algebra of persistence modules, in both the one-parameter and multi-parameter settings, considered as either sheaves or graded modules. The two theories are different. We consider the graded module…

Algebraic Topology · Mathematics 2022-05-09 Peter Bubenik , Nikola Milicevic

To understand the empirical success of approximate MAP inference, recent work (Lang et al., 2018) has shown that some popular approximation algorithms perform very well when the input instance is stable. The simplest stability condition…

Machine Learning · Statistics 2020-11-16 Hunter Lang , David Sontag , Aravindan Vijayaraghavan

In the fundamental Stable Marriage and Stable Roommates problems, there are inherent trade-offs between the size and stability of solutions. While in the former problem, a stable matching always exists and can be found efficiently using the…

Computer Science and Game Theory · Computer Science 2026-01-27 Frederik Glitzner , David Manlove

We propose a general technique for extracting a larger set of stable information from persistent homology computations than is currently done. The persistent homology algorithm is usually viewed as a procedure which starts with a filtered…

Computational Geometry · Computer Science 2021-01-29 Paul Bendich , Peter Bubenik , Alexander Wagner

Multiparameter persistence modules can be uniquely decomposed into indecomposable summands. Among these indecomposables, intervals stand out for their simplicity, making them preferable for their ease of interpretation in practical…

Algebraic Topology · Mathematics 2024-03-19 Ángel Javier Alonso , Michael Kerber , Primoz Skraba

We study the stability properties of nonlinear multi-task regression in reproducing Hilbert spaces with operator-valued kernels. Such kernels, a.k.a. multi-task kernels, are appropriate for learning prob- lems with nonscalar outputs like…

Machine Learning · Computer Science 2013-06-18 Julien Audiffren , Hachem Kadri

We present a general framework how to investigate stability of solutions within a single self-consistent renormalization scheme being a parquet-type extension of the Baym-Kadanoff construction of conserving approximations. To obtain a…

Strongly Correlated Electrons · Physics 2009-10-31 V. Janis

In topological data analysis, we want to discern topological and geometric structure of data, and to understand whether or not certain features of data are significant as opposed to simply random noise. While progress has been made on…

Computational Geometry · Computer Science 2020-01-10 So Mang Han , Taylor Okonek , Nikesh Yadav , Xiaojun Zheng

A method to apply and visualize persistent homology of time series is proposed. The method captures persistent features in space and time, in contrast to the existing procedures, where one usually chooses one while keeping the other fixed.…

Algebraic Topology · Mathematics 2024-12-17 Martina Flammer , Knut Hüper

In this paper, we introduce a novel persistence framework for Morse decompositions in Markov chains using combinatorial multivector fields. Our approach provides a structured method to analyze recurrence and stability in finite-state…

Dynamical Systems · Mathematics 2025-03-31 Donald Woukeng

We study continuity of the roots of nonmonic polynomials as a function of their coefficients using only the most elementary results from an introductory course in real analysis and the theory of single variable polynomials. Our approach…

Classical Analysis and ODEs · Mathematics 2021-12-30 Anthony Stefan , Aaron Welters

We consider the multi-frequency inverse source problem in the presence of a non-homogeneous medium using passive measurements. Precisely, we derive stability estimates for determining the source from the knowledge of only the imaginary part…

Analysis of PDEs · Mathematics 2024-04-23 Faouzi Triki , Kristoffer Linder-Steinlein , Mirza Karamehmedovic

In this paper we study the existence and regularity of stable manifolds associated to fixed points of parabolic type in the differentiable and analytic cases, using the parametrization method. The parametrization method relies on a suitable…

Dynamical Systems · Mathematics 2016-03-09 Inmaculada Baldomá , Ernest Fontich , Pau Martín

Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs) which are 2D multisets of points. Their variable size makes them, however, difficult to combine…

Machine Learning · Statistics 2019-06-14 Bartosz Zielinski , Michal Lipinski , Mateusz Juda , Matthias Zeppelzauer , Pawel Dlotko
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