Persistence frameworks

Persistence framework

A persistence framework is middleware that assists in the storage and retrieval of information between applications and databases, especially relational databases. It acts as a layer of abstraction for persisted data, bridging conceptual and technical differences between storage and utilisation. Many persistence frameworks are also object-relational mapping (ORM) tools (e.g. Hibernate, MyBatis SQL Maps, Apache Cayenne, Entity Framework, Slick, and Java Ultra-Lite Persistence). Such frameworks map the objects in the application domain to data that needs to be persisted in a database. The mappings can be defined using either XML files or metadata annotations. (Wikipedia).

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Austin Lawson (7/15/20): A canonical framework for summarizing persistence diagrams

Title: Persistence curves: A canonical framework for summarizing persistence diagrams Abstract: As Topological Data Analysis (TDA) grows in popularity so too does the need for topological methods compatible with modern machine learning algorithms. The use of machine learning algorithms di

From playlist AATRN 2020

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Ulrich Bauer (3/19/19): Persistence diagrams as diagrams

Title: Persistence Diagrams as Diagrams Abstract: We explore the perspective of viewing persistence diagrams, or persistence barcodes, as diagrams in the categorical sense. Specifically, we consider functors indexed over the reals and taking values in the category of matchings, which has

From playlist AATRN 2019

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Massimo Ferri (8/30/21): Selection of points in persistence diagrams

The need for point selection in a persistence diagram is shown. We recall V. Kurlin's selection criterion, intended for producing a hierarchy of segmentations out of a point cloud: diagonal gaps. We also show some applications of it on generalised persistence functions. Then we introduce t

From playlist Beyond TDA - Persistent functions and its applications in data sciences, 2021

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RubyConf 2014 - Building Your API for Longevity by Mike Stowe

One of the greatest challenges to developing an API is ensuring that your API lasts. After all, you don't want to have to release and manage multiple versions of your API just because you weren't expecting users to use it a certain way, or because you didn't anticipate far enough down the

From playlist RubyConf 2014

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What is Microsoft .NET Framework | Microsoft .NET Framework Tutorial | Edureka

Watch Sample Class recording: http://www.edureka.co/microsoft-dotnet-framework?utm_source=youtube&utm_medium=referral&utm_campaign=what-is-net-framework .NET Framework is a software framework developed by Microsoft that runs primarily on Microsoft Windows. It includes a large class librar

From playlist Microsoft .NET Framework

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Persistence Curves [Austin Lawson]

In this tutorial, we will explore Persistence Curves, which is a framework for generating functional and vectorized summaries of persistence diagrams. The associated Python package and tutorial notebook (seen in this video) can be found here: https://github.com/azlawson/PersistenceCurves

From playlist Tutorial-a-thon 2021 Spring

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Algebraic Stability of Persistence Diagrams [Ziva Urbancic]

In this tutorial we take a look at algebraic stability theorem for persistence diagrams. To be able to state it we also define the interleaving distance between persistence modules. Links to the papers mentioned in the video: Cohen-Steiner, Edelsbrunner, Harer. Stability of Persistence Di

From playlist Tutorial-a-thon 2021 Spring

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Liz Munch (1/29/20): Featurization of persistence diagrams using template functions for ML tasks

Title: Featurization of persistence diagrams using template functions for machine learning tasks Abstract: The persistence diagram is an increasingly useful tool from Topological Data Analysis, but its use alongside typical machine learning techniques requires mathematical finesse. The m

From playlist AATRN 2020

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Mattia G. Bergomi (8/29/21): Comparing Neural Networks via Generalized Persistence

Artificial neural networks are often used as black boxes to solve supervised tasks. At each layer, the network updates its representation of the dataset to minimize a given error function, depending on the correct assignment of predetermined labels to each observed data point. On the other

From playlist Beyond TDA - Persistent functions and its applications in data sciences, 2021

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Yohai Reani (9/21/22): Persistent Cycle Registration and Topological Bootstrap

In this talk we will present a novel approach for comparing the persistent homology representations of two spaces (filtrations). Commonly used comparison methods are based on numerical summaries such as persistence diagrams and persistence landscapes, along with suitable metrics (e.g. Wass

From playlist AATRN 2022

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GoRuCo 2013 - Putting off Persistence by Lauren Voswinkel

In Rails, we have a beautiful framework that can take us from a blank slate to a fully-functional app in little time. However, doing things "The Rails Way" has a lot of implicit dependencies, including persistence. Are you really equipped to make one of the largest decisions about your app

From playlist GoRuCo 2013

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Rachel Levanger (3/13/18): A comparison framework for interleaved persistence modules

In this talk, we'll take a look at a recent result in the theory of persistent homology that can be used to rigorously track noise introduced during the computation of a barcode or a persistence diagram. We'll then illustrate the use of this framework by looking closely at a number of exam

From playlist AATRN 2018

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Yusu Wang (4/25/18): Graph reconstruction via discrete Morse theory

Graphs form one of the most important types of data in various applications across science and engineering. They could be geometric in nature, such as road networks in GIS, or relational and abstract, such as protein-protein interaction networks. A fundamental problem is to reconstruct a h

From playlist AATRN 2018

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François Petit (6/22/20): Ephemeral persistence modules and distance comparison

Title: Ephemeral persistence modules and distance comparison Abstract: Sheaf theoretic methods have been recently introduced to study persistent modules. Persistence homology studies filtered or multi-filtered topological spaces. The filtrations are indexed by the elements of an ordered

From playlist ATMCS/AATRN 2020

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Yuzhou Chen (10/27/21): Topological Relational Learning on Graphs

Graph neural networks (GNNs) have emerged as a powerful tool for graph classification and representation learning. However, GNNs tend to suffer from over-smoothing problems and are vulnerable to graph perturbations. To address these challenges, we propose a novel topological neural framewo

From playlist AATRN 2021

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What Is Spring Framework In Java | Spring Framework Tutorial For Beginners With Examples | Edureka

🔥 Spring Framework Certification Training - https://www.edureka.co/spring-framework This Edureka "What Is Spring Framework" tutorial will help you in understanding the fundamentals of Spring Framework and build a strong foundation in Spring. Below are the topics covered in this tutorial:

From playlist Spring Framework Tutorial Videos

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