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Related papers: Multi-dimensional interpolations in C++

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This work aims to assess the state of the art of data parallel deep neural network training, trying to identify potential research tracks to be exploited for performance improvement. Beside, it presents a design for a practical C++ library…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-26 Paolo Viviani , Maurizio Drocco , Marco Aldinucci

We present Clusterplot, a multi-class high-dimensional data visualization tool designed to visualize cluster-level information offering an intuitive understanding of the cluster inter-relations. Our unique plots leverage 2D blobs devised to…

Graphics · Computer Science 2021-03-05 Or Malkai , Min Lu , Daniel Cohen-Or

The last two decades have seen major developments in interpolatory methods for model reduction of large-scale linear dynamical systems. Advances of note include the ability to produce (locally) optimal reduced models at modest cost; refined…

Numerical Analysis · Mathematics 2014-09-18 Christopher Beattie , Serkan Gugercin

Developing an understanding of high-dimensional data can be facilitated by visualizing that data using dimensionality reduction. However, the low-dimensional embeddings are often difficult to interpret. To facilitate the exploration and…

Machine Learning · Computer Science 2025-04-16 Fuyin Lai , Edith Heiter , Guillaume Bied , Jefrey Lijffijt

The use of applications on computers, smartphones, and tablets has been considerably simplied thanks to interactive and dynamic graphical interfaces coupled with the mouse and touch screens. It is no longer necessary to be a computer…

Human-Computer Interaction · Computer Science 2025-11-21 Michel Adam , Patrice Frison , Moncef Daoud , Sabine Letellier Zarshenas

Controlling infinite dimensional models remains a challenging task for many practitioners since they are not suitable for traditional control design techniques or will result in a high-order controller too complex for implementation.…

Systems and Control · Electrical Eng. & Systems 2020-12-17 Pauline Kergus

Given a large set of measurement sensor data, in order to identify a simple function that captures the essence of the data gathered by the sensors, we suggest representing the data by (spatial) functions, in particular by polynomials. Given…

Networking and Internet Architecture · Computer Science 2012-10-12 Hadassa Daltrophe , Shlomi Dolev , Zvi Lotker

Standard approaches for variable selection in linear models are not tailored to deal properly with high-dimensional and incomplete data. Currently, methods dedicated to high-dimensional data handle missing values by ad-hoc strategies, like…

Methodology · Statistics 2021-06-09 Avner Bar-Hen , Vincent Audigier

The Hermite interpolation formulas are based on the interpretation of interpolation nodes as roots of suitable polynomials. Therefore, such formulas belong to the class of algebraic interpolations. The article considers a multidimensional…

Complex Variables · Mathematics 2022-06-24 Matvey Durakov , Evgeniy Leinartas , August Tsikh

Provided a special function of one variable and some of its derivatives can be accurately computed over a finite range, a method is presented to build a series of polynomial approximations of the function with a defined relative error over…

Computational Physics · Physics 2007-05-23 C. Semay

We present a framework for efficiently performing Monte Carlo wave-function simulations in cavity QED with moving particles. It relies heavily on the object-oriented programming paradigm as realised in C++, and is extensible and applicable…

Quantum Physics · Physics 2009-11-13 A. Vukics , H. Ritsch

This paper suggests integrating one-dimensional optimization methods to tackle diverse problems, emphasizing their significance in resolving practical issues and applying mathematical principles to real-world contexts. It focuses on…

Optimization and Control · Mathematics 2024-06-19 Erick Clapton de Lima Silva , Francisco Márcio Barboza

In recent years, rather than enclosing data within a single organization, exchanging and combining data from different domains has become an emerging practice. Many studies have discussed the economic and utility value of data and data…

Computers and Society · Computer Science 2020-12-23 Teruaki Hayashi , Hiroki Sakaji , Hiroyasu Matsushima , Yoshiaki Fukami , Takumi Shimizu , Yukio Ohsawa

Craig interpolation and uniform interpolation have many applications in knowledge representation, including explainability, forgetting, modularization and reuse, and even learning. At the same time, many relevant knowledge representation…

Artificial Intelligence · Computer Science 2025-12-10 Jean Christoph Jung , Patrick Koopmann , Matthias Knorr

Particle filters are a class of algorithms that are used for "tracking" or "filtering" in real-time for a wide array of time series models. Despite their comprehensive applicability, particle filters are not always the tool of choice for…

Computation · Statistics 2020-01-29 Taylor R. Brown

Object-oriented programming languages such as Java and Objective C have become popular for implementing agent-based and other object-based simulations since objects in those languages can {\em reflect} (i.e. make runtime queries of an…

Programming Languages · Computer Science 2007-05-23 Duraid Madina , Russell K. Standish

As computational challenges in optimization and statistical inference grow ever harder, algorithms that utilize derivatives are becoming increasingly more important. The implementation of the derivatives that make these algorithms so…

Mathematical Software · Computer Science 2015-09-25 Bob Carpenter , Matthew D. Hoffman , Marcus Brubaker , Daniel Lee , Peter Li , Michael Betancourt

The traditional split-up into a low level language and a high level language in the design of computer algebra systems may become obsolete with the advent of more versatile computer languages. We describe GiNaC, a special-purpose system…

Symbolic Computation · Computer Science 2007-05-23 Christian Bauer , Alexander Frink , Richard Kreckel

Several machine learning models are defined for inputs of any size, such as graphs with different numbers of nodes and point clouds containing varying numbers of points. The universality properties of such any-dimensional models remain…

Machine Learning · Computer Science 2026-05-25 Shengtai Yao , Eitan Levin , Mateo Díaz

Good parametrisations of affine transformations are essential to interpolation, deformation, and analysis of shape, motion, and animation. It has been one of the central research topics in computer graphics. However, there is no single…

Graphics · Computer Science 2016-07-07 Shizuo Kaji , Hiroyuki Ochiai
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