International Conference on Conceptual Structures最新文献_第2页

Maximal Ordinal Two-Factorizations 极大有序二分解

International Conference on Conceptual Structures Pub Date : 2023-04-06 DOI: 10.48550/arXiv.2304.03338

Dominik Dürrschnabel, Gerd Stumme

引用次数: 1

Enabling Non-Linear Quantum Operations through Variational Quantum Splines 通过变分量子样条实现非线性量子运算

International Conference on Conceptual Structures Pub Date : 2023-03-08 DOI: 10.48550/arXiv.2303.04788

Matteo Antonio Inajetovic, Filippo Orazi, A. Macaluso, Stefano Lodi, Claudio Sartori

{"title":"Enabling Non-Linear Quantum Operations through Variational Quantum Splines","authors":"Matteo Antonio Inajetovic, Filippo Orazi, A. Macaluso, Stefano Lodi, Claudio Sartori","doi":"10.48550/arXiv.2303.04788","DOIUrl":"https://doi.org/10.48550/arXiv.2303.04788","url":null,"abstract":"The postulates of quantum mechanics impose only unitary transformations on quantum states, which is a severe limitation for quantum machine learning algorithms. Quantum Splines (QSplines) have recently been proposed to approximate quantum activation functions to introduce non-linearity in quantum algorithms. However, QSplines make use of the HHL as a subroutine and require a fault-tolerant quantum computer to be correctly implemented. This work proposes the Generalised QSplines (GQSplines), a novel method for approximating non-linear quantum activation functions using hybrid quantum-classical computation. The GQSplines overcome the highly demanding requirements of the original QSplines in terms of quantum hardware and can be implemented using near-term quantum computers. Furthermore, the proposed method relies on a flexible problem representation for non-linear approximation and it is suitable to be embedded in existing quantum neural network architectures. In addition, we provide a practical implementation of GQSplines using Pennylane and show that our model outperforms the original QSplines in terms of quality of fitting.","PeriodicalId":125954,"journal":{"name":"International Conference on Conceptual Structures","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133246028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Spatially-varying meshless approximation method for enhanced computational efficiency 提高计算效率的空间变化无网格逼近方法

International Conference on Conceptual Structures Pub Date : 2023-03-03 DOI: 10.48550/arXiv.2303.01760

M. Jančič, Miha Rot, G. Kosec

{"title":"Spatially-varying meshless approximation method for enhanced computational efficiency","authors":"M. Jančič, Miha Rot, G. Kosec","doi":"10.48550/arXiv.2303.01760","DOIUrl":"https://doi.org/10.48550/arXiv.2303.01760","url":null,"abstract":"In this paper, we address a way to reduce the total computational cost of meshless approximation by reducing the required stencil size through spatial variation of computational node regularity. Rather than covering the entire domain with scattered nodes, only regions with geometric details are covered with scattered nodes, while the rest of the domain is discretised with regular nodes. Consequently, in regions covered with regular nodes the approximation using solely the monomial basis can be performed, effectively reducing the required stencil size compared to the approximation on scattered nodes where a set of polyharmonic splines is added to ensure convergent behaviour. The performance of the proposed hybrid scattered-regular approximation approach, in terms of computational efficiency and accuracy of the numerical solution, is studied on natural convection driven fluid flow problems. We start with the solution of the de Vahl Davis benchmark case, defined on square domain, and continue with two- and three-dimensional irregularly shaped domains. We show that the spatial variation of the two approximation methods can significantly reduce the computational complexity, with only a minor impact on the solution accuracy.","PeriodicalId":125954,"journal":{"name":"International Conference on Conceptual Structures","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123346275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph-level representations using ensemble-based readout functions 使用基于集成的读出函数的图形级表示

International Conference on Conceptual Structures Pub Date : 2023-03-03 DOI: 10.48550/arXiv.2303.02023

Jakub Binkowski, Albert Sawczyn, Denis Janiak, Piotr Bielak, Tomasz Kajdanowicz

引用次数: 0

RAFEN - Regularized Alignment Framework for Embeddings of Nodes RAFEN -节点嵌入的正则化对齐框架

International Conference on Conceptual Structures Pub Date : 2023-03-03 DOI: 10.48550/arXiv.2303.01926

Kamil Tagowski, Piotr Bielak, Jakub Binkowski, Tomasz Kajdanowicz

引用次数: 0

Oscillatory behaviour of the RBF-FD approximation accuracy under increasing stencil size 增大模板尺寸时RBF-FD近似精度的振荡特性

International Conference on Conceptual Structures Pub Date : 2023-03-03 DOI: 10.48550/arXiv.2303.02252

Andrej Kolar-Pozun, M. Jančič, Miha Rot, G. Kosec

引用次数: 0

Data-Driven Stability Analysis of a Chaotic Time-Delayed System 混沌时滞系统的数据驱动稳定性分析

International Conference on Conceptual Structures Pub Date : 2023-02-14 DOI: 10.1007/978-3-031-36027-5_31

G. Margazoglou, L. Magri

引用次数: 0

Solving (Max) 3-SAT via Quadratic Unconstrained Binary Optimization 利用二次无约束二元优化求解(Max) 3-SAT

International Conference on Conceptual Structures Pub Date : 2023-02-07 DOI: 10.48550/arXiv.2302.03536

Jonas Nusslein, Sebastian Zieliński, Thomas Gabor, Claudia Linnhoff-Popien, Sebastian Feld

引用次数: 3

Physics-Informed Long Short-Term Memory for Forecasting and Reconstruction of Chaos 基于物理的长短期记忆预测与混沌重建

International Conference on Conceptual Structures Pub Date : 2023-02-03 DOI: 10.48550/arXiv.2302.10779

Elise Özalp, G. Margazoglou, L. Magri

{"title":"Physics-Informed Long Short-Term Memory for Forecasting and Reconstruction of Chaos","authors":"Elise Özalp, G. Margazoglou, L. Magri","doi":"10.48550/arXiv.2302.10779","DOIUrl":"https://doi.org/10.48550/arXiv.2302.10779","url":null,"abstract":"We present the Physics-Informed Long Short-Term Memory (PI-LSTM) network to reconstruct and predict the evolution of unmeasured variables in a chaotic system. The training is constrained by a regularization term, which penalizes solutions that violate the system's governing equations. The network is showcased on the Lorenz-96 model, a prototypical chaotic dynamical system, for a varying number of variables to reconstruct. First, we show the PI-LSTM architecture and explain how to constrain the differential equations, which is a non-trivial task in LSTMs. Second, the PI-LSTM is numerically evaluated in the long-term autonomous evolution to study its ergodic properties. We show that it correctly predicts the statistics of the unmeasured variables, which cannot be achieved without the physical constraint. Third, we compute the Lyapunov exponents of the network to infer the key stability properties of the chaotic system. For reconstruction purposes, adding the physics-informed loss qualitatively enhances the dynamical behaviour of the network, compared to a data-driven only training. This is quantified by the agreement of the Lyapunov exponents. This work opens up new opportunities for state reconstruction and learning of the dynamics of nonlinear systems.","PeriodicalId":125954,"journal":{"name":"International Conference on Conceptual Structures","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114578305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Bayesian Optimization of the Layout of Wind Farms with a High-Fidelity Surrogate Model 基于高保真代理模型的风电场布局贝叶斯优化

International Conference on Conceptual Structures Pub Date : 2023-02-02 DOI: 10.1007/978-3-031-36027-5_26

Nikolaos Bempedelis, L. Magri

引用次数: 1