Searched for: subject%3A%22tensors%22
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van Dijk, Mees (author)
Algorithms which can effectively detect epileptic seizures have the potential to improve current treatment methods for people who suffer from epilepsy. The current state-of-the-art methods use neural networks, which are able to learn directly from the electroencephalogram (EEG) data without feature extraction. However, neural networks have...
master thesis 2024
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Kirchner, K. (author), Schwab, Christoph (author)
We formulate standard and multilevel Monte Carlo methods for the kth moment M<sub>ε</sub><sup>k</sup>[ξ] of a Banach space valued random variable ξ:Ω→E, interpreted as an element of the k-fold injective tensor product space ⊗<sub>ε</sub><sup>k</sup>E. For the standard Monte Carlo estimator of M<sub>ε</sub><sup>k</sup>[ξ], we prove the k...
journal article 2024
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Masfara, La ODE Marzujriban (author), Weemstra, C. (author)
The Hamiltonian Monte Carlo algorithm is known to be highly efficient when sampling high-dimensional model spaces due to Hamilton's equations guiding the sampling process. For weakly non-linear problems, linearizing the forward problem enhances this efficiency. This study integrates this linearization with geological prior knowledge for...
journal article 2024
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Kerkhove, Casper (author)
The recent success of - and demand for - compliant mechanisms has increased rapidly within the micro-electromechanical systems-, aircraft-, spacecraft-, surgical-, and precision-instrument industries. Yet, even greater success may be achieved by overcoming the computational cost and instability of the mechanisms' design methodology. This...
master thesis 2023
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Smeenk, Rutger (author)
This research aims at quantifying the uncertainty in the predictions of tensor network constrained kernel machines, focusing on the Canonical Polyadic Decomposition (CPD) constrained kernel machine. Constraining the parameters in the kernel machine optimization problem to be a CPD results in a linear computational complexity in the number of...
master thesis 2023
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Stunnenberg, Kenneth (author)
Brain disorders in children pose significant challenges to their development, impacting cognition, speech, movement, and behavior. The uncertainty surrounding prognostic information at the time of diagnosis leaves families with numerous questions about the future. The Child Brain Lab at Erasmus MC Sophia Children's Hospital conducts IQ,...
master thesis 2023
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de Heer, Owen (author)
Matrix multiplication with the standard algorithm has an algebraic complexity of O(n^3) for n x n matrices, but in 1969 Strassen found another algorithm for multiplying 2 x 2 matrices with which he showed that matrix multiplication can be done with a complexity of O(n^2.81) by applying his algorithm recursively for large...
bachelor thesis 2023
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van Dobben de Bruyn, J. (author)
doctoral thesis 2023
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Teh, Irvin (author), Shelley, David (author), Boyle, J.H. (author), Zhou, Fenglei (author), Poenar, Ana Maria (author), Sharrack, Noor (author), Foster, Richard J. (author), Yuldasheva, Nadira Y. (author), Parker, Geoff J.M. (author)
Purpose: Tensor-valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the technical feasibility of tensor-valued diffusion encoding at high b-values with q-space trajectory imaging (QTI) analysis, in the human heart in vivo....
journal article 2023
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Draganov, D.S. (author), Naranjo, D. (author), Polychronopoulou, Katerina (author), Weemstra, C. (author)
Geothermal energy is a cleaner and more sustainable source of power, which plays a key role in the transition to a low-carbon economy. Sustainable and safe exploitation of geothermal resources, however, depends on our ability to understand and manage the associated seismic risks. In 2018, Nature's Heat geothermal project began operations in...
abstract 2023
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Chimmalgi, S. (author), Wahls, S. (author)
Riemann theta functions play a crucial role in the field of nonlinear Fourier analysis, where they are used to realize inverse nonlinear Fourier transforms for periodic signals. The practical applicability of this approach has however been limited since Riemann theta functions are multi-dimensional Fourier series whose computation suffers...
journal article 2023
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Li, Longlong (author), Khait, M. (author), Voskov, D.V. (author), Terekhov, Kirill M. (author), Abushaikha, Ahmad (author)
We apply Massively Parallel Interface for MPFA-O scheme with state-of-the-art Operator-Based Linearization (OBL) approach for multiphase flow in porous media. The implementation of MPFA-O scheme enhances the modelling capabilities for non-K-orthogonal mesh. A fully implicit scheme is applied to guarantee the stability of solutions when a mass...
journal article 2023
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Gülmez, D.E. (author), Maldonado, Jesus (author), Masania, K. (author), Sinke, J. (author), Dransfeld, C.A. (author)
Chopped Tape Thermoplastic Composites (CTTCs) offer high formability and performance for complex-shaped components in the aerospace and automotive industries. However, the mesoscopic discontinuity leads to spatial variabilities and correspondingly high scatter in the elastic properties of CTTCs due to the random orientations of chopped tapes...
journal article 2023
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Hehenberger, S.P. (author), Caizzone, Stefano (author), Thurner, Stefan (author), Yarovoy, Alexander (author)
Additive manufactured structured dielectrics with engineered permittivity tensors are promising tools for novel microwave components and are drawing increasing attention from researchers. However, design modeling and experimental verification of anisotropic materials are challenging and have not yet been thoroughly explored in the literature. In...
conference paper 2023
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de Rooij, S.J.S. (author), Batselier, K. (author), Hunyadi, Borbala (author)
Recent advancements in wearable EEG devices have highlighted the importance of accurate seizure detection algorithms, yet the ever-increasing size of the generated datasets poses a significant challenge to existing seizure detection methods based on kernel machines. Typically, this problem is mitigated by significantly undersampling the...
conference paper 2023
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Denarié, Pierre-Antoine (author)
Blind Source Separation (BSS), the separation of latent source components from observed mixtures, is relevant to many fields of expertise such as neuro-imaging, economics and machine learning. Reliable estimates of the sources can be obtained through diagonalization of the cumulant tensor, i.e., a fourth-order symmetric multi-linear array...
master thesis 2022
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Jonnalagadda, Aravind (author)
Natural Language Processing (NLP) deals with understanding and processing human text by any computer software. There are several network architectures in the fields of deep learning and artificial intelligence that are used for NLP. Deep learning techniques like recurrent neural networks and feed-forward neural networks are used to develop...
master thesis 2022
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Chandrashekar, Rohan (author)
Humans make decisions when presented with choices based on influences. The Internet today presents people with abundant choices to choose from. Recommending choices with an emphasis on people's preferences has become increasingly sought. Grundy (1979), the first computer librarian Recommender System (RS), provided users with book recommendations...
master thesis 2022
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van Mourik, Ewoud (author)
This thesis studies the Canonical Polyadic Decomposition (CPD) constrained kernel machine for large scale learning, i.e. learning with a large number of samples. The kernel machine optimization problem is solved in the primal space, such that the complexity of the problem scales linearly in the number of samples as opposed to scaling cubically...
master thesis 2022
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CHENG, ZHIMIN (author)
A wide range of practical problems involve computing multi-dimensional integrations. However, in most cases, it is hard to find analytical solutions to these multi-dimensional integrations. Their numerical solutions always suffer from the `curse of dimension', which means the computational complexity grows exponentially with respect to the...
master thesis 2022
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