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Flaschel, Moritz (author), Kumar, Siddhant (author), De Lorenzis, Laura (author)We propose a new approach for data-driven automated discovery of isotropic hyperelastic constitutive laws. The approach is unsupervised, i.e., it requires no stress data but only displacement and global force data, which are realistically available through mechanical testing and digital image correlation techniques; it delivers interpretable...journal article 2021
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Feng, S. (author), Scharenborg, O.E. (author)For a language with no transcribed speech available (the zero-resource scenario), conventional acoustic modeling algorithms are not applicable. Recently, zero-resource acoustic modeling has gained much interest. One research problem is unsupervised subword modeling (USM), i.e., learning a feature representation that can distinguish subword units...conference paper 2021
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Zhou, Zixia (author), Zu, Xinrui (author), Wang, Yuanyuan (author), Lelieveldt, Boudewijn P.F. (author), Tao, Q. (author)Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this article, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a...journal article 2021
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Villa, Amalia (author), Narayanan, Abhijith Mundanad (author), Van Huffel, Sabine (author), Bertrand, Alexander (author), Varon, Carolina (author)Feature selection techniques are very useful approaches for dimensionality reduction in data analysis. They provide interpretable results by reducing the dimensions of the data to a subset of the original set of features. When the data lack annotations, unsupervised feature selectors are required for their analysis. Several algorithms for...journal article 2021
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Nadeem, A. (author), Hammerschmidt, C.A. (author), Hernandez Ganan, C. (author), Verwer, S.E. (author)Malware family labels are known to be inconsistent. They are also black-box since they do not represent the capabilities of malware. The current state of the art in malware capability assessment includes mostly manual approaches, which are infeasible due to the ever-increasing volume of discovered malware samples. We propose a novel...book chapter 2021
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Simion-Constantinescu, Andrei (author)This thesis presents a novel self-supervised approach of learning visual representations from videos containing human actions. Our approach tackles the complex problem of learning without the need of labeled data by exploring to what extent the ideas successfully used for images can be transferred, adapted and extended to videos for action...master thesis 2020
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Man, K.W. (author)As software is produced more and more every year, software also gets exploited more. This exploitation can lead to huge monetary losses and other damages to companies and users. The exploitation can be reduced by automatically detecting the software vulnerabilities that leads to exploitation. Unfortunately, the state-of-the-art methods for this...master thesis 2020
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Ciulei, Victor (author)Airlines plan the trajectory of their flights in advance. However, this plan is not always followed since, during the actual flight, aircraft deviate either horizontally by rerouting, or vertically by choosing a different Flight Level. The issue arises when some airlines frequently deviate from their flight plans frequently, to the disadvantage...master thesis 2020
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Simidžioski, Magdalena (author)To detect malicious activities in a network, intrusion detection systems are used. Even though these solutions are widely deployed for this purpose they have one serious shortcoming which is the huge amount of false alarms that they are generating. Different measures are taken to tackle this problem such as manually changing the settings of the...master thesis 2020
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Trommel, Kars (author)During the preparation for the Olympic Sailing Competition, held in 2021 in Tokyo, Japan, the Dutch National Sailing Team encountered days with unpredicted wind behaviour. To gain more understanding in the wind patterns occurring, a deep learning based approach is taken. The goal of this research is to find out if unsupervised learning methods...master thesis 2020
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Jooste, Nicael (author)In this study, an unsupervised classification approach is used to investigate and characterize the spatial and temporal variability of MetOp-A ASCAT backscatter (σ◦) and the TUW SMR vegetation parameters across mainland France between 2007 and 2017. Currently, soil moisture data is retrieved from ASCAT backscatter measurements using the TU Wien...master thesis 2020
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Gudi, A.A. (author), Bittner, M. (author), van Gemert, J.C. (author)Remote photo-plethysmography (rPPG) uses a camera to estimate a person’s heart rate (HR). Similar to how heart rate can provide useful information about a person’s vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine fluctuations in the...journal article 2020
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Wang, H. (author)The condition monitoring of railway infrastructures is collecting big data for intelligent asset management. Making the most of the big data is a critical challenge facing the railway industry. This study focuses on one of the main railway infrastructures, namely the catenary (overhead line) system that transmits power to trains. To facilitate...conference paper 2020
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Zhang, Zheming (author), Wang, Fang (author), Pang, Y. (author), Yan, Gaowei (author)The problem of misalignment of the original measurement model is caused by nonlinear, time-varying characteristic of the batch process. In this paper, a method based on geodesic flow kernel (GFK) for feature transfer is proposed. By mapping data into the manifold space, the feature transfer from source domain to target domain is implemented....conference paper 2020
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Scharenborg, O.E. (author), Besacier, Laurent (author), Black, Alan W. (author), Hasegawa-Johnson, Mark (author), Metze, Florian (author), Neubig, Graham (author), Stueker, Sebastian (author), Godard, Pierre (author), Mueller, M (author)Speech technology plays an important role in our everyday life. Among others, speech is used for human-computer interaction, for instance for information retrieval and on-line shopping. In the case of an unwritten language, however, speech technology is unfortunately difficult to create, because it cannot be created by the standard...journal article 2020
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Feng, S. (author), Scharenborg, O.E. (author)This study addresses unsupervised subword modeling, i.e.,<br/>learning feature representations that can distinguish subword<br/>units of a language. The proposed approach adopts a two-stage<br/>bottleneck feature (BNF) learning framework, consisting of autoregressive<br/>predictive coding (APC) as a front-end and a DNNBNF<br/>model as a back-end...conference paper 2020
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Roeling, M.P. (author), Nadeem, A. (author), Verwer, S.E. (author)Network data clustering and sequential data mining are large<br/>fields of research, but how to combine them to analyze spatial-temporal<br/>network data remains a technical challenge. This study investigates a<br/>novel combination of two sequential similarity methods (Dynamic Time<br/>Warping and N-grams with Cosine distances), with two state...conference paper 2020
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Wang, He (author), Cucu Laurenciu, N. (author), Jiang, Y. (author), Cotofana, S.D. (author)To fully unleash the potential of graphene-based devices for neuromorphic computing, we propose a graphene synapse and a graphene neuron that form together a basic Spiking Neural Network (SNN) unit, which can potentially be utilized to implement complex SNNs. Specifically, the proposed synapse enables two fundamental synaptic functionalities,...journal article 2020
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Pathak, Chinmay (author)Anomaly detection is a task of interest in many domains. Typical way of tackling this problem is using an unsupervised way. Recently, deep neural network based density estimators such as Normalizing flows have seen a huge interest. The ability of these models to do the exact latent-variable inference and exact log-likelihood calculation with...master thesis 2019
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Paredes-Vallés, Federico (author), Scheper, K.Y.W. (author), de Croon, G.C.H.E. (author)The combination of spiking neural networks and event-based vision sensors holds the potential of highly efficient and high-bandwidth optical flow estimation. This paper presents the first hierarchical spiking architecture in which motion (direction and speed) selectivity emerges in an unsupervised fashion from the raw stimuli generated with an...journal article 2019