Refine
Has Fulltext
- yes (2523) (remove)
Year of publication
Document Type
- Doctoral Thesis (2523) (remove)
Language
Keywords
- climate change (53)
- Klimawandel (51)
- Modellierung (34)
- Nanopartikel (28)
- machine learning (21)
- Fernerkundung (20)
- Synchronisation (19)
- remote sensing (18)
- Spracherwerb (17)
- Blickbewegungen (16)
Institute
- Institut für Physik und Astronomie (405)
- Institut für Biochemie und Biologie (384)
- Institut für Geowissenschaften (327)
- Institut für Chemie (303)
- Extern (149)
- Institut für Umweltwissenschaften und Geographie (122)
- Institut für Ernährungswissenschaft (102)
- Wirtschaftswissenschaften (97)
- Hasso-Plattner-Institut für Digital Engineering GmbH (89)
- Department Psychologie (88)
- Institut für Informatik und Computational Science (85)
- Department Linguistik (83)
- Institut für Mathematik (63)
- Sozialwissenschaften (57)
- Department Sport- und Gesundheitswissenschaften (53)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (44)
- Department Erziehungswissenschaft (41)
- Institut für Romanistik (23)
- Historisches Institut (20)
- Institut für Philosophie (17)
- Institut für Germanistik (15)
- Öffentliches Recht (14)
- Strukturbereich Kognitionswissenschaften (12)
- Institut für Anglistik und Amerikanistik (9)
- Institut für Jüdische Studien und Religionswissenschaft (9)
- Digital Engineering Fakultät (7)
- Fachgruppe Betriebswirtschaftslehre (7)
- Fachgruppe Politik- & Verwaltungswissenschaft (7)
- Fachgruppe Volkswirtschaftslehre (7)
- Institut für Künste und Medien (7)
- Department Grundschulpädagogik (5)
- Mathematisch-Naturwissenschaftliche Fakultät (5)
- Department Musik und Kunst (4)
- Fachgruppe Soziologie (4)
- Psycholinguistics and Neurolinguistics (4)
- Bürgerliches Recht (3)
- Potsdam Institute for Climate Impact Research (PIK) e. V. (3)
- Fakultät für Gesundheitswissenschaften (2)
- Institut für Jüdische Theologie (2)
- Institut für Slavistik (2)
- Interdisziplinäres Zentrum für Kognitive Studien (2)
- Multilingualism (2)
- Patholinguistics/Neurocognition of Language (2)
- Applied Computational Linguistics (1)
- Department für Inklusionspädagogik (1)
- Foundations of Computational Linguistics (1)
- Institut für Religionswissenschaft (1)
- Interdisziplinäres Zentrum für Dynamik komplexer Systeme (1)
- Kommunalwissenschaftliches Institut (1)
- Language Acquisition (1)
- Lehreinheit für Wirtschafts-Arbeit-Technik (1)
- Phonology & Phonetics (1)
- Potsdam Research Institute for Multilingualism (PRIM) (1)
- Potsdam Transfer - Zentrum für Gründung, Innovation, Wissens- und Technologietransfer (1)
- Strafrecht (1)
- Syntax, Morphology & Variability (1)
We establish elements of a new approach to ellipticity and parametrices within operator algebras on manifolds with higher singularities, only based on some general axiomatic requirements on parameter-dependent operators in suitable scales of spaes. The idea is to model an iterative process with new generations of parameter-dependent operator theories, together with new scales of spaces that satisfy analogous requirements as the original ones, now on a corresponding higher level. The "full" calculus involves two separate theories, one near the tip of the corner and another one at the conical exit to infinity. However, concerning the conical exit to infinity, we establish here a new concrete calculus of edge-degenerate operators which can be iterated to higher singularities.
A central insight from psychological studies on human eye movements is that eye movement patterns are highly individually characteristic. They can, therefore, be used as a biometric feature, that is, subjects can be identified based on their eye movements. This thesis introduces new machine learning methods to identify subjects based on their eye movements while viewing arbitrary content. The thesis focuses on probabilistic modeling of the problem, which has yielded the best results in the most recent literature. The thesis studies the problem in three phases by proposing a purely probabilistic, probabilistic deep learning, and probabilistic deep metric learning approach. In the first phase, the thesis studies models that rely on psychological concepts about eye movements. Recent literature illustrates that individual-specific distributions of gaze patterns can be used to accurately identify individuals. In these studies, models were based on a simple parametric family of distributions. Such simple parametric models can be robustly estimated from sparse data, but have limited flexibility to capture the differences between individuals. Therefore, this thesis proposes a semiparametric model of gaze patterns that is flexible yet robust for individual identification. These patterns can be understood as domain knowledge derived from psychological literature. Fixations and saccades are examples of simple gaze patterns. The proposed semiparametric densities are drawn under a Gaussian process prior centered at a simple parametric distribution. Thus, the model will stay close to the parametric class of densities if little data is available, but it can also deviate from this class if enough data is available, increasing the flexibility of the model. The proposed method is evaluated on a large-scale dataset, showing significant improvements over the state-of-the-art. Later, the thesis replaces the model based on gaze patterns derived from psychological concepts with a deep neural network that can learn more informative and complex patterns from raw eye movement data. As previous work has shown that the distribution of these patterns across a sequence is informative, a novel statistical aggregation layer called the quantile layer is introduced. It explicitly fits the distribution of deep patterns learned directly from the raw eye movement data. The proposed deep learning approach is end-to-end learnable, such that the deep model learns to extract informative, short local patterns while the quantile layer learns to approximate the distributions of these patterns. Quantile layers are a generic approach that can converge to standard pooling layers or have a more detailed description of the features being pooled, depending on the problem. The proposed model is evaluated in a large-scale study using the eye movements of subjects viewing arbitrary visual input. The model improves upon the standard pooling layers and other statistical aggregation layers proposed in the literature. It also improves upon the state-of-the-art eye movement biometrics by a wide margin. Finally, for the model to identify any subject — not just the set of subjects it is trained on — a metric learning approach is developed. Metric learning learns a distance function over instances. The metric learning model maps the instances into a metric space, where sequences of the same individual are close, and sequences of different individuals are further apart. This thesis introduces a deep metric learning approach with distributional embeddings. The approach represents sequences as a set of continuous distributions in a metric space; to achieve this, a new loss function based on Wasserstein distances is introduced. The proposed method is evaluated on multiple domains besides eye movement biometrics. This approach outperforms the state of the art in deep metric learning in several domains while also outperforming the state of the art in eye movement biometrics.
Lamprophyre sind porphyrische, aus Mantelschmelzen gebildete Gesteine, die meist in Form von Gängen auftreten. Sie zeichnen sich durch auffällige und charakteristische texturelle, chemische und mineralogische Eigenschaften aus. Als ehemalige Mantelschmelzen liefern sie Information sowohl über Bedingungen der Schmelzbildung im Mantel als auch über geodynamische Prozesse, die zu metasomatischer Veränderung des Mantels geführt haben. Im Saxothuringikum Mitteleuropas, am Nordrand des Böhmischen Massivs, gibt es zahlreiche Lamprophyrvorkommen, die hier zur Charakterisierung der Mantelentwicklung während der variszischen Orogenese dienen. Die vorliegende Arbeit befaßt sich mit den mineralogischen, geochemischen und isotopischen (Sr-Nd-Pb) Signaturen von spätvariszischen kalkalkalischen Lamprophyren, von postvariszischen ultramafischen Lamprophyren, von Alkalibasalten der Lausitz und, zum Vergleich, von prävariszischen Gabbros. Darüberhinaus nutzt die Arbeit Lithium-Isotopensignaturen kombiniert mit Sr-Nd-Pb–Isotopendaten spätvariszischer kalkalkalischer Lamprophyre aus drei variszischen Domänen (Erzgebirge, Lausitz, Sudeten) zur Erkundung der lokalen Mantelüberprägungen während der variszischen Orogenese.