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2019


Fast and Resource-Efficient Control of Wireless Cyber-Physical Systems
Fast and Resource-Efficient Control of Wireless Cyber-Physical Systems

Baumann, D.

KTH Royal Institute of Technology, Stockholm, Febuary 2019 (phdthesis)

ics

PDF [BibTex]

2019


PDF [BibTex]


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Ferromagnetic colloids in liquid crystal solvents

Zarubin, G.

Universität Stuttgart, Stuttgart, 2019 (phdthesis)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Fluctuating interface with a pinning potential

Pranjić, Daniel

Universität Stuttgart, Stuttgart, 2019 (mastersthesis)

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[BibTex]

[BibTex]


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Controlling pattern formation in the confined Schnakenberg model

Beyer, David Bernhard

Universität Stuttgart, Stuttgart, 2019 (mastersthesis)

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[BibTex]

[BibTex]


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Interfaces in fluids of ionic liquid crystals

Bartsch, H.

Universität Stuttgart, Stuttgart, 2019 (phdthesis)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Special issue on transport in narrow channels
Journal of Physics: Condensed Matter, 31, IOP Publishing, Bristol, 2019 (misc)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Actively Learning Dynamical Systems with Gaussian Processes

Buisson-Fenet, M.

Mines ParisTech, PSL University, 2019 (mastersthesis)

Abstract
Predicting the behavior of complex systems is of great importance in many fields such as engineering, economics or meteorology. The evolution of such systems often follows a certain structure, which can be induced, for example from the laws of physics or of market forces. Mathematically, this structure is often captured by differential equations. The internal functional dependencies, however, are usually unknown. Hence, using machine learning approaches that recreate this structure directly from data is a promising alternative to designing physics-based models. In particular, for high dimensional systems with nonlinear effects, this can be a challenging task. Learning dynamical systems is different from the classical machine learning tasks, such as image processing, and necessitates different tools. Indeed, dynamical systems can be actuated, often by applying torques or voltages. Hence, the user has a power of decision over the system, and can drive it to certain states by going through the dynamics. Actuating this system generates data, from which a machine learning model of the dynamics can be trained. However, gathering informative data that is representative of the whole state space remains a challenging task. The question of active learning then becomes important: which control inputs should be chosen by the user so that the data generated during an experiment is informative, and enables efficient training of the dynamics model? In this context, Gaussian processes can be a useful framework for approximating system dynamics. Indeed, they perform well on small and medium sized data sets, as opposed to most other machine learning frameworks. This is particularly important considering data is often costly to generate and process, most of all when producing it involves actuating a complex physical system. Gaussian processes also yield a notion of uncertainty, which indicates how sure the model is about its predictions. In this work, we investigate in a principled way how to actively learn dynamical systems, by selecting control inputs that generate informative data. We model the system dynamics by a Gaussian process, and use information-theoretic criteria to identify control trajectories that maximize the information gain. Thus, the input space can be explored efficiently, leading to a data-efficient training of the model. We propose several methods, investigate their theoretical properties and compare them extensively in a numerical benchmark. The final method proves to be efficient at generating informative data. Thus, it yields the lowest prediction error with the same amount of samples on most benchmark systems. We propose several variants of this method, allowing the user to trade off computations with prediction accuracy, and show it is versatile enough to take additional objectives into account.

ics

[BibTex]

[BibTex]

2017


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Stationary and time-dependent heat transfer in paradigmatic many-body geometries

Asheichyk, Kiryl

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

2017


[BibTex]


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Non-equilibrium forces after temperature quenches in ideal fluids with conserved density

Hölzl, Christian

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Numerical studies of active colloids at fluid interfaces

Peter, Toni

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Collective dynamics of laterally confined active particles near fluid-fluid interfaces

Kistner, Irina

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Self-diffusion of DNA grafted functional colloids in a crowded environment

Werner, M.

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Electrostatic interaction between non-identical charged particles at an electrolyte interface

Schmetzer, Timo

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


Evaluation of the passive dynamics of compliant legs with inertia
Evaluation of the passive dynamics of compliant legs with inertia

Györfi, B.

University of Applied Science Pforzheim, Germany, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Microscopic investigation of the Marangoni effect

Pöhnl, Matthias

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Interfacial structure of a catalytic surface

Lipp, Melanie

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

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[BibTex]

[BibTex]

2012


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Nanodroplets at topographic steps

Bartsch, H.

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

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[BibTex]

[BibTex]


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Janus particles in critical liquids

Labbe-Laurent, M.

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

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[BibTex]

[BibTex]


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Phase equilibria of binary liquid crystals

Klöss, Hans-Christian

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

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[BibTex]

[BibTex]


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Pinning of drops at superhydrophobic surfaces

Daschke, Lena

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

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[BibTex]

[BibTex]


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Impedance spectroscopy of ions at interfaces

Reindl, A.

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

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[BibTex]

[BibTex]


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Surface of an evaporating liquid

Arnold, Daniel

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

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[BibTex]

[BibTex]


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Statics and dynamics of critical Casimir forces

Tröndle, M.

Universität Stuttgart, Stuttgart, 2012 (phdthesis)

icm

link (url) [BibTex]

link (url) [BibTex]


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Critical Casimir forces beyond the Derjaguin approximation

Brunner, Niklas

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

icm

[BibTex]

[BibTex]


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Crystallization of flexible molecules

Held, Felix

Universität Stuttgart, Stuttgart, 2012 (mastersthesis)

icm

[BibTex]

[BibTex]