@conference {722,
	title = {Coarse-Graining Large Search Landscapes using Massive Edge Collapse},
	booktitle = {Topology-Based Methods in Visualization 2017},
	year = {2017},
	author = {Sebastian Volke and Martin Middendorf and Gerik Scheuermann}
}
@inbook {703,
	title = {Comparing Finite-Time Lyapunov Exponents in Approximated Vector Fields},
	booktitle = {Topological Methods in Data Analysis and Visualization IV: Theory, Algorithms, and Applications},
	year = {2017},
	pages = {267-281},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	issn = {978-3-319-44684-4},
	doi = {10.1007/978-3-319-44684-4_16},
	author = {Stefan Koch and Sebastian Volke and Gerik Scheuermann and Hans Hagen and Mario Hlawitschka}
}
@inbook {702,
	title = {Visualizing Topological Properties of the Search Landscape of Combinatorial Optimization Problems},
	booktitle = {Topological Methods in Data Analysis and Visualization IV: Theory, Algorithms, and Applications},
	year = {2017},
	month = {04/2017},
	pages = {69-85},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	isbn = {ISBN 978-3-319-44684-4},
	doi = {10.1007/978-3-319-44684-4_4},
	author = {Sebastian Volke and Dirk Zeckzer and Martin Middendorf and Gerik Scheuermann}
}
@conference {692,
	title = {Identifying Linear Vector Fields on 2D Manifolds},
	booktitle = {WSCG},
	year = {2016},
	abstract = {Local linearity of vector fields is a property that is well researched and understood. Linear approximation can be
used to simplify algorithms or for data reduction. Whereas the concept is easy to implement in 2D and 3D, it
loses meaning on manifolds as linearity has either to be defined based on an embedding in a higher-dimensional
Cartesian space or on a map. We present an adaptive atlas-based vector field decomposition to solve the problem
on manifolds and present its application on synthetic and climate data.},
	author = {Sebastian Volke and Stefan Koch and Mario Hlawitschka}
}
@conference {693,
	title = {Measuring Event Probabilities in Uncertain Scalar Datasets using Gaussian Processes},
	booktitle = {WSCG},
	year = {2016},
	abstract = {In this paper, we show how the concept of Gaussian process regression can be used to determine potential events in
scalar data sets. As a showcase, we will investigate climate data sets in order to identify potential extrem weather
events by deriving the probabilities of their appearances. The method is implemented directly on the GPU to ensure
interactive frame rates and pixel precise visualizations. We will see, that this approach is especially well suited for
sparse sampled data because of its reconstruction properties.},
	author = {Steven Schlegel and Sebastian Volke and Gerik Scheuermann}
}
@proceedings {650,
	title = {A Visual Method for Analysis and Comparison of Search Landscapes},
	year = {2015},
	month = {07/2015},
	pages = {497--504},
	publisher = {ACM},
	address = {Madrid, Spain},
	doi = {10.1145/2739480.2754733},
	author = {Sebastian Volke and Dirk Zeckzer and Gerik Scheuermann and Martin Middendorf}
}
@inbook {621,
	title = {Comparing the Optimization Behaviour of Heuristics with Topology Based Visualization},
	booktitle = {Theory and Practice of Natural Computing},
	series = {Lecture Notes in Computer Science},
	volume = {8890},
	year = {2014},
	pages = {47-58},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	keywords = {visualization; fitness landscape; combinatorial optimization problem; barrier landscape; heuristic; optimization behaviour},
	issn = {978-3-319-13748-3},
	doi = {10.1007/978-3-319-13749-0_5},
	url = {http://dx.doi.org/10.1007/978-3-319-13749-0_5},
	author = {Simon Bin and Sebastian Volke and Gerik Scheuermann and Martin Middendorf}
}
@inbook {553,
	title = {Visual Analysis of Discrete Particle Swarm Optimization Using Fitness 	Landscapes},
	booktitle = {Recent Advances in the Theory and Application of Fitness Landscapes},
	volume = {6},
	number = {Emergence, Complexity and Computation},
	year = {2014},
	pages = {487 - 507},
	publisher = {Springer},
	organization = {Springer},
	edition = {Hendrik Richter and Andries Engelbrecht},
	address = {Berlin, Heidelberg},
	issn = {978-3-642-41887-7},
	doi = {10.1007/978-3-642-41888-4_17},
	url = {http://dx.doi.org/10.1007/978-3-642-41888-4_17},
	author = {Sebastian Volke and Simon Bin and Dirk Zeckzer and Martin Middendorf and Gerik Scheuermann}
}
@article {527,
	title = {dPSO-Vis: Topology-based Visualization of Discrete Particle Swarm Optimization},
	journal = {Computer Graphics Forum},
	volume = {32},
	year = {2013},
	pages = {351-360},
	abstract = {Particle swarm optimization (PSO) is a metaheuristic that has been applied successfully to many continuous and combinatorial optimization problems, e.g., in the fields of economics, engineering, and natural sciences. In PSO a swarm of particles moves within a search space in order to find an optimal solution. Unfortunately, it is hard to understand in detail why and how changes in the design of PSO algorithms affect the optimization behavior. Visualizing the particle states could provide substantially better insight into PSO algorithms, but in case of combinatorial optimization problems, it raises the problem of illustrating the discrete states that cannot easily be embedded spatially. We propose a visualization approach to analyze the optimization problem topologically using a landscape metaphor. Therefore, we transform the configuration space of the optimization problem into a barrier landscape that is topologically equivalent. This visualization is augmented by an illustration of the time-dependent states of the particles. The user of our tool {\textemdash} called dPSO-Vis {\textemdash} is able to analyze the swarm{\textquoteright}s behavior within the search space. We illustrate our approach with a brief analysis of a PSO algorithm that predicts the secondary structure of RNA molecules.},
	author = {Sebastian Volke and Martin Middendorf and Mario Hlawitschka and Jens Kasten and Dirk Zeckzer and Gerik Scheuermann}
}
