1 citations · 1 across the 17 of their papers we have counts for
19 papers
Uniqueness, analyticity and mixing for Gibbs point processes via spectral gaps
Andreas Göbel, Matthew Jenssen, Marcus Michelen +3
A Gibbs point process models particles interacting in the continuum through a potential. Among the most classical examples is the hard-sphere model, where given an activity paramet…
A simple proof of rapid mixing on random regular graphs beyond uniqueness
Andreas Göbel, Matthew Jenssen, Marcus Michelen +3
A recent breakthrough of Chen, Chen, Chen, Yin, and Zhang shows rapid mixing for Glauber dynamics for the hard-core model on random regular graphs beyond the tree uniqueness thresh…
Information-Theoretic Thresholds for Bipartite Latent-Space Graphs under Noisy Observations
Andreas Göbel, Marcus Pappik, Leon Schiller
We study information-theoretic phase transitions for the detectability of latent geometry in bipartite random geometric graphs RGGs with Gaussian d-dimensional latent vectors while…
Simple analyticity criteria for repulsive multi-body potentials
Tyler Helmuth, Marcus Pappik, Will Perkins
We prove a simple, explicit lower bound on the radius of a zero-free disk for Gibbs point processes defined by finite-range, repulsive multi-body interactions. Our lower bound impr…
Testing Thresholds and Spectral Properties of High-Dimensional Random Toroidal Graphs via Edgeworth-Style Expansions
Samuel Baguley, Andreas Göbel, Marcus Pappik +1
We study high-dimensional random geometric graphs (RGGs) of edge-density with vertices uniformly distributed on the -dimensional torus and edges inserted between sufficientl…
Gradually Declining Immunity Retains the Exponential Duration of Immunity-Free Diffusion
Andreas Göbel, Nicolas Klodt, Martin S. Krejca +1
Diffusion processes pervade numerous areas of AI, abstractly modeling the dynamics of exchanging, oftentimes volatile, information in networks. A central question is how long the i…
Perfect sampling from rapidly mixing Markov chains
Andreas Göbel, Jingcheng Liu, Pasin Manurangsi +1
We show that efficient approximate sampling algorithms, combined with a slow exponential time oracle for computing its output distribution, can be combined into constructing effici…
Uniqueness of locally stable Gibbs point processes via spatial birth-death dynamics
Samuel Baguley, Andreas Göbel, Marcus Pappik
We prove that for every locally stable and tempered pair potential with bounded range, there exists a unique infinite-volume Gibbs point process on for every act…
Fast and Slow Mixing of the Kawasaki Dynamics on Bounded-Degree Graphs
Aiya Kuchukova, Marcus Pappik, Will Perkins +1
We study the worst-case mixing time of the global Kawasaki dynamics for the fixed-magnetization Ising model on the class of graphs of maximum degree . Proving a conjecture of Ca…
From Market Saturation to Social Reinforcement: Understanding the Impact of Non-Linearity in Information Diffusion Models
Tobias Friedrich, Andreas Göbel, Nicolas Klodt +2
Diffusion of information in networks is at the core of many problems in AI. Common examples include the spread of ideas and rumors as well as marketing campaigns. Typically, inform…
Perfect Sampling for Hard Spheres from Strong Spatial Mixing
Konrad Anand, Andreas Göbel, Marcus Pappik +1
We provide a perfect sampling algorithm for the hard-sphere model on subsets of with expected running time linear in the volume under the assumption of strong spatia…
Fixed Parameter Multi-Objective Evolutionary Algorithms for the W-Separator Problem
Samuel Baguley, Tobias Friedrich, Aneta Neumann +3
Parameterized analysis provides powerful mechanisms for obtaining fine-grained insights into different types of algorithms. In this work, we combine this field with evolutionary al…
Analysis of the survival time of the SIRS process via expansion
Tobias Friedrich, Andreas Göbel, Nicolas Klodt +2
We study the SIRS process, a continuous-time Markov chain modeling the spread of infections on graphs. In this model, vertices are either susceptible, infected, or recovered. Each…
Using random graphs to sample repulsive Gibbs point processes with arbitrary-range potentials
Tobias Friedrich, Andreas Göbel, Maximilian Katzmann +2
We study computational aspects of repulsive Gibbs point processes, which are probabilistic models of interacting particles in a finite-volume region of space. We introduce an appro…
Analysis of a Gray-Box Operator for Vertex Cover
Samuel Baguley, Tobias Friedrich, Timo Kötzing +3
Combinatorial optimization problems are a prominent application area of evolutionary algorithms, where the (1+1) EA is one of the most investigated. We extend this algorithm by int…
Algorithms for hard-constraint point processes via discretization
Tobias Friedrich, Andreas Göbel, Maximilian Katzmann +2
We study algorithmic applications of a natural discretization for the hard-sphere model and the Widom-Rowlinson model in a region . These models are…
A spectral independence view on hardspheres via block dynamics
Tobias Friedrich, Andreas Göbel, Martin S. Krejca +1
The hard-sphere model is one of the most extensively studied models in statistical physics. It describes the continuous distribution of spherical particles, governed by hard-core i…
Polymer Dynamics via Cliques: New Conditions for Approximations
Tobias Friedrich, Andreas Göbel, Martin S. Krejca +1
Abstract polymer models are systems of weighted objects, called polymers, equipped with an incompatibility relation. An important quantity associated with such models is the partit…
Convergence and Hardness of Strategic Schelling Segregation
Hagen Echzell, Tobias Friedrich, Pascal Lenzner +5
The phenomenon of residential segregation was captured by Schelling's famous segregation model where two types of agents are placed on a grid and an agent is content with her locat…