Julian Pfeifle

dblp:45/2708 · DBLP profile ↗
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5ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0001-9777-2602ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 3 · 1 since 2021Databases, data management, data science and information retrieval · 2Graphics, computer vision, multimedia, augmented reality and games · 1
YearPublicationVenuePosition
2023 Generalised cone complexes and tropical moduli in polymake
abstract
We investigate geometric embeddings among several classes of generalised cone complexes and algorithms, e.g., to compute their homology. Interesting cases arise from moduli spaces of tropical curves. Specifically, via an explicit computation, we show that the tropical honeycomb curves form a contractible sub-locus in the moduli of all tropical K4-curves.
Dominic Bunnett, Michael Joswig, Julian Pfeifle
ISSAC3
2011 Prodsimplicial-Neighborly Polytopes
Benjamin Matschke, Julian Pfeifle, Vincent Pilaud
Discret. Comput. Geom.2
2011 Root Polytopes and Growth Series of Root Lattices
abstract
The convex hull of the roots of a classical root lattice is called a root polytope. We determine explicit unimodular triangulations of the boundaries of the root polytopes associated to the root lattices $A_n$, $C_n$, and $D_n$, and we compute their f- and h-vectors. This leads us to recover formulae for the growth series of these root lattices, which were first conjectured by Conway, Mallows, and Sloane and Baake and Grimm and were proved by Conway and Sloane and Bacher, de la Harpe, and Venkov. We also prove the formula for the growth series of the root lattice $B_n$, which requires a modification of our technique.
Federico Ardila, Matthias Beck, Serkan Hosten, Julian Pfeifle, Kim Seashore
SIAM J. Discret. Math.4
2010 Overlapping Community Search for social networks
abstract
Finding decompositions of a graph into a family of clusters is crucial to understanding its underlying structure. While most existing approaches focus on partitioning the nodes, real-world datasets suggest the presence of overlapping communities. We present OCA, a novel algorithm to detect overlapped communities in large data graphs. It outperforms previous proposals in terms of execution time, and efficiently handles large graphs containing more than 108nodes and edges.
Arnau Padrol, Guillem Perarnau, Julian Pfeifle, Victor Muntés-Mulero
ICDE3
2008 The rotation graph of k
Clemens Huemer, Ferran Hurtado, Julian Pfeifle
Inf. Process. Lett.3