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M. Huber

5 papers hereh-index 13 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cond-mat.mtrl-sci1
  • cs.LG1
  • math.AT1
same name
  • M. Huber — 50 papers, h 55
  • M. Huber — 38 papers, h 43
  • M. Huber — 31 papers, h 57
  • M. Huber — 29 papers, h 6
  • M. Huber — 18 papers, h 20
  • M. Huber — 16 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

5 papers

cs.CL2026

Exploring Dowker Homology for Sentence Similarity

Marius Huber, Juri Opitz

Dowker homology is a topological tool that may be used to analyze the relative position of two point clouds living in a common space. We investigate whether Dowker homology capture…

cs.CL2026

Fixation Sequences as Time Series: A Topological Approach to Dyslexia Detection

Marius Huber, David R. Reich, Lena A. Jäger

Persistent homology, a method from topological data analysis, extracts robust, multi-scale features from data. It produces stable representations of time series by applying varying…

cond-mat.mtrl-sci2026

Sign-resolved nanoscale readout and control of hidden antiferromagnetic spin order

A. Schmid, D. Siebenkotten, D. Dai +16

Antiferromagnetic memories promise ultrafast, stray-field-free information storage. Yet perfect magnetic compensation conceals the information carrier itself: the sign of the Néel…

math.AT2025

Flagifying the Dowker Complex

Marius Huber, Patrick Schnider

The Dowker complex DR​(X,Y) is a simplicial complex capturing the topological interplay between two finite sets X and Y under some relation R⊆X×Y.…

cs.LG2024

AuToMATo: An Out-Of-The-Box Persistence-Based Clustering Algorithm

Marius Huber, Sara Kalisnik, Patrick Schnider

We present AuToMATo, a novel clustering algorithm based on persistent homology. While AuToMATo is not parameter-free per se, we provide default choices for its parameters that make…

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