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Mathias Niepert

57 papers hereh-index 357.4k citations121 works total

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

author position
  • sole author6
  • first author5
  • middle author14
  • last author28

Across the 53 of 57 papers where every author was matched, so the position is known.

fields
  • cs.LG25
  • cs.AI16
  • cs.CL4
  • cs.CV3
  • cs.IR3
  • cs.DC2
same name
  • Mathias Niepert — 26 papers, h 8
  • Mathias Niepert — 26 papers, h 8
  • Mathias Niepert — 2 papers, h 2

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
20082026
most citedLearning Convolutional Neural Networks for Graphs

808 citations · 1.4k across the 52 of their papers we have counts for

collaborators
Showing 2014 · cs.AIShow all

4 papers · 2 filters

cs.AI2014

Lifted Probabilistic Inference for Asymmetric Graphical Models

Guy Van den Broeck, Mathias Niepert

Lifted probabilistic inference algorithms have been successfully applied to a large number of symmetric graphical models. Unfortunately, the majority of real-world graphical models…

cs.AI2014

Markov Chains on Orbits of Permutation Groups

Mathias Niepert

We present a novel approach to detecting and utilizing symmetries in probabilistic graphical models with two main contributions. First, we present a scalable approach to computing…

cs.AI2014★ 9 cited

On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach

Mathias Niepert, Dirk Van Gucht, Marc Gyssens

A lattice-theoretic framework is introduced that permits the study of the conditional independence (CI) implication problem relative to the class of discrete probability measures.…

cs.AI2014★ 12 cited

Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference

Mathias Niepert, Guy Van den Broeck

Exchangeability is a central notion in statistics and probability theory. The assumption that an infinite sequence of data points is exchangeable is at the core of Bayesian statist…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.