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Jonas Latz

3 papers here

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

author position
  • sole author1
  • first author1
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • math.NA2
  • stat.CO1
ORCID 0000-0002-4600-0247

identity via Semantic Scholar / OpenAlex

most citedCan Physics-Informed Neural Networks beat the Finite Element Method?

11 citations · 11 across the 3 of their papers we have counts for

collaborators

3 papers

math.NA2024

The random timestep Euler method and its continuous dynamics

Jonas Latz

ODE solvers with randomly sampled timestep sizes appear in the context of chaotic dynamical systems, differential equations with low regularity, and, implicitly, in stochastic opti…

stat.CO2023

Nested Sampling for Uncertainty Quantification and Rare Event Estimation

Jonas Latz, Doris Schneider, Philipp Wacker

Nested Sampling is a method for computing the Bayesian evidence, also called the marginal likelihood, which is the integral of the likelihood with respect to the prior. More genera…

math.NA2023★ 11 cited

Can Physics-Informed Neural Networks beat the Finite Element Method?

Tamara G. Grossmann, Urszula Julia Komorowska, Jonas Latz +1

Partial differential equations play a fundamental role in the mathematical modelling of many processes and systems in physical, biological and other sciences. To simulate such proc…

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