Springe direkt zu Inhalt

Dr. Hannes Stuke

Department of Mathematics and Computer Science, Institute of Mathematics

Group Nonlinear Dynamics

Group Mathematics of Machine Learning

Principal Investigator

Arnimallee 7, rear building
14195 Berlin
Hannes currently works on predictive models and large language models at Wand AI

Research interests

  • Machine learning
  • Dynamical Systems
  • Blow-Up of Evolutionary PDEs
  • Bianchi Cosmological Models
  • Dynamical systems
  • Applications to biology
  • Applications to medicine

Current Projects

Recent Projects

Gurevich P., Stuke H.
Robustness Against Outliers For Deep Neural Networks By Gradient Conjugate Priors
Preprint:  arXiv:1905.08464 [stat.ML]

Stuke H.
Complex time blow-up of the nonlinear heat equation
Preprint arXiv:1812.10707 [math.DS]

Gurevich P., Stuke H. 
Gradient conjugate priors and deep neural networks.
J. Artificial Intelligence 10.1016/j.artint.2019.103184   

Gurevich P., Stuke H.
Pairing an arbitrary regressor with an artificial neural network estimating aleatoric uncertainty.

Neurocomputing. 10.1016/j.neucom.2019.03.031

Gurevich P., Stuke H., Kastrup A., Stuke H. and Hildebrandt H. 
Neuropsychological testing and machine learning distinguish Alzheimer's disease from other causes for cognitive impairment.
Front. Aging Neurosci. 9:114 (2017) 
Fila M., Stuke H.
Very slow stabilization for a nonlinear Fokker–Planck equation 
Nonlinear Analysis, Theory, Methods & Applications (2016)
Fila M., Stuke H. 
Special asymptotics for a critical fast diffusion equation
Discrete and Continuous Dynamical Systems (2014)
Ghoussoub's self-dual variational principle
Bachelor Thesis, Free University Berlin, 2011 
(pdf, 330 kB)