Julius Berner
Julius Berner
Faculty of Mathematics, University of Vienna
Verified email at univie.ac.at - Homepage
Cited by
Cited by
Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of …
J Berner, P Grohs, A Jentzen
SIAM Journal on Mathematics of Data Science 2 (3), 631-657, 2020
How degenerate is the parametrization of neural networks with the ReLU activation function?
DM Elbrächter, J Berner, P Grohs
Advances in Neural Information Processing Systems, 7790-7801, 2019
Group testing for SARS-CoV-2 allows for up to 10-fold efficiency increase across realistic scenarios and testing strategies
CM Verdun, T Fuchs, P Harar, D Elbrächter, DS Fischer, J Berner, ...
medRxiv, 2020
Towards a regularity theory for ReLU networks–chain rule and global error estimates
J Berner, D Elbrächter, P Grohs, A Jentzen
2019 13th International conference on Sampling Theory and Applications …, 2019
Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning
J Berner, M Dablander, P Grohs
Advances in Neural Information Processing Systems 33, 2020
The system can't perform the operation now. Try again later.
Articles 1–5