Grohs, Philipp

6 publications

ICLR 2023 Learning ReLU Networks to High Uniform Accuracy Is Intractable Julius Berner, Philipp Grohs, Felix Voigtlaender

NeurIPS 2023 Variational Monte Carlo on a Budget — Fine-Tuning Pre-Trained Neural Wavefunctions Michael Scherbela, Leon Gerard, Philipp Grohs

NeurIPS 2022 Gold-Standard Solutions to the Schrödinger Equation Using Deep Learning: How Much Physics Do We Need? Leon Gerard, Michael Scherbela, Philipp Marquetand, Philipp Grohs

NeurIPS 2020 Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning Julius Berner, Markus Dablander, Philipp Grohs

NeurIPS 2019 How Degenerate Is the Parametrization of Neural Networks with the ReLU Activation Function? Dennis Maximilian Elbrächter, Julius Berner, Philipp Grohs

ICML 2016 Discrete Deep Feature Extraction: A Theory and New Architectures Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic, Philipp Grohs, Helmut Boelcskei