Schmidt-Hieber, Johannes

7 publications

NeurIPS 2025 On the VC Dimension of Deep Group Convolutional Neural Networks Anna Sepliarskaia, Sophie Langer, Johannes Schmidt-Hieber

NeurIPS 2025 Spike-Timing-Dependent Hebbian Learning as Noisy Gradient Descent Niklas Dexheimer, Sascha Gaudlitz, Johannes Schmidt-Hieber

NeurIPS 2025 Statistical Guarantees for High-Dimensional Stochastic Gradient Descent Jiaqi Li, Zhipeng Lou, Johannes Schmidt-Hieber, Wei Biao Wu

AISTATS 2025 Understanding the Effect of GCN Convolutions in Regression Tasks Juntong Chen, Johannes Schmidt-Hieber, Claire Donnat, Olga Klopp

JMLR 2024 Dropout Regularization Versus L2-Penalization in the Linear Model Gabriel Clara, Sophie Langer, Johannes Schmidt-Hieber

JMLR 2023 Posterior Contraction for Deep Gaussian Process Priors Gianluca Finocchio, Johannes Schmidt-Hieber

NeurIPS 2022 On the Inability of Gaussian Process Regression to Optimally Learn Compositional Functions Matteo Giordano, Kolyan Ray, Johannes Schmidt-Hieber