Johannes Schmidt-Hieber
5 papers · 2022–2026 · 3 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓
🌍
Conference Polyglot · Bronze
🌉
Interdisciplinary Bridge · Bronze
🗺️
Taxonomy Completionist
(15)
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(5)
Optimization & Theory · Machine Learning
(4)
Core Methods
(3)
Artificial Intelligence
(2)
Deep Learning
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Bayesian & Probabilistic · Machine Learning
(2)
Optimization & Theory · Deep Learning
(2)
Mathematics & Optimization
(1)
Architectures
(1)
Learning Types
(1)
Optimization
(1)
Keywords
dropout regularization
(2)
linear regression
(2)
posterior contraction
(2)
gaussian process
(1)
gradient descent
(1)
nonparametric regression
(1)
bayesian regression
(1)
l2 regularization
(1)
online inference
(1)
gaussian process prior
(1)
minimax rate
(1)
asymptotic normality
(1)
bias-variance tradeoff
(1)
regression task
(1)
neighborhood aggregation
(1)
information-theoretic lower bound
(1)
graph convolutional network
(1)
deep gaussian process
(1)
central limit theorem
(1)
minimax convergence rate
(1)
Papers
Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models
JMLR 2026
Understanding the Effect of GCN Convolutions in Regression Tasks
AISTATS 2025
Dropout Regularization Versus l2-Penalization in the Linear Model
JMLR 2024
Posterior Contraction for Deep Gaussian Process Priors
JMLR 2023
On the inability of Gaussian process regression to optimally learn compositional functions
NeurIPS 2022