Johannes Lederer
Scholar

Johannes Lederer

Google Scholar ID: qqgDCDIAAAAJ
Professor of Data-Driven Methods, University of Hamburg
High-Dimensional StatisticsTheory of Deep LearningData ScienceArtificial Intelligence
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
1,478
 
H-index
20
 
i10-index
39
 
Publications
20
 
Co-authors
0
 
Contact
No contact links provided.
Publications
8 items
Generative Modeling under Non-Monotonic MAR Missingness via Approximate Wasserstein Gradient Flows
2026
Cited
0
Non-asymptotic error bounds for probability flow ODEs under weak log-concavity
2025
Cited
0
Adaptive tail index estimation: minimal assumptions and non-asymptotic guarantees
2025
Cited
0
Regularization can make diffusion models more efficient
2025
Cited
0
How many samples are needed to train a deep neural network?
International Conference on Learning Representations · 2024
Cited
4
AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2
arXiv.org · 2024
Cited
1
Affine Invariance in Continuous-Domain Convolutional Neural Networks
arXiv.org · 2023
Cited
1
Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks
arXiv.org · 2022
Cited
1
Resume (English only)
Co-authors
0 total
Co-authors: 0 (list not available)