Lederer, Johannes
- AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2
2024/05/23 by Simon Damm, Damm, Simon, Mike Laszkiewicz +5 · 10 citations
Computer Science · Medicine · #Anomaly Detection Techniques and Applications #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
- The Bernstein-Orlicz norm and deviation inequalities
2011/11/10 by van de Geer, Sara, Lederer, Johannes · 2 citations
#60E15 #60F10 #FOS: Mathematics #Probability (math.PR)
- Activation Functions in Artificial Neural Networks: A Systematic Overview
2021/01/25 by Lederer, Johannes · 2 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
- How many samples are needed to train a deep neural network?
2024/05/26 by Pegah Golestaneh, Golestaneh, Pegah, Mahsa Taheri +3 · 3 citations
Computer Science · #Neural Networks and Applications
- Extremes in High Dimensions: Methods and Scalable Algorithms
2023/03/07 by Johannes Lederer, Lederer, Johannes, Marco Oesting +1 · 2 citations
Economics, Econometrics and Finance · Mathematics · Environmental Science · #Financial Risk and Volatility Modeling #Statistical Methods and Inference #Hydrology and Drought Analysis
- Oracle Inequalities for High-dimensional Prediction
2016/08/01 by Lederer, Johannes, Yu, Lu, Gaynanova, Irina · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- Is there a role for statistics in artificial intelligence?
2020/09/13 by Friedrich, Sarah, Antes, Gerd, Behr, Sigrid +11 · 1 citation
#Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Statistical Guarantees for Regularized Neural Networks
2020/05/30 by Taheri, Mahsa, Xie, Fang, Lederer, Johannes · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Neural and Evolutionary Computing (cs.NE) #Statistics Theory (math.ST)
- Single-Model Attribution of Generative Models Through Final-Layer Inversion
2023/05/26 by Mike Laszkiewicz, Laszkiewicz, Mike, Jonas Ricker +5 · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG)
- Regularization and Reparameterization Avoid Vanishing Gradients in Sigmoid-Type Networks
2021/06/04 by Ven, Leni, Lederer, Johannes · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Marginal Tail-Adaptive Normalizing Flows
2022/06/21 by Laszkiewicz, Mike, Lederer, Johannes, Fischer, Asja · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)