Suivre
Moritz Knolle
Moritz Knolle
Technical University of Munich, Institute for Ai in Medicine & Healthcare
Adresse e-mail validée de tum.de
Titre
Citée par
Citée par
Année
Tumor-derived prostaglandin E2 programs cDC1 dysfunction to impair intratumoral orchestration of anti-cancer T cell responses
F Bayerl, P Meiser, S Donakonda, A Hirschberger, SB Lacher, AM Pedde, ...
Immunity 56 (6), 1341-1358. e11, 2023
312023
A distinct stimulatory cDC1 subpopulation amplifies CD8+ T cell responses in tumors for protective anti-cancer immunity
P Meiser, MA Knolle, A Hirschberger, GP de Almeida, F Bayerl, S Lacher, ...
Cancer Cell 41 (8), 1498-1515. e10, 2023
202023
Differentially private federated deep learning for multi-site medical image segmentation
A Ziller, D Usynin, N Remerscheid, M Knolle, M Makowski, R Braren, ...
arXiv preprint arXiv:2107.02586, 2021
142021
Efficient, high-performance semantic segmentation using multi-scale feature extraction
M Knolle, G Kaissis, F Jungmann, S Ziegelmayer, D Sasse, M Makowski, ...
Plos one 16 (8), e0255397, 2021
102021
Complex-valued deep learning with differential privacy
A Ziller, D Usynin, M Knolle, K Hammernik, D Rueckert, G Kaissis
arXiv preprint arXiv:2110.03478, 2021
72021
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index
G Kaissis, M Knolle, F Jungmann, A Ziller, D Usynin, D Rueckert
Journal of Privacy and Confidentiality, 2021
62021
Partial sensitivity analysis in differential privacy
TT Mueller, A Ziller, D Usynin, M Knolle, F Jungmann, D Rueckert, ...
arXiv preprint arXiv:2109.10582, 2021
32021
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation
A Ziller, D Usynin, M Knolle, K Prakash, A Trask, R Braren, M Makowski, ...
arXiv preprint arXiv:2107.04265, 2021
32021
How Do Input Attributes Impact the Privacy Loss in Differential Privacy?
TT Mueller, S Kolek, F Jungmann, A Ziller, D Usynin, M Knolle, ...
arXiv preprint arXiv:2211.10173, 2022
22022
An automatic differentiation system for the age of differential privacy
D Usynin, A Ziller, M Knolle, A Trask, K Prakash, D Rueckert, G Kaissis
arXiv preprint arXiv:2109.10573, 2021
22021
Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty
M Knolle, A Ziller, D Usynin, R Braren, MR Makowski, D Rueckert, ...
arXiv preprint arXiv:2107.04296, 2021
22021
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD
M Knolle, R Dorfman, A Ziller, D Rueckert, G Kaissis
arXiv preprint arXiv:2308.12018, 2023
12023
(Predictable) performance bias in unsupervised anomaly detection
F Meissen, S Breuer, M Knolle, A Buyx, R Müller, G Kaissis, B Wiestler, ...
EBioMedicine 101, 2024
2024
SoK: Memorisation in machine learning
D Usynin, M Knolle, G Kaissis
arXiv preprint arXiv:2311.03075, 2023
2023
AI and Big Data in Cardiology: A Practical Guide (Diagnosis Chapter)
D Rueckert, M Knolle, N Duchateau, R Razavi, G Kaissis
Springer Nature, 2023
2023
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–15