![](https://dblp.org/img/logo.ua.320x120.png)
![](https://dblp.org/img/dropdown.dark.16x16.png)
![](https://dblp.org/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.org/img/search.dark.16x16.png)
![search dblp](https://dblp.org/img/search.dark.16x16.png)
default search action
Dmitrii Usynin
Person information
Refine list
![note](https://dblp.org/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c3]Dmitrii Usynin
, Daniel Rueckert
, Georgios Kaissis
:
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training. EICC 2024: 179-185 - [i19]Jack K. Fitzsimons, Agustín Freitas Pasqualini, Robert Pisarczyk, Dmitrii Usynin:
Naturally Private Recommendations with Determinantal Point Processes. CoRR abs/2405.13677 (2024) - [i18]Felix Hsieh, Huy H. Nguyen, AprilPyone MaungMaung, Dmitrii Usynin, Isao Echizen:
Mitigating Backdoor Attacks using Activation-Guided Model Editing. CoRR abs/2407.07662 (2024) - 2023
- [j6]Tamara T. Mueller
, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert
, Georgios Kaissis
:
Differentially Private Graph Neural Networks for Whole-Graph Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7308-7318 (2023) - [j5]Dmitrii Usynin
, Daniel Rueckert
, Georgios Kaissis
:
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks. ACM Trans. Priv. Secur. 26(3): 38:1-38:30 (2023) - [c2]Tomás Chobola
, Dmitrii Usynin
, Georgios Kaissis
:
Membership Inference Attacks Against Semantic Segmentation Models. AISec@CCS 2023: 43-53 - [i17]Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Leveraging gradient-derived metrics for data selection and valuation in differentially private training. CoRR abs/2305.02942 (2023) - [i16]Dmitrii Usynin, Moritz Knolle, Georgios Kaissis:
SoK: Memorisation in machine learning. CoRR abs/2311.03075 (2023) - 2022
- [j4]Georgios Kaissis
, Moritz Knolle
, Friederike Jungmann
, Alexander Ziller
, Dmitrii Usynin
, Daniel Rueckert
:
Unified Interpretation of the Gaussian Mechanism for Differential Privacy Through the Sensitivity Index. J. Priv. Confidentiality 12(1) (2022) - [j3]Dmitrii Usynin, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis:
Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning. Proc. Priv. Enhancing Technol. 2022(1): 274-290 (2022) - [c1]Dmitrii Usynin, Helena Klause, Johannes C. Paetzold, Daniel Rueckert, Georgios Kaissis:
Can Collaborative Learning Be Private, Robust and Scalable? DeCaF/FAIR@MICCAI 2022: 37-46 - [i15]Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Differentially Private Graph Classification with GNNs. CoRR abs/2202.02575 (2022) - [i14]Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis:
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks. CoRR abs/2203.00481 (2022) - [i13]Tamara T. Mueller, Dmitrii Usynin, Johannes C. Paetzold, Daniel Rueckert, Georgios Kaissis:
SoK: Differential Privacy on Graph-Structured Data. CoRR abs/2203.09205 (2022) - [i12]Dmitrii Usynin, Helena Klause, Daniel Rueckert, Georgios Kaissis:
Can collaborative learning be private, robust and scalable? CoRR abs/2205.02652 (2022) - [i11]Tamara T. Mueller, Stefan Kolek, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Daniel Rueckert, Georgios Kaissis:
How Do Input Attributes Impact the Privacy Loss in Differential Privacy? CoRR abs/2211.10173 (2022) - [i10]Tomás Chobola, Dmitrii Usynin, Georgios Kaissis:
Membership Inference Attacks Against Semantic Segmentation Models. CoRR abs/2212.01082 (2022) - 2021
- [j2]Georgios Kaissis
, Alexander Ziller
, Jonathan Passerat-Palmbach
, Théo Ryffel
, Dmitrii Usynin
, Andrew Trask, Ionésio Lima, Jason Mancuso, Friederike Jungmann
, Marc-Matthias Steinborn
, Andreas Saleh, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren
:
End-to-end privacy preserving deep learning on multi-institutional medical imaging. Nat. Mach. Intell. 3(6): 473-484 (2021) - [j1]Dmitrii Usynin
, Alexander Ziller
, Marcus R. Makowski, Rickmer Braren
, Daniel Rueckert, Ben Glocker
, Georgios Kaissis
, Jonathan Passerat-Palmbach
:
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning. Nat. Mach. Intell. 3(9): 749-758 (2021) - [e1]Cristina Oyarzun Laura, M. Jorge Cardoso
, Michal Rosen-Zvi
, Georgios Kaissis
, Marius George Linguraru, Raj Shekhar, Stefan Wesarg, Marius Erdt, Klaus Drechsler, Yufei Chen, Shadi Albarqouni
, Spyridon Bakas
, Bennett A. Landman
, Nicola Rieke
, Holger Roth
, Xiaoxiao Li
, Daguang Xu
, Maria Gabrani, Ender Konukoglu, Michal Guindy, Daniel Rueckert, Alexander Ziller, Dmitrii Usynin, Jonathan Passerat-Palmbach:
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning - 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings. Lecture Notes in Computer Science 12969, Springer 2021, ISBN 978-3-030-90873-7 [contents] - [i9]Alexander Ziller, Dmitrii Usynin
, Nicolas Remerscheid, Moritz Knolle, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Differentially private federated deep learning for multi-site medical image segmentation. CoRR abs/2107.02586 (2021) - [i8]Alexander Ziller, Dmitrii Usynin
, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis:
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. CoRR abs/2107.04265 (2021) - [i7]Moritz Knolle, Alexander Ziller, Dmitrii Usynin
, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis:
Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty. CoRR abs/2107.04296 (2021) - [i6]Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin
, Daniel Rueckert:
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index. CoRR abs/2109.10528 (2021) - [i5]Dmitrii Usynin
, Alexander Ziller, Moritz Knolle, Daniel Rueckert, Georgios Kaissis:
An automatic differentiation system for the age of differential privacy. CoRR abs/2109.10573 (2021) - [i4]Tamara T. Mueller, Alexander Ziller, Dmitrii Usynin
, Moritz Knolle, Friederike Jungmann, Daniel Rueckert, Georgios Kaissis:
Partial sensitivity analysis in differential privacy. CoRR abs/2109.10582 (2021) - [i3]Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kerstin Hammernik, Daniel Rueckert, Georgios Kaissis:
Complex-valued deep learning with differential privacy. CoRR abs/2110.03478 (2021) - [i2]Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis:
Distributed Machine Learning and the Semblance of Trust. CoRR abs/2112.11040 (2021) - 2020
- [i1]Alexander Ziller
, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin
, Andrew Trask, Ionésio Da Lima Costa Junior, Jason Mancuso, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren, Georgios Kaissis:
Privacy-preserving medical image analysis. CoRR abs/2012.06354 (2020)
Coauthor Index
![](https://dblp.org/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-21 20:26 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint