Georgios Kaissis

ORCID

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 119

Top Venues

CoRR

Nat. Mach. Intell.

Trans. Mach. Learn. Res.

ISBI

Publications

Alexander Ziller, Anneliese Riess, Kristian Schwethelm, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis
Bounding Reconstruction Attack Success of Adversaries Without Data Priors. CoRR (2024)
Georgios Kaissis, Stefan Kolek, Borja Balle, Jamie Hayes, Daniel Rueckert
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. CoRR (2024)
Daniel Truhn, Soroosh Tayebi Arasteh, Oliver Lester Saldanha, Gustav Müller-Franzes, Firas Khader, Philip Quirke, Nicholas P. West, Richard Gray, Gordon G. A. Hutchins, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Alexander Brobeil, Tanwei Yuan, Jenny Chang-Claude, Michael Hoffmeister, Sebastian Foersch, Tianyu Han, Sebastian Keil, Maximilian Schulze-Hagen, Peter Isfort, Philipp Bruners, Georgios Kaissis, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather
Encrypted federated learning for secure decentralized collaboration in cancer image analysis. Medical Image Anal. 92 (2024)
Richard Osuala, Daniel M. Lang, Anneliese Riess, Georgios Kaissis, Zuzanna Szafranowska, Grzegorz Skorupko, Oliver Díaz, Julia A. Schnabel, Karim Lekadir
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data. CoRR (2024)
Bogdan Kulynych, Juan Felipe Gómez, Georgios Kaissis, Flávio du Pin Calmon, Carmela Troncoso
Attack-Aware Noise Calibration for Differential Privacy. CoRR (2024)
Ioannis Lagogiannis, Felix Meissen, Georgios Kaissis, Daniel Rueckert
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art. IEEE Trans. Medical Imaging 43 (1) (2024)
Alexander H. Berger, Laurin Lux, Suprosanna Shit, Ivan Ezhov, Georgios Kaissis, Martin J. Menten, Daniel Rueckert, Johannes C. Paetzold
Cross-domain and Cross-dimension Learning for Image-to-Graph Transformers. CoRR (2024)
Philip Müller, Felix Meissen, Georgios Kaissis, Daniel Rueckert
Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI Pooling. CoRR (2024)
Philip Müller, Georgios Kaissis, Daniel Rueckert
ChEX: Interactive Localization and Region Description in Chest X-rays. CoRR (2024)
Kristian Schwethelm, Johannes Kaiser, Moritz Knolle, Daniel Rueckert, Georgios Kaissis, Alexander Ziller
Visual Privacy Auditing with Diffusion Models. CoRR (2024)
Reza Nasirigerdeh, Nader Razmi, Julia A. Schnabel, Daniel Rueckert, Georgios Kaissis
Machine Unlearning for Medical Imaging. CoRR (2024)
Deniz Daum, Richard Osuala, Anneliese Riess, Georgios Kaissis, Julia A. Schnabel, Maxime Di Folco
On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models. CoRR (2024)
Tamara T. Mueller, Sophie Starck, Alina Dima, Stephan Wunderlich, Kyriaki-Margarita Bintsi, Kamilia Zaripova, Rickmer Braren, Daniel Rueckert, Anees Kazi, Georgios Kaissis
A Survey on Graph Construction for Geometric Deep Learning in Medicine: Methods and Recommendations. Trans. Mach. Learn. Res. 2024 (2024)
Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Daniel Rueckert, Georgios Kaissis
Kernel Normalized Convolutional Networks. Trans. Mach. Learn. Res. 2024 (2024)
Marieke Ar Bak, Vince I. Madai, Leo Anthony Celi, Georgios Kaissis, Ronald Cornet, Menno Maris, Daniel Rueckert, Alena Buyx, Stuart McLennan
Federated learning is not a cure-all for data ethics. Nat. Mac. Intell. 6 (4) (2024)
Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training. EICC (2024)
Tamara T. Müller, Sophie Starck, Kyriaki-Margarita Bintsi, Alexander Ziller, Rickmer Braren, Georgios Kaissis, Daniel Rueckert
Are Population Graphs Really as Powerful as Believed? Trans. Mach. Learn. Res. 2024 (2024)
Dmitrii Usynin, Moritz Knolle, Georgios Kaissis
SoK: Memorisation in machine learning. CoRR (2023)
Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Huaqi Qiu, Georgios Kaissis, Daniel Rueckert
MAD: Modality Agnostic Distance Measure for Image Registration. MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI (2023)
Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis
Label Noise-Robust Learning using a Confidence-Based Sieving Strategy. Trans. Mach. Learn. Res. 2023 (2023)
Tamara T. Mueller, Maulik Chevli, Ameya Daigavane, Daniel Rueckert, Georgios Kaissis
Privacy-Utility Trade-offs in Neural Networks for Medical Population Graphs: Insights from Differential Privacy and Graph Structure. CoRR (2023)
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) (2023)
Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus R. Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis
Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology. CoRR (2023)
Felix Meissen, Svenja Breuer, Moritz Knolle, Alena Buyx, Ruth Müller, Georgios Kaissis, Benedikt Wiestler, Daniel Rueckert
(Predictable) Performance Bias in Unsupervised Anomaly Detection. CoRR (2023)
Ioannis Lagogiannis, Felix Meissen, Georgios Kaissis, Daniel Rueckert
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art. CoRR (2023)
Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann, Daniel Rueckert, Rickmer Braren, Georgios Kaissis
Exploiting Segmentation Labels and Representation Learning to Forecast Therapy Response of PDAC Patients. ISBI (2023)
Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Leveraging gradient-derived metrics for data selection and valuation in differentially private training. CoRR (2023)
Tomás Chobola, Dmitrii Usynin, Georgios Kaissis
Membership Inference Attacks Against Semantic Segmentation Models. AISec@CCS (2023)
Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Huaqi Qiu, Georgios Kaissis, Daniel Rueckert
MAD: Modality Agnostic Distance Measure for Image Registration. CoRR (2023)
Felix Meissen, Philip Müller, Georgios Kaissis, Daniel Rueckert
Robust Detection Outcome: A Metric for Pathology Detection in Medical Images. MIDL (2023)
Tamara T. Mueller, Siyu Zhou, Sophie Starck, Friederike Jungmann, Alexander Ziller, Orhun Aksoy, Danylo Movchan, Rickmer Braren, Georgios Kaissis, Daniel Rueckert
Body Fat Estimation from Surface Meshes using Graph Neural Networks. CoRR (2023)
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. UNSURE@MICCAI (2023)
Georgios Kaissis, Alexander Ziller, Stefan Kolek, Anneliese Riess, Daniel Rueckert
Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning. NeurIPS (2023)
Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner, Kyriaki-Margarita Bintsi, Daniel Rueckert, Georgios Kaissis
Extended Graph Assessment Metrics for Regression and Weighted Graphs. GRAIL/OCELOT@MICCAI (2023)
Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks. ACM Trans. Priv. Secur. 26 (3) (2023)
Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models. AISec@CCS (2023)
Alexander Ziller, Alp Güvenir, Ayhan Can Erdur, Tamara T. Mueller, Philip Müller, Friederike Jungmann, Johannes Brandt, Jan Peeken, Rickmer Braren, Daniel Rueckert, Georgios Kaissis
Explainable 2D Vision Models for 3D Medical Data. CoRR (2023)
David Bani-Harouni, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis
Gradient Self-alignment in Private Deep Learning. ISIC/Care-AI/MedAGI/DeCaF@MICCAI (2023)
Felix Meissen, Philip Müller, Georgios Kaissis, Daniel Rueckert
Robust Detection Outcome: A Metric for Pathology Detection in Medical Images. CoRR (2023)
Moritz Knolle, Robert Dorfman, Alexander Ziller, Daniel Rueckert, Georgios Kaissis
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD. CoRR (2023)
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. CoRR (2023)
Soroosh Tayebi Arasteh, Mahshad Lotfinia, Teresa Nolte, Marwin Saehn, Peter Isfort, Christiane Kuhl, Sven Nebelung, Georgios Kaissis, Daniel Truhn
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy. CoRR (2023)
Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner, Kyriaki-Margarita Bintsi, Daniel Rueckert, Georgios Kaissis
Extended Graph Assessment Metrics for Graph Neural Networks. CoRR (2023)
Reza Nasirigerdeh, Javad Torkzadehmahani, Daniel Rueckert, Georgios Kaissis
Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning. SaTML (2023)
Tamara T. Mueller, Siyu Zhou, Sophie Starck, Friederike Jungmann, Alexander Ziller, Orhun Aksoy, Danylo Movchan, Rickmer Braren, Georgios Kaissis, Daniel Rueckert
Body Fat Estimation from Surface Meshes Using Graph Neural Networks. ShapeMI@MICCAI (2023)
Tim Tanida, Philip Müller, Georgios Kaissis, Daniel Rueckert
Interactive and Explainable Region-guided Radiology Report Generation. CVPR (2023)
Philip Müller, Felix Meissen, Johannes Brandt, Georgios Kaissis, Daniel Rueckert
Anatomy-Driven Pathology Detection on Chest X-rays. CoRR (2023)
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F. Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R. Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard Ohene Botwe, Bishesh Khanal, Brigit Beger, Carol C. Wu, Celia Cintas, Curtis P. Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I. Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A. González, Folkert W. Asselbergs, Fred W. Prior, Gabriel P. Krestin, Gary S. Collins, Geletaw Sahle Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C. Woodruff, Hugo J. W. L. Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James S. Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W. Gichoya, Julia A. Schnabel, et al.
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. CoRR (2023)
Tim Tanida, Philip Müller, Georgios Kaissis, Daniel Rueckert
Interactive and Explainable Region-guided Radiology Report Generation. CoRR (2023)
Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis
Equivariant Differentially Private Deep Learning. CoRR (2023)
Georgios Kaissis, Jamie Hayes, Alexander Ziller, Daniel Rueckert
Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy. CoRR (2023)
Felix Meissen, Johannes Getzner, Alexander Ziller, Georgios Kaissis, Daniel Rueckert
How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection. CoRR (2023)
Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis
Utility-preserving Federated Learning. AISec@CCS (2023)
Alexander Ziller, Tamara T. Mueller, Simon Stieger, Leonhard F. Feiner, Johannes Brandt, Rickmer Braren, Daniel Rueckert, Georgios Kaissis
Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging. CoRR (2023)
Philip Müller, Felix Meissen, Johannes Brandt, Georgios Kaissis, Daniel Rueckert
Anatomy-Driven Pathology Detection on Chest X-rays. MICCAI (1) (2023)
Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland H. Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Miriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Grün, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz K. Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John S. Lowengrub, Jun Ma, Klaus H. Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Manuel Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern H. Menze
The Liver Tumor Segmentation Benchmark (LiTS). Medical Image Anal. 84 (2023)
Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis
Privacy: An axiomatic approach. CoRR (2022)
Qi Dou, Tiffany Y. So, Meirui Jiang, Quande Liu, Varut Vardhanabhuti, Georgios Kaissis, Zeju Li, Weixin Si, Heather H. C. Lee, Kevin Yu, Zuxin Feng, Li Dong, Egon Burian, Friederike Jungmann, Rickmer Braren, Marcus R. Makowski, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Simon C. H. Yu, Pheng-Ann Heng
Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. npj Digit. Medicine 5 (2022)
Felix Meissen, Johannes C. Paetzold, Georgios Kaissis, Daniel Rueckert
Unsupervised Anomaly Localization with Structural Feature-Autoencoders. CoRR (2022)
Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis
Label Noise-Robust Learning using a Confidence-Based Sieving Strategy. CoRR (2022)
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) (2022)
Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Differentially Private Graph Classification with GNNs. CoRR (2022)
Georgios Kaissis, Alexander Ziller, Stefan Kolek Martinez de Azagra, Daniel Rueckert
Generalised Likelihood Ratio Testing Adversaries through the Differential Privacy Lens. CoRR (2022)
Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks. CoRR (2022)
Vasiliki Sideri-Lampretsa, Georgios Kaissis, Daniel Rueckert
Multi-Modal Unsupervised Brain Image Registration Using Edge Maps. ISBI (2022)
Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Daniel Rueckert, Georgios Kaissis
Kernel Normalized Convolutional Networks. CoRR (2022)
Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert
Joint Learning of Localized Representations from Medical Images and Reports. ECCV (26) (2022)
Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis
Bridging the Gap: Differentially Private Equivariant Deep Learning for Medical Image Analysis. CoRR (2022)
Reza Nasirigerdeh, Javad Torkzadehmahani, Daniel Rueckert, Georgios Kaissis
Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning. CoRR (2022)
Tomás Chobola, Dmitrii Usynin, Georgios Kaissis
Membership Inference Attacks Against Semantic Segmentation Models. CoRR (2022)
Nicolas W. Remerscheid, Alexander Ziller, Daniel Rueckert, Georgios Kaissis
SmoothNets: Optimizing CNN architecture design for differentially private deep learning. CoRR (2022)
Suprosanna Shit, Rajat Koner, Bastian Wittmann, Johannes C. Paetzold, Ivan Ezhov, Hongwei Li, Jiazhen Pan, Sahand Sharifzadeh, Georgios Kaissis, Volker Tresp, Bjoern H. Menze
Relationformer: A Unified Framework for Image-to-Graph Generation. ECCV (37) (2022)
Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis
Privacy: An Axiomatic Approach. Entropy 24 (5) (2022)
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)
Philip Müller, Georgios Kaissis, Daniel Rueckert
The Role of Local Alignment and Uniformity in Image-Text Contrastive Learning on Medical Images. CoRR (2022)
Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann, Daniel Rueckert, Rickmer Braren, Georgios Kaissis
Exploiting segmentation labels and representation learning to forecast therapy response of PDAC patients. CoRR (2022)
Dmitrii Usynin, Helena Klause, Johannes C. Paetzold, Daniel Rueckert, Georgios Kaissis
Can Collaborative Learning Be Private, Robust and Scalable? DeCaF/FAIR@MICCAI (2022)
Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert
Radiological Reports Improve Pre-training for Localized Imaging Tasks on Chest X-Rays. MICCAI (5) (2022)
Dmitrii Usynin, Helena Klause, Daniel Rueckert, Georgios Kaissis
Can collaborative learning be private, robust and scalable? CoRR (2022)
Suprosanna Shit, Rajat Koner, Bastian Wittmann, Johannes C. Paetzold, Ivan Ezhov, Hongwei Li, Jiazhen Pan, Sahand Sharifzadeh, Georgios Kaissis, Volker Tresp, Bjoern H. Menze
Relationformer: A Unified Framework for Image-to-Graph Generation. CoRR (2022)
Felix Meissen, Benedikt Wiestler, Georgios Kaissis, Daniel Rueckert
On the Pitfalls of Using the Residual Error as Anomaly Score. CoRR (2022)
Vasiliki Sideri-Lampretsa, Georgios Kaissis, Daniel Rueckert
Multi-modal unsupervised brain image registration using edge maps. CoRR (2022)
Felix Meissen, Georgios Kaissis, Daniel Rueckert
AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation. CoRR (2022)
Tamara T. Mueller, Dmitrii Usynin, Johannes C. Paetzold, Daniel Rueckert, Georgios Kaissis
SoK: Differential Privacy on Graph-Structured Data. CoRR (2022)
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 (2022)
Helena Klause, Alexander Ziller, Daniel Rueckert, Kerstin Hammernik, Georgios Kaissis
Differentially private training of residual networks with scale normalisation. CoRR (2022)
Felix Meissen, Benedikt Wiestler, Georgios Kaissis, Daniel Rueckert
On the Pitfalls of Using the Residual Error as Anomaly Score. MIDL (2022)
Felix Meissen, Johannes C. Paetzold, Georgios Kaissis, Daniel Rueckert
Unsupervised Anomaly Localization with Structural Feature-Autoencoders. BrainLes@MICCAI (2022)
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) (2021)
Johannes C. Paetzold, Julian McGinnis, Suprosanna Shit, Ivan Ezhov, Paul Büschl, Chinmay Prabhakar, Anjany Sekuboyina, Mihail I. Todorov, Georgios Kaissis, Ali Ertürk, Stephan Günnemann, Bjoern H. Menze
Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience. NeurIPS Datasets and Benchmarks (2021)
Moritz Knolle, Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
NeuralDP Differentially private neural networks by design. CoRR (2021)
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 (2021)
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 (2021)
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 (2021)
Teddy Koker, Fatemehsadat Mireshghallah, Tom Titcombe, Georgios Kaissis
U-Noise: Learnable Noise Masks for Interpretable Image Segmentation. ICIP (2021)
Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis
Distributed Machine Learning and the Semblance of Trust. CoRR (2021)
Felix Meissen, Georgios Kaissis, Daniel Rueckert
AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation. MIDOG/MOOD/Learn2Reg@MICCAI (2021)
Dmitrii Usynin, Alexander Ziller, Moritz Knolle, Daniel Rueckert, Georgios Kaissis
An automatic differentiation system for the age of differential privacy. CoRR (2021)
Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert
Joint Learning of Localized Representations from Medical Images and Reports. CoRR (2021)
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 (2021)

Georgios Kaissis.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

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Georgios Kaissis