Knockoff Nets: Stealing Functionality of Black-Box Models T Orekondy, B Schiele, M Fritz Computer Vision and Pattern Recognition (CVPR), 2019 | 532 | 2019 |
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks T Orekondy, B Schiele, M Fritz International Conference on Learning Representations (ICLR), 2020 | 167 | 2020 |
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators D Chen, T Orekondy, M Fritz Advances in Neural Information Processing Systems (NeurIPS), 2020 | 159 | 2020 |
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images T Orekondy, B Schiele, M Fritz The IEEE International Conference on Computer Vision (ICCV), 2017 | 149 | 2017 |
Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images T Orekondy, M Fritz, B Schiele Computer Vision and Pattern Recognition (CVPR), 2018 | 90 | 2018 |
Gradient-Leaks: Understanding Deanonymization in Federated Learning T Orekondy, SJ Oh, Y Zhang, B Schiele, M Fritz NeurIPS Workshop on Federated Learning for Data Privacy and Confidentiality, 2019 | 66* | 2019 |
Differential privacy defenses and sampling attacks for membership inference S Rahimian, T Orekondy, M Fritz ACM Workshop on Artificial Intelligence and Security (AISec), 193-202, 2021 | 30 | 2021 |
Sampling attacks: Amplification of membership inference attacks by repeated queries S Rahimian, T Orekondy, M Fritz arXiv preprint arXiv:2009.00395, 2020 | 30 | 2020 |
Infoscrub: Towards attribute privacy by targeted obfuscation HP Wang, T Orekondy, M Fritz Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 21 | 2021 |
MIMO-GAN: Generative MIMO Channel Modeling T Orekondy, A Behboodi, JB Soriaga IEEE International Conference on Communications (ICC), 2022 | 18 | 2022 |
WiNeRT: Towards Neural Ray Tracing for Wireless Channel Modelling and Differentiable Simulations T Orekondy, P Kumar, S Kadambi, H Ye, J Soriaga, A Behboodi International Conference on Learning Representations (ICLR), 2023 | 10 | 2023 |
Data-Driven Probabilistic Modeling of Wireless Channels using Conditional Variational Auto-encoders A Behboodi, S Zheng, JB Soriaga, M Welling, T Orekondy US Patent App. 17/504,341, 2022 | 1 | 2022 |
Multi-dimensional geometric wireless channel rendering using machine learning models T Orekondy, A Behboodi, K Pratik, JB Soriaga, S Kadambi US Patent App. 17/935,046, 2024 | | 2024 |
Wireless channel rendering using neural networks T Orekondy, A Behboodi, YE Hao, JB Soriaga US Patent App. 17/935,006, 2024 | | 2024 |
Active Learning Policies for Solving Inverse Problems T Bakker, T Hehn, T Orekondy, A Behboodi, FV Massoli NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in …, 2023 | | 2023 |
Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps TM Hehn, T Orekondy, O Shental, A Behboodi, J Bucheli, A Doshi, ... GLOBECOM 2023-2023 IEEE Global Communications Conference, 4804-4809, 2023 | | 2023 |
Switching policies for solving inverse problems T Bakker, FV Massoli, T Hehn, T Orekondy, A Behboodi NeurIPS 2023 Workshop on Deep Learning and Inverse Problems, 2023 | | 2023 |
Generative wireless channel modeling T Orekondy, A Behboodi, JB Soriaga, M Welling US Patent App. 18/054,896, 2023 | | 2023 |
Understanding and controlling leakage in machine learning T Orekondy Saarländische Universitäts-und Landesbibliothek, 2020 | | 2020 |
HADES: Hierarchical Approximate Decoding for Structured Prediction T Orekondy ETH-Zürich, 2015 | | 2015 |