| DataComp: In search of the next generation of multimodal datasets SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ... arXiv preprint arXiv:2304.14108, 2023 | 234 | 2023 |
| The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks R Entezari, H Sedghi, O Saukh, B Neyshabur International Conference on Learning Representations, 2021 | 166 | 2021 |
| Scaling Rectified Flow Transformers for High-Resolution Image Synthesis P Esser, S Kulal, A Blattmann, R Entezari, J Müller, H Saini, Y Levi, ... arXiv preprint arXiv:2403.03206, 2024 | 153 | 2024 |
| Avid: Adversarial visual irregularity detection M Sabokrou, M Pourreza, M Fayyaz, R Entezari, M Fathy, J Gall, E Adeli Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019 | 125 | 2019 |
| REPAIR: REnormalizing Permuted Activations for Interpolation Repair K Jordan, H Sedghi, O Saukh, R Entezari, B Neyshabur arXiv preprint arXiv:2211.08403, 2022 | 57 | 2022 |
| The Role of Pre-training Data in Transfer Learning R Entezari, M Wortsman, O Saukh, MM Shariatnia, H Sedghi, L Schmidt arXiv preprint arXiv:2302.13602, 2023 | 18 | 2023 |
| Understanding the effect of sparsity on neural networks robustness L Timpl, R Entezari, H Sedghi, B Neyshabur, O Saukh ICML 2021 Workshop on Over-parameterization: Pitfalls & Opportunities, 2021 | 10 | 2021 |
| Class-dependent Compression of Deep Neural Networks R Entezari, O Saukh arXiv preprint arXiv:1909.10364, 2019 | 9* | 2019 |
| Deep and efficient impact models for edge characterization and control of energy events G Stamatescu, R Entezari, K Römer, O Saukh 2019 IEEE 25th International Conference on Parallel and Distributed Systems …, 2019 | 8 | 2019 |
| Deep neural network pruning for nuclei instance segmentation in hematoxylin and eosin-stained histological images A Mahbod, R Entezari, I Ellinger, O Saukh Applications of Medical Artificial Intelligence: First International …, 2022 | 6 | 2022 |
| Studying the impact of magnitude pruning on contrastive learning methods F Corti, R Entezari, S Hooker, D Bacciu, O Saukh arXiv preprint arXiv:2207.00200, 2022 | 6 | 2022 |
| To Share or Not to Share: On Location Privacy in IoT Sensor Data F Papst, N Stricker, R Entezari, O Saukh 2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design …, 2022 | 3 | 2022 |
| How well do contrastively trained models transfer? MM Shariatnia, R Entezari, M Wortsman, O Saukh, L Schmidt First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward at …, 2022 | 2 | 2022 |
| A probabilistic graphical model approach for human activity recognition using skeleton data AH Bayat, MM Arzani, M Fathy, A Matinnejad, B Minaei-Bidgoli, ... 2016 2nd International Conference of Signal Processing and Intelligent …, 2016 | 2 | 2016 |
| PhD Forum Abstract: Understanding Deep Model Compression for IoT Devices R Entezari 2020 19th ACM/IEEE International Conference on Information Processing in …, 2020 | 1 | 2020 |
| A DEEP LEARNING METHOD TO ESTIMATE 3D POINT OF REGARD BY JOINT HEAD AND EYE INFORMATION R ENTEZARI, MM ARZANI, M FATHY, AH BAYAT THE CSI JOURNAL ON COMPUTER SCIENCE AND ENGINEERING 13 (2), 42-47, 2016 | | 2016 |
| Linear Mode Connectivity of Deep Neural Networks via Permutation Invariance and Renormalization K Jordan, H Sedghi, O Saukh, R Entezari, B Neyshabur International Conference on Learning Representations, 0 | | |
Olga SaukhTU Graz / CSH ViennaVerified email at tugraz.at
