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ORCIDRahim Entezari
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2020 – today
- 2024
[c10]Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, Robin Rombach:
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. ICML 2024- [i11]Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, Kyle Lacey, Alex Goodwin, Yannik Marek, Robin Rombach:
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. CoRR abs/2403.03206 (2024) - [i10]Eunji Kim, Siwon Kim, Rahim Entezari, Sungroh Yoon:
Unlocking Intrinsic Fairness in Stable Diffusion. CoRR abs/2408.12692 (2024) - 2023
- [c9]Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur:
REPAIR: REnormalizing Permuted Activations for Interpolation Repair. ICLR 2023 - [c8]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023 - [i9]Rahim Entezari, Mitchell Wortsman, Olga Saukh, Moein Shariatnia, Hanie Sedghi, Ludwig Schmidt:
The Role of Pre-training Data in Transfer Learning. CoRR abs/2302.13602 (2023) - [i8]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - 2022
- [c7]Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur:
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. ICLR 2022 - [c6]Franz Papst
, Naomi Stricker, Rahim Entezari, Olga Saukh:
To Share or Not to Share: On Location Privacy in IoT Sensor Data. IoTDI 2022: 128-140 - [c5]Amirreza Mahbod, Rahim Entezari, Isabella Ellinger, Olga Saukh:
Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin and Eosin-Stained Histological Images. AMAI@MICCAI 2022: 108-117 - [i7]Amirreza Mahbod, Rahim Entezari, Isabella Ellinger, Olga Saukh:
Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images. CoRR abs/2206.07422 (2022) - [i6]Lukas Timpl, Rahim Entezari, Hanie Sedghi, Behnam Neyshabur, Olga Saukh:
Understanding the effect of sparsity on neural networks robustness. CoRR abs/2206.10915 (2022) - [i5]Francesco Corti, Rahim Entezari, Sara Hooker, Davide Bacciu, Olga Saukh:
Studying the impact of magnitude pruning on contrastive learning methods. CoRR abs/2207.00200 (2022) - [i4]Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur:
REPAIR: REnormalizing Permuted Activations for Interpolation Repair. CoRR abs/2211.08403 (2022) - 2021
- [i3]Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur:
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. CoRR abs/2110.06296 (2021) - 2020
- [c4]Rahim Entezari:
PhD Forum Abstract: Understanding Deep Model Compression for IoT Devices. IPSN 2020: 385-386
2010 – 2019
- 2019
- [c3]Grigore Stamatescu, Rahim Entezari, Kay Römer, Olga Saukh:
Deep and Efficient Impact Models for Edge Characterization and Control of Energy Events. ICPADS 2019: 639-646 - [i2]Rahim Entezari, Olga Saukh:
Class-dependent Compression of Deep Neural Networks. CoRR abs/1909.10364 (2019) - 2018
- [j2]Rahim Entezari, Alijabbar Rashidi:
Incoherent waveform design for compressed sensing radar based on pulse-train scenario. IET Commun. 12(17): 2132-2136 (2018) - [c2]Mohammad Sabokrou, Masoud PourReza, Mohsen Fayyaz, Rahim Entezari, Mahmood Fathy, Jürgen Gall, Ehsan Adeli:
AVID: Adversarial Visual Irregularity Detection. ACCV (6) 2018: 488-505 - [i1]Mohammad Sabokrou, Masoud PourReza, Mohsen Fayyaz, Rahim Entezari, Mahmood Fathy, Jürgen Gall, Ehsan Adeli:
AVID: Adversarial Visual Irregularity Detection. CoRR abs/1805.09521 (2018) - 2017
- [j1]Rahim Entezari, Hossein Bahramgiri, Mahnaz Tajamolian:
RFID unilateral distance bounding protocols: A trade-off between mafia and distance fraud. Comput. Commun. 98: 97-105 (2017) - 2014
- [c1]Rahim Entezari, Hossein Bahramgiri, Mahnaz Tajamolian:
A mafia and distance fraud high-resistance RFID distance bounding protocol. ISCISC 2014: 67-72
Coauthor Index
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last updated on 2024-10-07 22:18 CEST by the dblp team
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