A mafia and distance fraud high-resistance RFID distance bounding protocol. - Rahim Entezari; Hossein Bahramgiri; Mahnaz Tajamolian (ISCISC, 2014)

RFID unilateral distance bounding protocols: A trade-off between mafia and distance fraud. - Rahim Entezari; Hossein Bahramgiri; Mahnaz Tajamolian (Comput. Commun., 2017)

AVID: Adversarial Visual Irregularity Detection. - Mohammad Sabokrou; Masoud PourReza; Mohsen Fayyaz; Rahim Entezari; Mahmood Fathy; Jürgen Gall; Ehsan Adeli 001 (ACCV (6), 2018)

Incoherent waveform design for compressed sensing radar based on pulse-train scenario. - Rahim Entezari; Alijabbar Rashidi (IET Commun., 2018)

Deep and Efficient Impact Models for Edge Characterization and Control of Energy Events. - Grigore Stamatescu; Rahim Entezari; Kay Römer; Olga Saukh (ICPADS, 2019)

Class-dependent Compression of Deep Neural Networks. - Rahim Entezari; Olga Saukh (CoRR, 2019)

PhD Forum Abstract: Understanding Deep Model Compression for IoT Devices. - Rahim Entezari (IPSN, 2020)

The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. - Rahim Entezari; Hanie Sedghi; Olga Saukh; Behnam Neyshabur (ICLR, 2022)

To Share or Not to Share: On Location Privacy in IoT Sensor Data. - Franz Papst; Naomi Stricker; Rahim Entezari; Olga Saukh (IoTDI, 2022)

Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin and Eosin-Stained Histological Images. - Amirreza Mahbod; Rahim Entezari; Isabella Ellinger; Olga Saukh (AMAI@MICCAI, 2022)

Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images. - Amirreza Mahbod; Rahim Entezari; Isabella Ellinger; Olga Saukh (CoRR, 2022)

Understanding the effect of sparsity on neural networks robustness. - Lukas Timpl; Rahim Entezari; Hanie Sedghi; Behnam Neyshabur; Olga Saukh (CoRR, 2022)

Studying the impact of magnitude pruning on contrastive learning methods. - Francesco Corti; Rahim Entezari; Sara Hooker; Davide Bacciu; Olga Saukh (CoRR, 2022)

REPAIR: REnormalizing Permuted Activations for Interpolation Repair. - Keller Jordan; Hanie Sedghi; Olga Saukh; Rahim Entezari; Behnam Neyshabur (ICLR, 2023)

DataComp: In search of the next generation of multimodal datasets. - Samir Yitzhak Gadre; Gabriel Ilharco; Alex Fang; Jonathan Hayase; Georgios Smyrnis; Thao Nguyen; Ryan Marten; Mitchell Wortsman; Dhruba Ghosh; Jieyu Zhang 001; Eyal Orgad; Rahim Entezari; et al. (NeurIPS, 2023)

The Role of Pre-training Data in Transfer Learning. - Rahim Entezari; Mitchell Wortsman; Olga Saukh; Moein Shariatnia; Hanie Sedghi; Ludwig Schmidt (CoRR, 2023)

Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. - Patrick Esser; Sumith Kulal; Andreas Blattmann; Rahim Entezari; Jonas Müller; Harry Saini; Yam Levi; Dominik Lorenz; Axel Sauer; Frederic Boesel; Dustin Podell; Tim Dockhorn; et al. (ICML, 2024)

Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. - Patrick Esser; Sumith Kulal; Andreas Blattmann; Rahim Entezari; Jonas Müller; Harry Saini; Yam Levi; Dominik Lorenz; Axel Sauer; Frederic Boesel; Dustin Podell; Tim Dockhorn; et al. (CoRR, 2024)

Unlocking Intrinsic Fairness in Stable Diffusion. - Eunji Kim 002; Siwon Kim; Rahim Entezari; Sungroh Yoon (CoRR, 2024)

Rethinking Training for De-biasing Text-to-Image Generation: Unlocking the Potential of Stable Diffusion. - Eunji Kim 002; Siwon Kim; Minjun Park; Rahim Entezari; Sungroh Yoon (CVPR, 2025)