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Rahim Entezari
Rahim Entezari
Research Scientist, Stability
Verified email at stability.ai - Homepage
Title
Cited by
Cited by
Year
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
1692023
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
1432021
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
1202019
REPAIR: REnormalizing Permuted Activations for Interpolation Repair
K Jordan, H Sedghi, O Saukh, R Entezari, B Neyshabur
arXiv preprint arXiv:2211.08403, 2022
482022
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
372024
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
172023
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
92021
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
82019
Class-dependent Compression of Deep Neural Networks
R Entezari, O Saukh
arXiv preprint arXiv:1909.10364, 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
52022
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
52022
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
32022
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
22022
PhD Forum Abstract: Understanding Deep Model Compression for IoT Devices
R Entezari
2020 19th ACM/IEEE International Conference on Information Processing in …, 2020
12020
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
12016
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
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