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ORCIDKossar Pourahmadi
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2020 – today
- 2024
[c4]K. L. Navaneet, Kossar Pourahmadi Meibodi, Soroush Abbasi Koohpayegani, Hamed Pirsiavash:
CompGS: Smaller and Faster Gaussian Splatting with Vector Quantization. ECCV (32) 2024: 330-349- [i5]Ajinkya Tejankar, Navaneet K. L., Ujjawal Panchal, Kossar Pourahmadi, Hamed Pirsiavash:
MoIN: Mixture of Introvert Experts to Upcycle an LLM. CoRR abs/2410.09687 (2024) - 2023
- [c3]Parsa Nooralinejad, Ali Abbasi, Soroush Abbasi Koohpayegani, Kossar Pourahmadi Meibodi, Rana Muhammad Shahroz Khan, Soheil Kolouri, Hamed Pirsiavash:
PRANC: Pseudo RAndom Networks for Compacting deep models. ICCV 2023: 16975-16985 - [i4]K. L. Navaneet, Kossar Pourahmadi Meibodi, Soroush Abbasi Koohpayegani, Hamed Pirsiavash:
Compact3D: Compressing Gaussian Splat Radiance Field Models with Vector Quantization. CoRR abs/2311.18159 (2023) - 2022
- [c2]K. L. Navaneet, Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Kossar Pourahmadi, Akshayvarun Subramanya, Hamed Pirsiavash:
Constrained Mean Shift Using Distant yet Related Neighbors for Representation Learning. ECCV (31) 2022: 23-41 - 2021
- [i3]Kossar Pourahmadi, Parsa Nooralinejad, Hamed Pirsiavash:
A Simple Baseline for Low-Budget Active Learning. CoRR abs/2110.12033 (2021) - [i2]Ajinkya Tejankar, Soroush Abbasi Koohpayegani, K. L. Navaneet, Kossar Pourahmadi, Akshayvarun Subramanya, Hamed Pirsiavash:
Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning. CoRR abs/2112.04607 (2021) - 2020
- [c1]Reza Hojabr, Kamyar Givaki
, Kossar Pourahmadi, Parsa Nooralinejad, Ahmad Khonsari, Dara Rahmati, M. Hassan Najafi:
TaxoNN: A Light-Weight Accelerator for Deep Neural Network Training. ISCAS 2020: 1-5 - [i1]Reza Hojabr, Kamyar Givaki, Kossar Pourahmadi, Parsa Nooralinejad, Ahmad Khonsari, Dara Rahmati, M. Hassan Najafi:
TaxoNN: A Light-Weight Accelerator for Deep Neural Network Training. CoRR abs/2010.05197 (2020)
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