Mohammad Ahsan Sohail on Muck Rack

Mohammad Ahsan Sohail

As seen in: PLOS ONE, MDPI, HubPages
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Articles

L2R-CIPU: Efficient CNN Computation with Left-to-Right Composite Inner Product Units

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By Malik Zohaib, Mohammad Ahsan Sohail, Mohammad Ibrahim, Muhammad Usman
| arxiv.org
arXiv:2406.00360 (cs) View PDF HTML (experimental) Subjects: Hardware Architecture (cs.AR) Cite as: arXiv:2406.00360 [cs.AR] (or arXiv:2406.00360v1 [cs.AR] for this version) Submission history From: Muhammad Usman [ view email] [v1] Sat, 1 Jun 2024 08:25:16 UTC (3,416 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Links to Code Toggle...
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Density Functional Theory Unveils the Secrets of SiAuF3 and SiCuF3: Exploring Their Striking Structural, Electronic, Elastic, and Optical Properties

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By Fekhra Hedhili, Hukam Khan, Mohammad Ahsan Sohail, Furqan Ullah
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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LayerCollapse: Adaptive compression of neural networks

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By Mohammad Ahsan Sohail, Soheil Zibakhsh
| arxiv.org
[Submitted on 29 Nov 2023 ( v1 ), last revised 8 Feb 2024 (this version, v2)] Title:LayerCollapse: Adaptive compression of neural networks Download a PDF of the paper titled LayerCollapse: Adaptive compression of neural networks, by Soheil Zibakhsh Shabgahi and 2 other authors Download PDF HTML (experimental) Abstract:Handling the ever-increasing scale of contemporary deep learning and transformer-based models poses a significant challenge.
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