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Michael Davies
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
- [c9]Michael Davies
, Ian McDougall
, Selvaraj Anandaraj
, Deep Machchhar
, Rithik Jain
, Karthikeyan Sankaralingam
:
A Journey of a 1, 000 Kernels Begins with a Single Step: A Retrospective of Deep Learning on GPUs. ASPLOS (2) 2024: 20-36 - [i6]Zhanpeng Zeng, Michael Davies, Pranav Pulijala, Karthikeyan Sankaralingam, Vikas Singh:
LookupFFN: Making Transformers Compute-lite for CPU inference. CoRR abs/2403.07221 (2024) - 2023
- [c8]Zhanpeng Zeng, Michael Davies, Pranav Pulijala, Karthikeyan Sankaralingam, Vikas Singh:
LookupFFN: Making Transformers Compute-lite for CPU inference. ICML 2023: 40707-40718 - [i5]Ian McDougall, Shayne Wadle, Harish Batchu, Michael Davies, Karthikeyan Sankaralingam:
BRYT: Data Rich Analytics Based Computer Architecture for A New Paradigm of Chip Design to Supplant Moore's Law. CoRR abs/2312.13428 (2023) - 2022
- [c7]Karthikeyan Sankaralingam, Tony Nowatzki, Vinay Gangadhar, Preyas Shah, Michael Davies, William Galliher, Ziliang Guo, Jitu Khare, Deepak Vijay, Poly Palamuttam, Maghawan Punde, Alex Tan, Vijay Thiruvengadam, Rongyi Wang, Shunmiao Xu:
The Mozart reuse exposed dataflow processor for AI and beyond: industrial product. ISCA 2022: 978-992 - 2021
- [i4]Nikolajs Skuratovs, Michael Davies:
Divergence Estimation in Message Passing algorithms. CoRR abs/2105.07086 (2021) - [i3]Michael Davies, Adam Labiosa, Karthikeyan Sankaralingam:
Understanding the Limits of Conventional Hardware Architectures for Deep-Learning. CoRR abs/2112.02204 (2021) - 2020
- [c6]Nikolajs Skuratovs, Michael Davies:
Upscaling Vector Approximate Message Passing. ICASSP 2020: 4757-4761 - [i2]Nikolajs Skuratovs, Michael Davies:
Compressed Sensing with Upscaled Vector Approximate Message Passing. CoRR abs/2011.01369 (2020)
2010 – 2019
- 2018
- [j3]Kin Gwn Lore, Daniel Stoecklein, Michael Davies, Baskar Ganapathysubramanian, Soumik Sarkar
:
A deep learning framework for causal shape transformation. Neural Networks 98: 305-317 (2018) - [j2]Alex Grieve
, Michael Davies
, Phillip H. Jones
, Joseph Zambreno
:
ARMOR: A Recompilation and Instrumentation-Free Monitoring Architecture for Detecting Memory Exploits. IEEE Trans. Computers 67(8): 1092-1104 (2018) - 2017
- [c5]Rochelle Schneider dos Santos
, Jonathon Taylor
, Michael Davies
, Anna Mavrogianni
, James Milner
:
The variation of air and surface temperatures in London within a 1km grid using vehicle-transect and ASTER data. JURSE 2017: 1-4 - 2016
- [c4]Michael Davies, Menisha Patel:
Are we managing the risk of sharing cyber situational awareness? A UK Public Sector case study. CyberSA 2016: 1-2 - [i1]Kin Gwn Lore, Daniel Stoecklein, Michael Davies, Baskar Ganapathysubramanian, Soumik Sarkar:
Deep Action Sequence Learning for Causal Shape Transformation. CoRR abs/1605.05368 (2016) - 2015
- [c3]Kin Gwn Lore, Daniel Stoecklein, Michael Davies, Baskar Ganapathysubramanian, Soumik Sarkar:
Hierarchical Feature Extraction for Efficient Design of Microfluidic Flow Patterns. FE@NIPS 2015: 213-225 - 2012
- [j1]Fabien Millioz, Michael Davies:
Sparse Detection in the Chirplet Transform: Application to FMCW Radar Signals. IEEE Trans. Signal Process. 60(6): 2800-2813 (2012) - 2011
- [c2]Shamaila Iram
, Dhiya Al-Jumeily
, Paul Fergus
, Martin Randles
, Michael Davies:
E-Health: The Potential of Linked Data and Stream Reasoning for Personalised Healthcare. DeSE 2011: 46-49
2000 – 2009
- 2008
- [c1]Xu Zhao
, Michael Davies:
A feasible Blind Equalization scheme in large constellation MIMO systems. ICASSP 2008: 1845-1848
Coauthor Index
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