Michaela Blott

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Papers (10)

1. FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks cs.AR · 2018 · author #1
2. Accuracy to Throughput Trade-offs for Reduced Precision Neural Networks on Reconfigurable Logic cs.CV · 2018 · author #4
3. FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs cs.CV · 2018 · author #6
4. SYQ: Learning Symmetric Quantization For Efficient Deep Neural Networks cs.CV · 2018 · author #3
5. Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic cs.CV · 2018 · author #1
6. Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices cs.NE · 2018 · author #4
7. Compressing Low Precision Deep Neural Networks Using Sparsity-Induced Regularization in Ternary Networks cs.CV · 2017 · author #4
8. Scaling Binarized Neural Networks on Reconfigurable Logic cs.CV · 2017 · author #4
9. FINN: A Framework for Fast, Scalable Binarized Neural Network Inference cs.CV · 2016 · author #4
10. High-Level Synthesis Case Study: Implementation of a Memcached Server cs.OH · 2014 · author #2

Mentions

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Frequent Coauthors

• Giulio Gambardella 8 shared papers
• Nicholas Fraser 5 shared papers
• Yaman Umuroglu 4 shared papers
• Kees Vissers 3 shared papers
• Nicholas J. Fraser 3 shared papers
• Philip Leong 3 shared papers
• Julian Faraone 2 shared papers
• Magnus Jahre 2 shared papers
• Philip H.W. Leong 2 shared papers
• Alessandro Pappalardo 1 shared papers
• David B. Thomas 1 shared papers
• Gianluca Durelli 1 shared papers
• Jiang Su 1 shared papers
• Kenneth O'Brien 1 shared papers
• Kenneth OBrien 1 shared papers
• Kimon Karras 1 shared papers
• Miriam Leeser 1 shared papers
• Muhammad Mohsin Ghaffar 1 shared papers
• Norbert Wehn 1 shared papers
• Peter Y. K. Cheung 1 shared papers