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Emanuele Valpreda
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2020 – today
- 2024
- [j3]Flavia Guella
, Emanuele Valpreda
MARLIN: A Co-Design Methodology for Approximate ReconfigurabLe Inference of Neural Networks at the Edge. IEEE Trans. Circuits Syst. I Regul. Pap. 71(5): 2105-2118 (2024) - [c6]Alessandra Dolmeta
Implementation and integration of NTT/INTT accelerator on RISC-V for CRYSTALS-Kyber. CF (Companion) 2024 - 2023
- [c5]Flavia Guella, Emanuele Valpreda, Michele Caon, Guido Masera
TEMET: Truncated REconfigurable Multiplier with Error Tuning. ApplePies 2023: 370-377 - [c4]Emanuele Valpreda
ERODE: Error Resilient Object DetEction by Recovering Bounding Box and Class Information. PRIME 2023: 277-280 - 2022
- [j2]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Emanuele Valpreda
HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology. Leibniz Trans. Embed. Syst. 8(1): 03:1-03:30 (2022) - [c3]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda
AnaCoNGA: Analytical HW-CNN Co-Design Using Nested Genetic Algorithms. DATE 2022: 238-243 - [c2]Nael Fasfous, Lukas Frickenstein, Michael Neumeier, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda
Mind the Scaling Factors: Resilience Analysis of Quantized Adversarially Robust CNNs. DATE 2022: 706-711 - [c1]Giuseppe Aiello, Beatrice Bussolino, Emanuele Valpreda
NLCMAP: A Framework for the Efficient Mapping of Non-Linear Convolutional Neural Networks on FPGA Accelerators. ICIP 2022: 926-930 - 2021
- [j1]Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Emanuele Valpreda
HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology. ACM Trans. Embed. Comput. Syst. 20(5s): 66:1-66:25 (2021)
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