Nicholas J. Fraser

Australian National University — Australia

Computer Science · Physical Sciences

11h-index690citations39works2.52yr avg
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Research Topics

Advanced Neural Network Applications(20), Adversarial Robustness in Machine Learning(11), CCD and CMOS Imaging Sensors(11), Radiation Effects in Electronics(8), Advanced Adaptive Filtering Techniques(7)

Publications39 total

Structural and evolutionary constraints of organophosphate resistance in dipteran carboxylesterases
Proceedings of the National Academy of Sciences·2026Open Access
Greater than the Sum of its LUTs: Scaling Up LUT-based Neural Networks with AmigoLUT
2025· 7 citedOpen Access
Protons Evaluation of 7nm Versal™ AI Engine (AIE) Based Radiation Tolerant Platform for Deep Learning Applications
2024
Synthesis of LUT Networks for Random-Looking Dense Functions with Don't Cares — Towards Efficient FPGA Implementation of DNN
2024· 3 cited
Radiation-Tolerant Deep Learning Processor Unit (DPU)-Based Platform Using Xilinx 20-nm Kintex UltraScale FPGA
IEEE Transactions on Nuclear Science·2022· 17 cited
Fault-Tolerant Neural Network Accelerators With Selective TMR
IEEE Design and Test·2022· 23 citedOpen Access
Accelerated Radiation Test on Quantized Neural Networks trained with Fault Aware Training
2022 IEEE Aerospace Conference (AERO)·2022· 9 cited
Trainable Preprocessing for Reduced Precision Neural Networks
2021 29th European Signal Processing Conference (EUSIPCO)·2021Open Access
Space DPU: Constructing a Radiation-Tolerant, FPGA-based Platform for Deep Learning Acceleration on Space Payloads
Zenodo (CERN European Organization for Nuclear Research)·2021· 3 citedOpen Access
Memory-Efficient Dataflow Inference for Deep CNNs on FPGA
2020· 2 citedOpen Access
FAT: Training Neural Networks for Reliable Inference Under Hardware\n Faults
arXiv (Cornell University)·2020Open Access
FAT: Training Neural Networks for Reliable Inference Under Hardware Faults
2020· 1 citedOpen Access
Algorithms and Architectures for High Performance Kernel Adaptive Filtering
The Sydney eScholarship Repository (The University of Sydney)·2020Open Access
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications
2020· 5 citedOpen Access
High-Throughput DNN Inference with LogicNets
2020· 7 cited
LogicNets: Co-Designed Neural Networks and Circuits for\n Extreme-Throughput Applications
arXiv (Cornell University)·2020Open Access
Evaluation of Optimized CNNs on FPGA and non-FPGA based Accelerators using a Novel Benchmarking Approach
2020· 1 cited
Kernel Normalised Least Mean Squares with Delayed Model Adaptation
ACM Transactions on Reconfigurable Technology and Systems·2020· 2 cited
Evaluation of Optimized CNNs on Heterogeneous Accelerators using a Novel Benchmarking Approach
IEEE Transactions on Computers·2020· 18 citedOpen Access
FINN- <i>R</i>
ACM Transactions on Reconfigurable Technology and Systems·2018· 383 citedOpen Access
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Frequent Co-authors

Michaela Blott(21), Giulio Gambardella(17), Philip H. W. Leong(15), Yaman Umuroglu(11), Kees Vissers(6), Miriam Leeser(5), Duncan J. M. Moss(5), Kenneth M. O'Brien(4), Julian Faraone(4), Thomas B. Preußer(3), Pierre Maillard(3), Minal Sawant(3), Ussama Zahid(3), Stephen Tridgell(3), Yash Akhauri(3), Magnus Jahre(2), Su Jiang(2), Gianluca Durelli(2), David B. Thomas(2), Peter Y. K. Cheung(2)