| A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA H Fan, S Liu, M Ferianc, HC Ng, Z Que, S Liu, X Niu, W Luk 2018 International Conference on Field-Programmable Technology (FPT), 14-21, 2018 | 69 | 2018 |
| F-E3D: FPGA-based acceleration of an efficient 3D convolutional neural network for human action recognition H Fan, C Luo, C Zeng, M Ferianc, Z Que, S Liu, X Niu, W Luk 2019 IEEE 30th international conference on Application-specific Systems …, 2019 | 44 | 2019 |
| High-performance FPGA-based accelerator for Bayesian neural networks H Fan, M Ferianc, M Rodrigues, H Zhou, X Niu, W Luk 2021 58th ACM/IEEE Design Automation Conference (DAC), 1063-1068, 2021 | 19 | 2021 |
| Toward full-stack acceleration of deep convolutional neural networks on FPGAs S Liu, H Fan, M Ferianc, X Niu, H Shi, W Luk IEEE Transactions on Neural Networks and Learning Systems 33 (8), 3974-3987, 2021 | 19 | 2021 |
| Improving performance estimation for FPGA-based accelerators for convolutional neural networks M Ferianc, H Fan, RSW Chu, J Stano, W Luk Applied Reconfigurable Computing. Architectures, Tools, and Applications …, 2020 | 19 | 2020 |
| FPGA-based acceleration for Bayesian convolutional neural networks H Fan, M Ferianc, Z Que, S Liu, X Niu, MRD Rodrigues, W Luk IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2022 | 13 | 2022 |
| Static block floating-point quantization for convolutional neural networks on FPGA H Fan, G Wang, M Ferianc, X Niu, W Luk 2019 International Conference on Field-Programmable Technology (ICFPT), 28-35, 2019 | 12 | 2019 |
| Optimizing FPGA-based CNN accelerator using differentiable neural architecture search H Fan, M Ferianc, S Liu, Z Que, X Niu, W Luk 2020 IEEE 38th International Conference on Computer Design (ICCD), 465-468, 2020 | 11 | 2020 |
| Algorithm and hardware co-design for reconfigurable cnn accelerator H Fan, M Ferianc, Z Que, H Li, S Liu, X Niu, W Luk 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC), 250-255, 2022 | 10 | 2022 |
| Improving performance estimation for design space exploration for convolutional neural network accelerators M Ferianc, H Fan, D Manocha, H Zhou, S Liu, X Niu, W Luk Electronics 10 (4), 520, 2021 | 9 | 2021 |
| Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions RI Masoud, Z Liu, M Ferianc, P Treleaven, M Rodrigues arXiv preprint arXiv:2309.12342, 2023 | 7 | 2023 |
| Optimizing Bayesian recurrent neural networks on an FPGA-based accelerator M Ferianc, Z Que, H Fan, W Luk, M Rodrigues 2021 International Conference on Field-Programmable Technology (ICFPT), 1-10, 2021 | 7 | 2021 |
| On the effects of quantisation on model uncertainty in bayesian neural networks M Ferianc, P Maji, M Mattina, M Rodrigues Uncertainty in Artificial Intelligence, 929-938, 2021 | 7 | 2021 |
| VINNAS: Variational Inference-based Neural Network Architecture Search M Ferianc, H Fan, M Rodrigues arXiv preprint arXiv:2007.06103, 2020 | 6 | 2020 |
| Accelerating Bayesian neural networks via algorithmic and hardware optimizations H Fan, M Ferianc, Z Que, X Niu, M Rodrigues, W Luk IEEE Transactions on Parallel and Distributed Systems 33 (12), 3387-3399, 2022 | 5 | 2022 |
| Renate: A Library for Real-World Continual Learning M Wistuba, M Ferianc, L Balles, C Archambeau, G Zappella 2023 Continual Learning in Computer Vision (CLCV) workshop at CVPR 2023, 2023 | 4 | 2023 |
| ComBiNet: Compact convolutional Bayesian neural network for image segmentation M Ferianc, D Manocha, H Fan, M Rodrigues Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 4 | 2021 |
| Impact of Noise on Calibration and Generalisation of Neural Networks M Ferianc, O Bohdal, T Hospedales, M Rodrigues ICML 2023 Workshop on Spurious Correlations, Invariance, and Stability, 2023 | 3 | 2023 |
| MIMMO: Multi-Input Massive Multi-Output Neural Network M Ferianc, M Rodrigues Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 3 | 2023 |
| On Causal Inference for Data-free Structured Pruning M Ferianc, A Sankaran, O Mastropietro, E Saboori, Q Cappart The AAAI-22 Workshop on Information-Theoretic Methods for Causal Inference …, 2021 | 2 | 2021 |
Fan HongxiangSamsung AI Center & University of CambridgeVerified email at imperial.ac.uk
