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ORCIDMartin Ferianc
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2020 – today
- 2024
[j4]Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues:
Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks. Trans. Mach. Learn. Res. 2024 (2024)- [i15]Martin Ferianc, Miguel Rodrigues:
YAMLE: Yet Another Machine Learning Environment. CoRR abs/2402.06268 (2024) - [i14]Martin Ferianc, Hongxiang Fan, Miguel Rodrigues:
SAE: Single Architecture Ensemble Neural Networks. CoRR abs/2402.06580 (2024) - [i13]Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun, Kevin K. Nejad, Felipe Yáñez
, Bati Yilmaz, Kangjoo Lee, Alexandra O. Cohen, Valentina Borghesani, Anton Pashkov, Daniele Marinazzo, Jonathan Nicholas, Alessandro Salatiello, Ilia Sucholutsky, Pasquale Minervini, Sepehr Razavi, Roberta Rocca, Elkhan Yusifov, Tereza Okalova, Nianlong Gu, Martin Ferianc, Mikail Khona, Kaustubh R. Patil, Pui-Shee Lee, Rui Mata, Nicholas E. Myers, Jennifer K. Bizley, Sebastian Musslick, Isil Poyraz Bilgin, Guiomar Niso, Justin M. Ales, Michael Gaebler, N. Apurva Ratan Murty, Leyla Loued-Khenissi, Anna Behler, Chloe M. Hall, Jessica Dafflon, Sherry Dongqi Bao, Bradley C. Love:
Large language models surpass human experts in predicting neuroscience results. CoRR abs/2403.03230 (2024) - [i12]Hao Mark Chen, Liam Castelli, Martin Ferianc, Hongyu Zhou, Shuanglong Liu, Wayne Luk, Hongxiang Fan:
Enhancing Dropout-based Bayesian Neural Networks with Multi-Exit on FPGA. CoRR abs/2406.14593 (2024) - 2023
- [c14]Juraj Papco, Matus Bakon, Lukas Kubica, Gabika Belicova, Branislav Droscak, Martin Ferianc, Martin Rovnak, Antonio M. Ruiz-Armenteros, Joaquim João Sousa:
Satellite-based InSAR Geodesy and Collocation with GNSS. CENTERIS/ProjMAN/HCist 2023: 2329-2340 - [c13]Martin Ferianc, Miguel Rodrigues:
MIMMO: Multi-Input Massive Multi-Output Neural Network. CVPR Workshops 2023: 4564-4569 - [c12]Vittorio Casagrande, Martin Ferianc, Miguel Rodrigues, Francesca Boem:
An Online Learning Method for Microgrid Energy Management Control*. MED 2023: 263-268 - [i11]Martin Wistuba, Martin Ferianc, Lukas Balles, Cédric Archambeau, Giovanni Zappella:
Renate: A Library for Real-World Continual Learning. CoRR abs/2304.12067 (2023) - [i10]Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues:
Impact of Noise on Calibration and Generalisation of Neural Networks. CoRR abs/2306.17630 (2023) - [i9]Reem I. Masoud, Ziquan Liu, Martin Ferianc, Philip C. Treleaven, Miguel Rodrigues:
Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions. CoRR abs/2309.12342 (2023) - 2022
- [j3]Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk:
FPGA-Based Acceleration for Bayesian Convolutional Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(12): 5343-5356 (2022) - [j2]Shuanglong Liu, Hongxiang Fan, Martin Ferianc, Xinyu Niu, Huifeng Shi, Wayne Luk:
Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs. IEEE Trans. Neural Networks Learn. Syst. 33(8): 3974-3987 (2022) - [j1]Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk:
Accelerating Bayesian Neural Networks via Algorithmic and Hardware Optimizations. IEEE Trans. Parallel Distributed Syst. 33(12): 3387-3399 (2022) - [c11]Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk:
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. ASP-DAC 2022: 250-255 - [c10]Hongxiang Fan, Martin Ferianc, Wayne Luk:
Enabling fast uncertainty estimation: accelerating bayesian transformers via algorithmic and hardware optimizations. DAC 2022: 325-330 - [i8]Martin Ferianc, Miguel Rodrigues:
Simple Regularisation for Uncertainty-Aware Knowledge Distillation. CoRR abs/2205.09526 (2022) - 2021
- [c9]Hongxiang Fan, Martin Ferianc, Miguel Rodrigues, Hongyu Zhou, Xinyu Niu, Wayne Luk:
High-Performance FPGA-based Accelerator for Bayesian Neural Networks. DAC 2021: 1063-1068 - [c8]Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues:
Optimizing Bayesian Recurrent Neural Networks on an FPGA-based Accelerator. FPT 2021: 1-10 - [c7]Martin Ferianc, Divyansh Manocha, Hongxiang Fan, Miguel Rodrigues:
ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation. ICANN (3) 2021: 483-494 - [c6]Martin Ferianc, Partha Maji, Matthew Mattina, Miguel Rodrigues:
On the effects of quantisation on model uncertainty in Bayesian neural networks. UAI 2021: 929-938 - [i7]Martin Ferianc, Partha Maji, Matthew Mattina, Miguel Rodrigues:
On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks. CoRR abs/2102.11062 (2021) - [i6]Martin Ferianc, Divyansh Manocha, Hongxiang Fan, Miguel Rodrigues:
ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation. CoRR abs/2104.06957 (2021) - [i5]Hongxiang Fan, Martin Ferianc, Miguel Rodrigues, Hongyu Zhou, Xinyu Niu, Wayne Luk:
High-Performance FPGA-based Accelerator for Bayesian Neural Networks. CoRR abs/2105.09163 (2021) - [i4]Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues:
High-Performance FPGA-based Accelerator for Bayesian Recurrent Neural Networks. CoRR abs/2106.06048 (2021) - [i3]Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk:
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. CoRR abs/2111.12787 (2021) - [i2]Martin Ferianc, Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Quentin Cappart:
On Causal Inference for Data-free Structured Pruning. CoRR abs/2112.10229 (2021) - 2020
- [c5]Martin Ferianc, Hongxiang Fan, Ringo S. W. Chu, Jakub Stano, Wayne Luk:
Improving Performance Estimation for FPGA-Based Accelerators for Convolutional Neural Networks. ARC 2020: 3-13 - [c4]Hongxiang Fan, Martin Ferianc, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk:
Optimizing FPGA-Based CNN Accelerator Using Differentiable Neural Architecture Search. ICCD 2020: 465-468 - [i1]Martin Ferianc, Hongxiang Fan, Miguel Rodrigues:
VINNAS: Variational Inference-based Neural Network Architecture Search. CoRR abs/2007.06103 (2020)
2010 – 2019
- 2019
- [c3]Hongxiang Fan, Cheng Luo, Chenglong Zeng, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Wayne Luk:
F-E3D: FPGA-based Acceleration of an Efficient 3D Convolutional Neural Network for Human Action Recognition. ASAP 2019: 1-8 - [c2]Hongxiang Fan, Gang Wang, Martin Ferianc, Xinyu Niu, Wayne Luk:
Static Block Floating-Point Quantization for Convolutional Neural Networks on FPGA. FPT 2019: 28-35 - 2018
- [c1]Hongxiang Fan, Shuanglong Liu, Martin Ferianc, Ho-Cheung Ng, Zhiqiang Que, Shen Liu, Xinyu Niu, Wayne Luk:
A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA. FPT 2018: 14-21
Coauthor Index
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last updated on 2024-10-11 17:25 CEST by the dblp team
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