Martin Ferianc

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 32

Top Topics

Network Architecture

Variational Inference

Top Venues

Publications

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)
Martin Ferianc, Miguel Rodrigues
YAMLE: Yet Another Machine Learning Environment. CoRR (2024)
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 (2024)
Martin Ferianc, Hongxiang Fan, Miguel Rodrigues
SAE: Single Architecture Ensemble Neural Networks. CoRR (2024)
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 (2024)
Martin Ferianc, Miguel Rodrigues
MIMMO: Multi-Input Massive Multi-Output Neural Network. CVPR Workshops (2023)
Martin Wistuba, Martin Ferianc, Lukas Balles, Cédric Archambeau, Giovanni Zappella
Renate: A Library for Real-World Continual Learning. CoRR (2023)
Vittorio Casagrande, Martin Ferianc, Miguel Rodrigues, Francesca Boem
. MED (2023)
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 (2023)
Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues
Impact of Noise on Calibration and Generalisation of Neural Networks. CoRR (2023)
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)
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) (2022)
Hongxiang Fan, Martin Ferianc, Wayne Luk
Enabling fast uncertainty estimation: accelerating bayesian transformers via algorithmic and hardware optimizations. DAC (2022)
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) (2022)
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) (2022)
Martin Ferianc, Miguel Rodrigues
Simple Regularisation for Uncertainty-Aware Knowledge Distillation. CoRR (2022)
Hongxiang Fan, Martin Ferianc, Miguel Rodrigues, Hongyu Zhou, Xinyu Niu, Wayne Luk
High-Performance FPGA-based Accelerator for Bayesian Neural Networks. DAC (2021)
Martin Ferianc, Divyansh Manocha, Hongxiang Fan, Miguel Rodrigues
ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation. CoRR (2021)
Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues
Optimizing Bayesian Recurrent Neural Networks on an FPGA-based Accelerator. FPT (2021)
Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. CoRR (2021)
Hongxiang Fan, Martin Ferianc, Miguel Rodrigues, Hongyu Zhou, Xinyu Niu, Wayne Luk
High-Performance FPGA-based Accelerator for Bayesian Neural Networks. CoRR (2021)
Martin Ferianc, Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Quentin Cappart
On Causal Inference for Data-free Structured Pruning. CoRR (2021)
Martin Ferianc, Divyansh Manocha, Hongxiang Fan, Miguel Rodrigues
ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation. ICANN (3) (2021)
Martin Ferianc, Partha Maji, Matthew Mattina, Miguel Rodrigues
On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks. CoRR (2021)
Martin Ferianc, Partha Maji, Matthew Mattina, Miguel Rodrigues
On the effects of quantisation on model uncertainty in Bayesian neural networks. UAI (2021)
Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues
High-Performance FPGA-based Accelerator for Bayesian Recurrent Neural Networks. CoRR (2021)
Martin Ferianc, Hongxiang Fan, Miguel Rodrigues
VINNAS: Variational Inference-based Neural Network Architecture Search. CoRR (2020)
Hongxiang Fan, Martin Ferianc, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk
Optimizing FPGA-Based CNN Accelerator Using Differentiable Neural Architecture Search. ICCD (2020)
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)
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)
Hongxiang Fan, Gang Wang, Martin Ferianc, Xinyu Niu, Wayne Luk
Static Block Floating-Point Quantization for Convolutional Neural Networks on FPGA. FPT (2019)
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)