Characterization of the role of collagen network structure and composition in cancer cell migration. - María Anguiano; Carlos Castilla; Martin Maska; Cristina Ederra; Javier Fernández-Marqués; Rafael Peláez; Ana Rouzaut; Arrate Muñoz-Barrutia; Michal Kozubek 001; Carlos Ortiz-de-Solorzano (EMBC, 2015)

Quantification of the 3D collagen network geometry in confocal reflection microscopy. - Martin Maska; Cristina Ederra; Javier Fernández-Marqués; Arrate Muñoz-Barrutia; Michal Kozubek 001; Carlos Ortiz-de-Solorzano (ICIP, 2015)

Deterministic Binary Filters for Convolutional Neural Networks. - Vincent W. S. Tseng; Sourav Bhattacharya; Javier Fernández-Marqués; Milad Alizadeh; Catherine Tong; Nicholas D. Lane (IJCAI, 2018)

Deterministic binary filters for keyword spotting applications. - Javier Fernández-Marqués; Vincent W. S. Tseng; Sourav Bhattacharya; Nicholas D. Lane (MobiSys, 2018)

On-the-fly deterministic binary filters for memory efficient keyword spotting applications on embedded devices. - Javier Fernández-Marqués; Vincent W. S. Tseng; Sourav Bhattacharya; Nicholas D. Lane (EMDL@MobiSys, 2018)

An Empirical study of Binary Neural Networks' Optimisation. - Milad Alizadeh; Javier Fernández-Marqués; Nicholas D. Lane; Yarin Gal (ICLR (Poster), 2019)

Searching for Winograd-aware Quantized Networks. - Javier Fernández-Marqués; Paul N. Whatmough; Andrew Mundy; Matthew Mattina (MLSys, 2020)

unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation. - Stylianos I. Venieris; Javier Fernández-Marqués; Nicholas D. Lane (FCCM, 2021)

Degree-Quant: Quantization-Aware Training for Graph Neural Networks. - Shyam Anil Tailor; Javier Fernández-Marqués; Nicholas Donald Lane (ICLR, 2021)

A first look into the carbon footprint of federated learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (CoRR, 2021)

On-device Federated Learning with Flower. - Akhil Mathur; Daniel J. Beutel; Pedro Porto Buarque de Gusmão; Javier Fernández-Marqués; Taner Topal; Xinchi Qiu; Titouan Parcollet; Yan Gao 016; Nicholas D. Lane (CoRR, 2021)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (CoRR, 2021)

Deep learning on microcontrollers: a study on deployment costs and challenges. - Filip Svoboda; Javier Fernández-Marqués; Edgar Liberis; Nicholas D. Lane (EuroMLSys@EuroSys, 2022)

Protea: client profiling within federated systems using flower. - Wanru Zhao; Xinchi Qiu; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Nicholas D. Lane (FedEdge@MobiCom, 2022)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Salah Zaiem; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (ICASSP, 2022)

ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity. - Xinchi Qiu; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Yan Gao 016; Titouan Parcollet; Nicholas Donald Lane (ICLR, 2022)

Federated Self-supervised Speech Representations: Are We There Yet? - Yan Gao 016; Javier Fernández-Marqués; Titouan Parcollet; Abhinav Mehrotra; Nicholas D. Lane (INTERSPEECH, 2022)

Match to Win: Analysing Sequences Lengths for Efficient Self-Supervised Learning in Speech and Audio. - Yan Gao 016; Javier Fernández-Marqués; Titouan Parcollet; Pedro P. B. de Gusmao; Nicholas D. Lane (SLT, 2022)

FedorAS: Federated Architecture Search under system heterogeneity. - Lukasz Dudziak; Stefanos Laskaridis; Javier Fernández-Marqués (CoRR, 2022)

Federated Learning for Inference at Anytime and Anywhere. - Zicheng Liu 006; Da Li 001; Javier Fernández-Marqués; Stefanos Laskaridis; Yan Gao 016; Lukasz Dudziak; Stan Z. Li; Shell Xu Hu; Timothy M. Hospedales (CoRR, 2022)

Are We There Yet? Product Quantization and its Hardware Acceleration. - Javier Fernández-Marqués; Ahmed F. AbouElhamayed; Nicholas D. Lane; Mohamed S. Abdelfattah (CoRR, 2023)

High-throughput Simulation of Federated Learning via Resource-Aware Client Placement. - Lorenzo Sani; Pedro Porto Buarque de Gusmão; Alex Iacob; Wanru Zhao; Xinchi Qiu; Yan Gao 016; Javier Fernández-Marqués; Nicholas Donald Lane (CoRR, 2023)

How Much Is Hidden in the NAS Benchmarks? Few-Shot Adaptation of a NAS Predictor. - Hrushikesh Loya; Lukasz Dudziak; Abhinav Mehrotra; Royson Lee; Javier Fernández-Marqués; Nicholas D. Lane; Hongkai Wen 001 (CoRR, 2023)

A First Look into the Carbon Footprint of Federated Learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Yan Gao 016; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (J. Mach. Learn. Res., 2023)

Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation. - Stylianos I. Venieris; Javier Fernández-Marqués; Nicholas D. Lane (ACM Trans. Design Autom. Electr. Syst., 2023)

Recurrent Early Exits for Federated Learning with Heterogeneous Clients. - Royson Lee; Javier Fernández-Marqués; Shell Xu Hu; Da Li 001; Stefanos Laskaridis; Lukasz Dudziak; Timothy M. Hospedales; Ferenc Huszár; Nicholas Donald Lane (ICML, 2024)

Privacy-Preserving Federated Learning using Flower Framework. - Mohammad Naseri; Javier Fernández-Marqués; Yan Gao 016; Heng Pan (KDD, 2024)

Supercharging Federated Learning with Flower and NVIDIA FLARE. - Holger R. Roth; Daniel J. Beutel; Yan Cheng; Javier Fernández-Marqués; Heng Pan; Chester Chen; Zhihong Zhang 001; Yuhong Wen; Sean Yang; Isaac Yang; Yuan-Ting Hsieh; Ziyue Xu 001; et al. (CoRR, 2024)

PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration. - Ahmed F. AbouElhamayed; Angela Cui; Javier Fernández-Marqués; Nicholas D. Lane; Mohamed S. Abdelfattah (ACM Trans. Reconfigurable Technol. Syst., 2025)

FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. - Yan Gao 016; Massimo Roberto Scamarcia; Javier Fernández-Marqués; Mohammad Naseri; Chong Shen Ng; Dimitris Stripelis; Zexi Li; Tao Shen; Jiamu Bai; Daoyuan Chen; Zikai Zhang; Rui Hu; et al. (CoRR, 2025)