X-TrainCaps: Accelerated Training of Capsule Nets through Lightweight Software Optimizations. - Alberto Marchisio; Beatrice Bussolino; Alessio Colucci; Muhammad Abdullah Hanif; Maurizio Martina; Guido Masera; Muhammad Shafique 001 (CoRR, 2019)

A Fast Design Space Exploration Framework for the Deep Learning Accelerators: Work-in-Progress. - Alessio Colucci; Alberto Marchisio; Beatrice Bussolino; Vojtech Mrazek; Maurizio Martina; Guido Masera; Muhammad Shafique 001 (CODES+ISSS, 2020)

Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks. - Alberto Marchisio; Beatrice Bussolino; Alessio Colucci; Maurizio Martina; Guido Masera; Muhammad Shafique 001 (DAC, 2020)

NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule Networks. - Alberto Marchisio; Andrea Massa; Vojtech Mrazek; Beatrice Bussolino; Maurizio Martina; Muhammad Shafique 001 (ICCAD, 2020)

FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks. - Alberto Marchisio; Beatrice Bussolino; Alessio Colucci; Muhammad Abdullah Hanif; Maurizio Martina; Guido Masera; Muhammad Shafique 001 (IJCNN, 2020)

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead. - Maurizio Capra; Beatrice Bussolino; Alberto Marchisio; Guido Masera; Maurizio Martina; Muhammad Shafique 001 (IEEE Access, 2020)

An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks. - Maurizio Capra; Beatrice Bussolino; Alberto Marchisio; Muhammad Shafique 001; Guido Masera; Maurizio Martina (Future Internet, 2020)

NLCMAP: A Framework for the Efficient Mapping of Non-Linear Convolutional Neural Networks on FPGA Accelerators. - Giuseppe Aiello; Beatrice Bussolino; Emanuele Valpreda; Massimo Ruo Roch; Guido Masera; Maurizio Martina; Stefano Marsi (ICIP, 2022)

Enabling Capsule Networks at the Edge through Approximate Softmax and Squash Operations. - Alberto Marchisio; Beatrice Bussolino; Edoardo Salvati; Maurizio Martina; Guido Masera; Muhammad Shafique 001 (ISLPED, 2022)

Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tiles. - Renzo Andri; Beatrice Bussolino; Antonio Cipolletta; Lukas Cavigelli; Zhe Wang 023 (MICRO, 2022)

RoHNAS: A Neural Architecture Search Framework With Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks. - Alberto Marchisio; Vojtech Mrazek; Andrea Massa; Beatrice Bussolino; Maurizio Martina; Muhammad Shafique 001 (IEEE Access, 2022)

Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tile. - Renzo Andri; Beatrice Bussolino; Antonio Cipolletta; Lukas Cavigelli; Zhe Wang 023 (CoRR, 2022)

11.3 Metis AIPU: A 12nm 15TOPS/W 209.6TOPS SoC for Cost- and Energy-Efficient Inference at the Edge. - Pascal Alexander Hager; Bert Moons; Stefan Cosemans; Ioannis A. Papistas; Bram Rooseleer; Jeroen Van Loon; Roel Uytterhoeven; Florian Zaruba; Spyridoula Koumousi; Milos Stanisavljevic; Stefan Mach; Sebastiaan Mutsaards; et al. (ISSCC, 2024)