LUMOR: An App for Standardized Control and Monitoring of a Porcine Lung and its Nutrient Cycle. - Gregor Lenz; Matthias Frohner; Stefan Sauermann; Mathias Forjan (eHealth, 2014)

Event-based Dynamic Face Detection and Tracking Based on Activity. - Gregor Lenz; Sio-Hoi Ieng; Ryad Benosman (CoRR, 2018)

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction. - Antonios Makropoulos; Emma C. Robinson; Andreas Schuh; Robert Wright; Sean P. Fitzgibbon; Jelena Bozek; Serena J. Counsell; Johannes K. Steinweg; Katy Vecchiato; Jonathan Passerat-Palmbach; Gregor Lenz; Filippo Mortari; et al. (NeuroImage, 2018)

Event-based Visual Gesture Recognition with Background Suppression running on a smart-phone. - Jean-Matthieu Maro; Gregor Lenz; Christopher Reeves; Ryad Benosman (FG, 2019)

A Mixed-Signal Spatio-Temporal Signal Classifier for On-Sensor Spike Sorting. - Germain Haessig; Daniel García-Lesta; Gregor Lenz; Ryad Benosman; Piotr Dudek (ISCAS, 2020)

Adversarial Attacks on Spiking Convolutional Networks for Event-based Vision. - Julian Büchel; Gregor Lenz; Yalun Hu; Sadique Sheik; Martino Sorbaro 001 (CoRR, 2021)

Neuromorphic algorithms and hardware for event-based processing. (Algorithmes et architectures matérielles neuromorphiques pour le calcul évènementiel). - Gregor Lenz (2021)

A sampling-based approach for efficient clustering in large datasets. - Georgios Exarchakis; Omar Oubari; Gregor Lenz (CVPR, 2022)

A Framework for Event-based Computer Vision on a Mobile Device. - Gregor Lenz; Serge Picaud; Sio-Hoi Ieng (CoRR, 2022)

EXODUS: Stable and Efficient Training of Spiking Neural Networks. - Felix Christian Bauer; Gregor Lenz; Saeid Haghighatshoar; Sadique Sheik (CoRR, 2022)

Efficient spatio-temporal feature clustering for large event-based datasets. - Omar Oubari; Georgios Exarchakis; Gregor Lenz; Ryad Benosman; Sio-Hoi Ieng (Neuromorph. Comput. Eng., 2022)

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. - Jason Yik; Soikat Hasan Ahmed; Zergham Ahmed; Brian Anderson; Andreas G. Andreou; Chiara Bartolozzi; Arindam Basu; Douwe den Blanken; Petrut Bogdan; Sander M. Bohté; Younes Bouhadjar; Sonia M. Buckley; et al. (CoRR, 2023)

Ultra-low-power Image Classification on Neuromorphic Hardware. - Gregor Lenz; Garrick Orchard; Sadique Sheik (CoRR, 2023)

Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing. - Jens Egholm Pedersen; Steven Abreu; Matthias Jobst; Gregor Lenz; Vittorio Fra; Felix Christian Bauer; Dylan R. Muir; Peng Zhou 017; Bernhard Vogginger; Kade Heckel; Gianvito Urgese; Sadasivan Shankar; et al. (CoRR, 2023)

Neuromorphic Intermediate Representation. - Steven Abreu; Felix Christian Bauer; Jason Eshraghian; Matthias Jobst; Gregor Lenz; Jens Egholm Pedersen; Sadique Sheik (Zenodo, 2023)

Training Spiking Neural Networks Using Lessons From Deep Learning. - Jason K. Eshraghian; Max Ward 001; Emre O. Neftci; Xinxin Wang 002; Gregor Lenz; Girish Dwivedi; Mohammed Bennamoun; Doo Seok Jeong; Wei D. Lu (Proc. IEEE, 2023)

Neuromorphic Intermediate Representation. - Steven Abreu; Felix Christian Bauer; Jason Eshraghian; Matthias Jobst; Gregor Lenz; Jens Egholm Pedersen; Sadique Sheik (Zenodo, 2023)

Low-power Ship Detection in Satellite Images Using Neuromorphic Hardware. - Gregor Lenz; Douglas McLelland (CoRR, 2024)

Neuromorphic Intermediate Representation. - Jens Egholm Pedersen; Steven Abreu; Matthias Jobst; Gregor Lenz; Vittorio Fra; Felix Bauer; Dylan Richard Muir; Peng Zhou 017; Bernhard Vogginger; Kade M. Heckel; Sadasivan Shankar; Terrence C. Stewart; et al. (Zenodo, 2024)