Guangzhi Tang

According to our database, Guangzhi Tang authored at least 18 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Benchmarking of hardware-efficient real-time neural decoding in brain-computer interfaces.

Paul Hueber, Guangzhi Tang, Manolis Sifalakis, Hua-Peng Liaw, Aurora Micheli, Nergis Tomen, Yao-Hong Liu

Neuromorph. Comput. Eng., 2024

Overcoming the Limitations of Layer Synchronization in Spiking Neural Networks.

Roel Koopman, Amirreza Yousefzadeh, Mahyar Shahsavari, Guangzhi Tang, Manolis Sifalakis

CoRR, 2024

Event-based Optical Flow on Neuromorphic Processor: ANN vs. SNN Comparison based on Activation Sparsification.

Yingfu Xu, Guangzhi Tang, Amirreza Yousefzadeh, Guido de Croon, Manolis Sifalakis

CoRR, 2024

EON-1: A Brain-Inspired Processor for Near-Sensor Extreme Edge Online Feature Extraction.

Alexandra F. Dobrita, Amirreza Yousefzadeh, Simon Thorpe, Kanishkan Vadivel, Paul Detterer, Guangzhi Tang, Gert-Jan van Schaik, Mario Konijnenburg, Anteneh Gebregiorgis, Said Hamdioui, Manolis Sifalakis

CoRR, 2024

SENSIM: An Event-driven Parallel Simulator for Multi-core Neuromorphic Systems.

Prithvish Nembhani, Kanishkan Vadivel, Guangzhi Tang, Mohammad Tahghighi, Gert-Jan van Schaik, Manolis Sifalakis, Zaid Al-Ars, Amirreza Yousefzadeh

Proceedings of the International Joint Conference on Neural Networks, 2024

TRIP: Trainable Region-of-Interest Prediction for Hardware-Efficient Neuromorphic Processing on Event-Based Vision.

Cina Arjmand, Yingfu Xu, Kevin Shidqi, Alexandra F. Dobrita, Kanishkan Vadivel, Paul Detterer, Manolis Sifalakis, Amirreza Yousefzadeh, Guangzhi Tang

Proceedings of the International Conference on Neuromorphic Systems, 2024

2023

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, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Michael Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi

CoRR, 2023

Open the box of digital neuromorphic processor: Towards effective algorithm-hardware co-design.

Guangzhi Tang, Ali Safa, Kevin Shidqi, Paul Detterer, Stefano Traferro, Mario Konijnenburg, Manolis Sifalakis, Gert-Jan van Schaik, Amirreza Yousefzadeh

Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

Empirical study on the efficiency of Spiking Neural Networks with axonal delays, and algorithm-hardware benchmarking.

Alberto Patiño-Saucedo, Amirreza Yousefzadeh, Guangzhi Tang, Federico Corradi, Bernabé Linares-Barranco, Manolis Sifalakis

Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

2022

Decoding EEG With Spiking Neural Networks on Neuromorphic Hardware.

Neelesh Kumar, Guangzhi Tang, Raymond Yoo, Konstantinos P. Michmizos

Trans. Mach. Learn. Res., 2022

2021

BioGrad: Biologically Plausible Gradient-Based Learning for Spiking Neural Networks.

Guangzhi Tang, Neelesh Kumar, Ioannis Polykretis, Konstantinos P. Michmizos

CoRR, 2021

2020

Real-time Mapping on a Neuromorphic Processor.

Guangzhi Tang, Konstantinos P. Michmizos

Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020

Reinforcement co-Learning of Deep and Spiking Neural Networks for Energy-Efficient Mapless Navigation with Neuromorphic Hardware.

Guangzhi Tang, Neelesh Kumar, Konstantinos P. Michmizos

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel's Loihi.

Ioannis Polykretis, Guangzhi Tang, Konstantinos P. Michmizos

Proceedings of the International Conference on Neuromorphic Systems, 2020

Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control.

Guangzhi Tang, Neelesh Kumar, Raymond Yoo, Konstantinos P. Michmizos

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Introducing Astrocytes on a Neuromorphic Processor: Synchronization, Local Plasticity and Edge of Chaos.

Guangzhi Tang, Ioannis E. Polykretis, Vladimir A. Ivanov, Arpit Shah, Konstantinos P. Michmizos

CoRR, 2019

Spiking Neural Network on Neuromorphic Hardware for Energy-Efficient Unidimensional SLAM.

Guangzhi Tang, Arpit Shah, Konstantinos P. Michmizos

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

2018

Gridbot: An autonomous robot controlled by a Spiking Neural Network mimicking the brain's navigational system.

Guangzhi Tang, Konstantinos P. Michmizos

CoRR, 2018