Peng Zhou

According to our database, Peng Zhou authored at least 13 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Biomimetic Spiking Neural Network Based on Monolayer 2-D Synapse With Short-Term Plasticity for Auditory Brainstem Processing.

Jieun Kim, Peng Zhou, Unbok Wi, Bomin Joo, Donguk Choi, Myeong-Lok Seol, Sravya Pulavarthi, Linfeng Sun, Heejun Yang, Woo Jong Yu, Jin-Woo Han, Sung Mo Kang, Bai-Sun Kong

IEEE Trans. Cogn. Dev. Syst., April, 2025

2024

Neuromorphic Intermediate Representation.

Jens Egholm Pedersen, Steven Abreu, Matthias Jobst, Gregor Lenz, Vittorio Fra, Felix Bauer, Dylan Richard Muir, Peng Zhou, Bernhard Vogginger, Kade M. Heckel, Sadasivan Shankar, Terrence C. Stewart, Sadique Sheik, Jason Eshraghian

Dataset, April, 2024

Deployment Pipeline from Rockpool to Xylo for Edge Computing.

Peng Zhou, Dylan R. Muir

CoRR, 2024

Scalable MatMul-free Language Modeling.

Rui-Jie Zhu, Yu Zhang, Ethan Sifferman, Tyler Sheaves, Yiqiao Wang, Dustin Richmond, Peng Zhou, Jason K. Eshraghian

CoRR, 2024

Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence.

Bo Peng, Daniel Goldstein, Quentin Anthony, Alon Albalak, Eric Alcaide, Stella Biderman, Eugene Cheah, Xingjian Du, Teddy Ferdinan, Haowen Hou, Przemyslaw Kazienko, Kranthi Kiran GV, Jan Kocon, Bartlomiej Koptyra, Satyapriya Krishna, Ronald McClelland Jr., Niklas Muennighoff, Fares Obeid, Atsushi Saito, Guangyu Song, Haoqin Tu, Stanislaw Wozniak, Ruichong Zhang, Bingchen Zhao, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu

CoRR, 2024

Gated Slot Attention for Efficient Linear-Time Sequence Modeling.

Yu Zhang, Songlin Yang, Rui-Jie Zhu, Yue Zhang, Leyang Cui, Yiqiao Wang, Bolun Wang, Freda Shi, Bailin Wang, Wei Bi, Peng Zhou, Guohong Fu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

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, Bernhard Vogginger, Kade Heckel, Gianvito Urgese, Sadasivan Shankar, Terrence C. Stewart, Jason K. Eshraghian, Sadique Sheik

CoRR, 2023

RWKV: Reinventing RNNs for the Transformer Era.

Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Huanqi Cao, Xin Cheng, Michael Chung, Matteo Grella, Kranthi Kiran G. V., Xuzheng He, Haowen Hou, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Xiangru Tang, Bolun Wang, Johan S. Wind, Stanislaw Wozniak, Ruichong Zhang, Zhenyuan Zhang, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu

CoRR, 2023

Backpropagating Errors Through Memristive Spiking Neural Networks.

Peng Zhou, Dong-Uk Choi, Sung-Mo Kang, Jason K. Eshraghian

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

2022

Gradient-Based Neuromorphic Learning on Dynamical RRAM Arrays.

Peng Zhou, Dong-Uk Choi, Wei D. Lu, Sung-Mo Steve Kang, Jason Kamran Eshraghian

IEEE J. Emerg. Sel. Topics Circuits Syst., 2022

SPICEprop: Backpropagating Errors Through Memristive Spiking Neural Networks.

Peng Zhou, Jason Kamran Eshraghian, Dong-Uk Choi, Sung-Mo Kang

CoRR, 2022

A Fully Memristive Spiking Neural Network with Unsupervised Learning.

Peng Zhou, Dong-Uk Choi, Jason Kamran Eshraghian, Sung-Mo Kang

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

2021

How to Build a Memristive Integrate-and-Fire Model for Spiking Neuronal Signal Generation.

Sung-Mo Steve Kang, Donguk Choi, Jason Kamran Eshraghian, Peng Zhou, Jieun Kim, Bai-Sun Kong, Xiaojian Zhu, Ahmet Samil Demirkol, Alon Ascoli, Ronald Tetzlaff, Wei D. Lu, Leon O. Chua

IEEE Trans. Circuits Syst. I Regul. Pap., 2021