General-purpose LSM learning processor architecture and theoretically guided design space exploration. - Qian Wang 003; Yingyezhe Jin; Peng Li 001 (BioCAS, 2015)

A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition. - Yong Zhang 049; Peng Li 001; Yingyezhe Jin; Yoonsuck Choe (IEEE Trans. Neural Networks Learn. Syst., 2015)

AP-STDP: A novel self-organizing mechanism for efficient reservoir computing. - Yingyezhe Jin; Peng Li 001 (IJCNN, 2016)

SSO-LSM: A Sparse and Self-Organizing architecture for Liquid State Machine based neural processors. - Yingyezhe Jin; Yu Liu 028; Peng Li 001 (NANOARCH, 2016)

Calcium-modulated supervised spike-timing-dependent plasticity for readout training and sparsification of the liquid state machine. - Yingyezhe Jin; Peng Li 001 (IJCNN, 2017)

Exploring sparsity of firing activities and clock gating for energy-efficient recurrent spiking neural processors. - Yu Liu 028; Yingyezhe Jin; Peng Li 001 (ISLPED, 2017)

Performance and robustness of bio-inspired digital liquid state machines: A case study of speech recognition. - Yingyezhe Jin; Peng Li 001 (Neurocomputing, 2017)

Design and architectural co-optimization of monolithic 3D liquid state machine-based neuromorphic processor. - Bon Woong Ku; Yu Liu 028; Yingyezhe Jin; Sandeep Kumar Samal; Peng Li 001; Sung Kyu Lim (DAC, 2018)

Area-efficient and low-power face-to-face-bonded 3D liquid state machine design. - Bon Woong Ku; Yu Liu 028; Yingyezhe Jin; Peng Li 001; Sung Kyu Lim (ICCAD, 2018)

Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks. - Yingyezhe Jin; Wenrui Zhang; Peng Li 001 (NeurIPS, 2018)

Online Adaptation and Energy Minimization for Hardware Recurrent Spiking Neural Networks. - Yu Liu 028; Yingyezhe Jin; Peng Li 001 (ACM J. Emerg. Technol. Comput. Syst., 2018)

Deep Entity Classification: Abusive Account Detection for Online Social Networks. - Teng Xu 009; Gerard Goossen; Huseyin Kerem Cevahir; Sara Khodeir; Yingyezhe Jin; Frank Li 001; Shawn Shan; Sagar Patel; David Freeman 001; Paul Pearce (USENIX Security Symposium, 2021)