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Seyoung Kim
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Publications
- 2023
- [c29]Minseong Um, Minil Kang, Hyunjeong Kwak, Kyungmi Noh, Seyoung Kim, Hyung-Min Lee:
An ECRAM-Based Analog Compute-in-Memory Neuromorphic System with High-Precision Current Readout. BioCAS 2023: 1-5 - 2022
- [j12]O. Murat Onen, Tayfun Gokmen, Teodor K. Todorov, Tomasz Nowicki, Jesús A. del Alamo, John Rozen, Wilfried Haensch, Seyoung Kim:
Neural Network Training With Asymmetric Crosspoint Elements. Frontiers Artif. Intell. 5: 891624 (2022) - [i10]O. Murat Onen, Tayfun Gokmen, Teodor K. Todorov, Tomasz Nowicki, Jesús A. del Alamo, John Rozen, Wilfried Haensch, Seyoung Kim:
Neural Network Training with Asymmetric Crosspoint Elements. CoRR abs/2201.13377 (2022) - 2020
- [j10]Youngseok Kim, Seyoung Kim, Chun-Chen Yeh, Vijay Narayanan, Jungwook Choi:
Hardware and Software Co-optimization for the Initialization Failure of the ReRAM-based Cross-bar Array. ACM J. Emerg. Technol. Comput. Syst. 16(4): 36:1-36:19 (2020) - [i7]Youngseok Kim, Seyoung Kim, Chun-Chen Yeh, Vijay Narayanan, Jungwook Choi:
Hardware and software co-optimization for the initialization failure of the ReRAM based cross-bar array. CoRR abs/2002.04605 (2020) - 2019
- [c20]Eduard A. Cartier, Wanki Kim, Nanbo Gong, Tayfun Gokmen, Martin M. Frank, Douglas M. Bishop, Youngseok Kim, Seyoung Kim, Takashi Ando, Ernest Y. Wu, Praneet Adusumilli, John Rozen, Paul M. Solomon, Wilfried Haensch, Matthew J. BrightSky, Abu Sebastian, Geoffrey W. Burr, Vijay Narayanan:
Reliability Challenges with Materials for Analog Computing. IRPS 2019: 1-10 - [i6]Hyungjun Kim, Malte J. Rasch, Tayfun Gokmen, Takashi Ando, Hiroyuki Miyazoe, Jae-Joon Kim, John Rozen, Seyoung Kim:
Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays. CoRR abs/1907.10228 (2019) - 2017
- [c15]Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee, Wilfried E. Haensch:
Analog CMOS-based resistive processing unit for deep neural network training. MWSCAS 2017: 422-425 - [i5]Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee, Wilfried E. Haensch:
Analog CMOS-based Resistive Processing Unit for Deep Neural Network Training. CoRR abs/1706.06620 (2017)
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